Singapore Economic Review Conference 2026

July 28, 2026
Time	Location	Event
07:30 to 09:00	Foyer (outside Ballroom 1 and 2, level 3)	Registration
09:00 to 10:45	Ballroom 1 (level 3)	Opening Plenary (Plenary 1) and Keynote
10:45 to 11:30	Foyer (outside Ballroom 1 and 2, level 3)	Morning Tea
11:30 to 12:50	Ballroom 1 (level 3)	Plenary 2: International Security in a Fractured Global Economy: The Middle East Crisis and Beyond (EGC Plenary)
12:50 to 14:00	Foyer (outside Ballroom 1 and 2, level 3)	Lunch
14:00 to 15:20	Ballroom 1 (level 3)	Plenary 3: Growth of Asia: What’s Next (ESS Plenary)
15:20 to 15:50	Foyer (outside Ballroom 1 and 2, level 3)	Afternoon Tea
15:50 to 17:10		Distinguished/Invited I, Level 5 breakout rooms
17:10 to 17:20	Level 5 breakout rooms	Transition/buffer, Level 5 breakout rooms
17:20 to 18:50		Parallel 1, Level 5 breakout rooms
18:50 to 19:30	Foyer (outside Ballroom 1 and 2, level 3)	Free time before Conference Dinner
19:30 to 22:00	Vista Room (level 3)	Conference Dinner
July 29, 2026
Time	Location	Event
08:00 to 08:30	Foyer (outside Ballroom 1 and 2, level 3)	Registration
08:30 to 10:00		Parallel 2, Level 5 breakout rooms
10:00 to 10:30	Foyer (outside Ballroom 1 and 2, level 3)	Morning Tea
10:30 to 11:50	Ballroom 1 (level 3)	(Plenary 4) Distinguished Albert Winsemius Lecture: Dale Whittington
11:50 to 13:00	Foyer (outside Ballroom 1 and 2, level 3)	Lunch
13:00 to 14:20	Ballroom 1 (level 3)	Plenary 5: Green economy, Sustainability, Environment and Climate Change Issues (MTI Plenary)
14:20 to 14:30	Ballroom 1 (level 3)	Transition/buffer
14:30 to 15:40	Ballroom 1 (level 3)	Plenary 6: Changing Global Monetary Landscape (MAS Plenary)
15:40 to 16:10	Foyer (outside Ballroom 1 and 2, level 3)	Afternoon Tea
16:10 to 17:20	Ballroom 1 (level 3)	Plenary 7: Momentum of the Chinese Economy (China Changing or Changing Global)
17:20 to 17:30	Level 5 breakout rooms	Transition/buffer, Level 5 breakout rooms
17:30 to 19:00		Parallel 3, Level 5 breakout rooms
July 30, 2026
Time	Location	Event
08:00 to 08:30	Foyer (outside Ballroom 1 and 2, level 3)	Registration
08:30 to 10:00		Parallel 4, Level 5 breakout rooms
10:00 to 10:30	Foyer (outside Ballroom 1 and 2, level 3)	Morning Tea
10:30 to 11:40	Ballroom 1 (level 3)	Plenary 8: The Challenge of Declining Fertility Rates
11:40 to 12:40	Foyer (outside Ballroom 1 and 2, level 3)	Lunch
12:40 to 13:50		Parallel 5, Level 5 breakout rooms
13:50 to 14:00	Level 5 breakout rooms	Transition/buffer, Level 5 breakout rooms
14:00 to 15:30		Parallel 6, Level 5 breakout rooms
15:30 to 16:40	Ballroom 1 (level 3)	Afternoon Tea + Tips on Publishing and "ask me anything"
16:40 to 18:10		Parallel 7, Level 5 breakout rooms
18:10 to 18:20	Level 5 breakout rooms	Transition/buffer, Level 5 breakout rooms
18:20 to 19:30		Parallel 8, Level 5 breakout rooms

Summary of All Sessions
Click here for an index of all participants

#	Date/Time	Type	Title/Location	Papers
1	July 28, 2026 9:00-10:45	panel	Opening Plenary - MND Minister Chee Hong Tat and Prof. Jeffrey Sachs     Location: Ballroom 1 (level 3)
2	July 28, 2026 11:30-12:50	plenary	Plenary: International Security in a Fractured Global Economy: The Middle East Crisis and Beyond (EGC Plenary)     Location: Ballroom 1 (level 3)	0
3	July 28, 2026 14:00-15:20	panel	ESS Plenary: Growth of Asia: What’s Next     Location: Ballroom 1 (level 3)	0
4	July 28, 2026 15:50-17:10	invited	Invited 1.1: Technology and A.I.     Location: Singapore Room (level 5)	3
5	July 28, 2026 15:50-17:10	invited	Invited 1.2: Environment and Green Economy     Location: Thailand Room (level 5)	4
6	July 28, 2026 15:50-17:10	invited	Invited 1.3: Econometrics     Location: Malaysia Room (level 5)	1
7	July 28, 2026 15:50-17:10	invited	Invited 1.4: Political Economy     Location: Indonesia Room (level 5)	4
8	July 28, 2026 15:50-17:10	invited	Invited 1.5: Behavioral and Experimental     Location: Philippines Room (level 5)	1
9	July 28, 2026 15:50-17:10	invited	Invited 1.6: Social and Developmental     Location: Brunei Room (level 5)	4
10	July 28, 2026 15:50-17:10	invited	Invited 1.7: Macroeconomics, Labor and Household Consumption     Location: Vietnam Room (level 5)	4
11	July 28, 2026 15:50-17:10	invited	Invited 1.8: Banking and Finance     Location: Cambodia Room (level 5)	2
12	July 28, 2026 17:20-18:50	invited	Behavioral I - Individual Decision     Location: Singapore Room (level 5)	4
13	July 28, 2026 17:20-18:50	invited	Development I     Location: Thailand Room (level 5)	4
14	July 28, 2026 17:20-18:50	invited	Econometrics I     Location: Malaysia Room (level 5)	4
15	July 28, 2026 17:20-18:50		Education I     Location: Indonesia Room (level 5)	4
16	July 28, 2026 17:20-18:50	invited	Financial I     Location: Philippines Room (level 5)	4
17	July 28, 2026 17:20-18:50	invited	Industrial Organization I     Location: Cambodia Room (level 5)	4
18	July 28, 2026 17:20-18:50	invited	Labor I     Location: Brunei Room (level 5)	4
19	July 28, 2026 17:20-18:50		Macroeconomics I - Monetary     Location: Vietnam Room (level 5)	4
20	July 29, 2026 8:30-10:00	invited	Asian I     Location: Cambodia Room (level 5)	4
21	July 29, 2026 8:30-10:00		Econometrics II     Location: Singapore Room (level 5)	4
22	July 29, 2026 8:30-10:00	invited	Environmental I     Location: Thailand Room (level 5)	4
23	July 29, 2026 8:30-10:00	invited	Financial II     Location: Vietnam Room (level 5)	4
24	July 29, 2026 8:30-10:00	invited	International I - International Finance     Location: Malaysia Room (level 5)	4
25	July 29, 2026 8:30-10:00		Public I - Fiscal     Location: Indonesia Room (level 5)	4
26	July 29, 2026 8:30-10:00	invited	Standard of Living, Well-being, Altruism and Happiness     Location: Brunei Room (level 5)	4
27	July 29, 2026 8:30-10:00	invited	Technology and Innovation I     Location: Philippines Room (level 5)	4
28	July 29, 2026 10:30-11:50	plenary	(Plenary) Distinguished Albert Winsemius Lecture: Dale Whittington     Location: Ballroom 1 (level 3)	1
29	July 29, 2026 13:00-14:20	panel	MTI Plenary: Green economy, Sustainability, Environment and Climate Change Issues     Location: Ballroom 1 (level 3)	0
30	July 29, 2026 14:30-15:40	invited	MAS Plenary: Changing Global Monetary Landscape     Location: Ballroom 1 (level 3)	0
31	July 29, 2026 16:10-17:20	invited	Plenary: Momentum of the Chinese Economy (China Changing or Changing Global)     Location: Ballroom 1 (level 3)	0
32	July 29, 2026 17:30-19:00	invited	Asian II     Location: Cambodia Room (level 5)	4
33	July 29, 2026 17:30-19:00	invited	Behavioral II     Location: Singapore Room (level 5)	4
34	July 29, 2026 17:30-19:00	invited	Development II     Location: Thailand Room (level 5)	4
35	July 29, 2026 17:30-19:00	invited	Environmental II: Efficiency, Productivity and Sustainability     Location: Malaysia Room (level 5)	4
36	July 29, 2026 17:30-19:00	invited	Financial III - Banking     Location: Indonesia Room (level 5)	4
37	July 29, 2026 17:30-19:00	invited	Labor II     Location: Philippines Room (level 5)	4
38	July 29, 2026 17:30-19:00	invited	Macroeconomics II     Location: Brunei Room (level 5)	4
39	July 29, 2026 17:30-19:00	invited	Urban I     Location: Vietnam Room (level 5)	4
40	July 30, 2026 8:30-10:00	contributed	AI and Digital Markets I     Location: Cambodia Room (level 5)	4
41	July 30, 2026 8:30-10:00	invited	Development III     Location: Singapore Room (level 5)	4
42	July 30, 2026 8:30-10:00	invited	Empirical I     Location: Thailand Room (level 5)	4
43	July 30, 2026 8:30-10:00	invited	Environmental III     Location: Malaysia Room (level 5)	4
44	July 30, 2026 8:30-10:00	invited	Financial IV - Corporate Finance     Location: Indonesia Room (level 5)	4
45	July 30, 2026 8:30-10:00	invited	Labor III     Location: Philippines Room (level 5)	3
46	July 30, 2026 8:30-10:00	invited	Public II     Location: Vietnam Room (level 5)	4
47	July 30, 2026 8:30-10:00	invited	Technology and Innovation II - Agricultural     Location: Brunei Room (level 5)	4
48	July 30, 2026 10:30-11:40	plenary	Plenary: The Challenge of Declining Fertility Rates     Location: Ballroom 1 (level 3)	0
49	July 30, 2026 12:40-13:50	invited	Asian III     Location: Cambodia Room (level 5)	2
50	July 30, 2026 12:40-13:50	invited	Energy I     Location: Singapore Room (level 5)	3
51	July 30, 2026 12:40-13:50	invited	Environmental IV     Location: Thailand Room (level 5)	3
52	July 30, 2026 12:40-13:50	invited	Industrial Organization II     Location: Malaysia Room (level 5)	3
53	July 30, 2026 12:40-13:50	invited	International II - Growth     Location: Indonesia Room (level 5)	3
54	July 30, 2026 12:40-13:50		Pandemic I     Location: Philippines Room (level 5)	2
55	July 30, 2026 12:40-13:50		Political I     Location: Brunei Room (level 5)	3
56	July 30, 2026 12:40-13:50	invited	AI and Digital Markets II     Location: Vietnam Room (level 5)	3
57	July 30, 2026 14:00-15:30	invited	AI and Digital Markets III     Location: Singapore Room (level 5)	4
58	July 30, 2026 14:00-15:30	invited	Asian IV     Location: Cambodia Room (level 5)	3
59	July 30, 2026 14:00-15:30	invited	Econometrics III     Location: Thailand Room (level 5)	4
60	July 30, 2026 14:00-15:30	invited	Environmental V     Location: Malaysia Room (level 5)	4
61	July 30, 2026 14:00-15:30	invited	Empirical II     Location: Indonesia Room (level 5)	3
62	July 30, 2026 14:00-15:30	invited	Energy II     Location: Philippines Room (level 5)	4
63	July 30, 2026 14:00-15:30		International III - Trade     Location: Brunei Room (level 5)	4
64	July 30, 2026 14:00-15:30	invited	Labor IV     Location: Vietnam Room (level 5)	4
65	July 30, 2026 15:30-16:40	invited	Editors' Tea Reception (Tips on Publishing and ask me anything)     Location: Ballroom 1 (level 3)	0
66	July 30, 2026 16:40-18:10	invited	AI and Digital Markets IV     Location: Cambodia Room (level 5)	4
67	July 30, 2026 16:40-18:10	invited	Econometrics IV (Applied): Data, Mobility and Innovation in Cities     Location: Singapore Room (level 5)	3
68	July 30, 2026 16:40-18:10	invited	Financial V - Stock Market     Location: Thailand Room (level 5)	4
69	July 30, 2026 16:40-18:10	invited	International IV     Location: Indonesia Room (level 5)	3
70	July 30, 2026 16:40-18:10	invited	Labor V     Location: Philippines Room (level 5)	3
71	July 30, 2026 16:40-18:10	invited	Public III - Taxation     Location: Brunei Room (level 5)	4
72	July 30, 2026 16:40-18:10		Technology and Innovation III     Location: Malaysia Room (level 5)	3
73	July 30, 2026 16:40-18:10	invited	Urban II     Location: Vietnam Room (level 5)	4

 

73 sessions, 231 papers, and 0 presentations with no associated papers

Singapore Economic Review Conference 2026
Detailed List of Sessions

                                                                                                                                                  

Session 1: Opening Plenary - MND Minister Chee Hong Tat and Prof. Jeffrey Sachs July 28, 2026 9:00 to 10:45 Location: Ballroom 1 (level 3)
Session Chair: Euston Quah, Nanyang Technological University
Session type: panel
Discussants:      Hong Tat Chee, Ministry for National Development      Jeffrey Sachs, Department of Economics, Columbia University
Session 2: Plenary: International Security in a Fractured Global Economy: The Middle East Crisis and Beyond (EGC Plenary) July 28, 2026 11:30 to 12:50 Location: Ballroom 1 (level 3)
Session Chair: Heng Chee Chan, Ministry of Foreign Affairs
Session type: plenary
Discussants:      Tim Besley, London School of Economics      Bruno Dallago, University of Trento      Danny Quah, National University of Singapore      Mehmet Bilgin, Istanbul Medeniyet University      K.S. Jomo, Khazanah Research Institute
Session 3: ESS Plenary: Growth of Asia: What’s Next July 28, 2026 14:00 to 15:20 Location: Ballroom 1 (level 3)
Session Chair: Prakash Kannan, GIC
Session type: panel
Discussants:      Selena Ling, OCBC      Teck Kin Suan, UOB      Manu Bhaskaran, NUS      Neil Parekh, GTFN      Jamus Lim, ESSEC Business School
Session 4: Invited 1.1: Technology and A.I. July 28, 2026 15:50 to 17:10 Location: Singapore Room (level 5)
Session Chair: Daniel Houser, George Mason University
Session type: invited
1. Demographic Change and Long-Term Growth: The Role of AI and Human Capital in an Aging Society Abstract This lecture examines how aging societies can sustain long-term growth despite shrinking workforces and rising fiscal pressures. It argues that demographic change does not mechanically determine economic outcomes; rather, growth depends critically on how economies adapt through technological innovation, human capital formation, and institutional reform. Artificial intelligence (AI) has the potential to raise productivity, complement older workers, and alleviate labor shortages, but its effects will depend heavily on its broad diffusion across firms and sectors. With appropriate policies and institutions, aging societies can maintain productivity growth and economic dynamism despite severe demographic pressures. The lecture also highlights AI’s potential to stimulate innovation. To illustrate these dynamics, it presents a case study of China based on a dynamic endogenous growth model incorporating demographic transition, AI, and endogenous innovation. The analysis shows that AI can substantially increase long-run growth by enhancing research productivity and inducing greater R&D investment, thereby partially offsetting the adverse effects of population aging.
By Jong-Wha Lee; Korea University
Presented by: Jong-Wha Lee, Korea University
2. Who Is Ready for CBDC? A Multi-Pillar Cross-Country Readiness Index and Toolkit for Policy Makers Abstract This paper introduces a comprehensive, multi-pillar Central Bank Digital Currency (CBDC) Readiness Index, designed to assess the foundational capacity of countries for implementing CBDCs. The index comprises five pillars: Digital and Technology Infrastructure, Economic and Household Capacity, Financial Depth and Inclusion, Institutions and Regulation, and Macro Resilience and Policy, providing a data-driven framework for evaluating CBDC readiness. Unlike existing indices that focus on project status or attention measures, this index emphasizes long-term structural factors such as digital infrastructure, financial inclusion, and institutional strength. Constructed using a robust, auditable methodology, the index employs CRITIC information weighting and geometric aggregation to ensure transparency and reliability. Calculated for up to 183 economies, the index allows for a comprehensive assessment of CBDC readiness, distinguishing it from individual design choices or short-term announcements. Robustness and sensitivity checks, including bootstrap resampling and leave-one-variable-out experiments, validate the stability of rankings. The CBDC Readiness Index serves as a policy toolkit, enabling central banks and international institutions to identify digital, financial, and institutional barriers and to design CBDC projects aligned with country-specific readiness profiles.
By Ahmet Aysan; Hamad Bin Khalifa University
Presented by: Ahmet Aysan, Hamad Bin Khalifa University
3. Bias in AI and HR Recruiting Decisions Abstract AI increasingly controls access to employment. As a result, substantial attention has focused on how AI judgements and decisions regarding job candidates compare to human decisions. Here we compare evaluations of job-candidate resumes between generative AI (GPT-4o) and over 1,200 ethnically Chinese HR professionals working in mainland China. We design four CVs that vary only in their included photo: an attractive and plain woman, and an attractive and plain man. We combine the CVs with three different job descriptions, resulting in a total of 12 conditions. We randomlyassignaround100HRprofessionalstoeachcondition.In each condition,each professional provides an overall candidate evaluation, as well as ratings on multiple dimensions of competence and social skill. Using identical prompts, we ask AI to complete the same evaluation tasks. We find AI evaluations to depart sharply from those of HR in that all of AI’s ratings distributions are economically and statistically significantly more concentrated. We nevertheless find substantial similarity in mean evaluation scores between HR professionals and AI. Moreover, correlations between competence/social skill scores and overall candidate evaluations are statistically similar between AI and HR.We find gender and attractiveness biases to be small in our regression analyses, but magnified in their implications for rankings of candidates. In particular, AI job candidate rankings are substantially more biased against women than rankings by HR professionals. Our results emphasize that humans have a critical role to play in ensuring equitable recruiting processes that achieve the benefits of diversity in the workplace.
By Daniel Houser; George Mason University
Presented by: Daniel Houser, George Mason University
Session 5: Invited 1.2: Environment and Green Economy July 28, 2026 15:50 to 17:10 Location: Thailand Room (level 5)
Session Chair: Jinhua Zhao, Cornell University
Session type: invited
1. Reducing Emissions of the Other Greenhouse Gas: Estimating the Costs of Methane Abatement Abstract Because of the importance of methane as a driver of climate change, I am leading a multi-year research and outreach effort – the Harvard Initiative on Reducing Global Methane Emissions – which involves more than a dozen faculty members and doctoral students from across the University, carrying out 23 individual research projects, focused on methane emissions from the oil and gas sector, agriculture, and waste disposal. These research projects include several examinations of the economics of reducing methane emissions, principally in the oil and gas sector, the key focus of this presentation. I begin by surveying and synthesizing investigations of methane abatement costs, starting with prospective analyses which use engineering cost models. With this approach, equipment and actions are specified for a “model plant,” and investment and operating costs summed, and revenues are subtracted due to theoretical marketing of captured methane, to generate estimates of net abatement costs. The limitations of such models are significant, and are carefully assessed. Next, I examine retrospective analyses, that is, econometric models, in which market behavior is statistically analyzed to generate estimates of how methane emissions have varied as a function of natural gas production, prices, policies, and other factors. Previous applications have relied on self-reported emission data, and static models of operator decisions. To correct for these and other issues, in new econometric work, I employ geographically and temporally precise remote-sensing (satellite) data of methane emissions; allow for lagged effects of previous abatement investments; employ contemporaneous and expected future natural gas prices at disaggregated pricing hubs; and recognize that natural gas prices affect both operation of existing wells and development of new wells, and thereby distinguish between the impacts of prices on emissions at existing wells from impacts on the development of new ones.
By Robert Stavins; Harvard University
Presented by: Robert Stavins, Harvard University
2. Potential Green Growth Path of the Pacific: Human Capital Development and Circulation of Domestic Savings into Domestic Investments Abstract This paper explores an innovative fiscal strategy for sustainable development in Palau by keeping debt levels low, given the limited macroeconomic tools available due to the absence of a central bank. Palau will introduce blockchain-based government savings bonds to mobilize domestic savings for local investments. The paper identifies key structural challenges in the Pacific islands, including Palu. The capital outward flight, skilled labor migration, and limited financial literacy. It proposes a comprehensive framework combining financial education, digital innovation, and targeted lending to housing, small businesses, and infrastructure. Theoretical modelling using an extended Solow-Mankiw framework illustrates the potential for increased domestic capital accumulation and economic resilience. The study concludes that, with practical implementation and strong spillover effects, infrastructure investments such as airports, when coupled with souvenir shops, restaurants, resting hotels, can help Palau achieve economic growth. Fisheries processing industry. The development of small-business financing and green investments using ocean waves, funded by domestic savings, will drive continuous green growth in Palau.
By Naoyuki Yoshino; Keio University
Presented by: Naoyuki Yoshino, Keio University
3. The Innovation-Inducing Effect of Standard-Based Industrial Policy: Evidence from China's Photovoltaic Industry Abstract The photovoltaic industry is one of the strategic and leading industries in China today and has increasingly become globally competitive with its full control of key technologies. This paper focuses on the innovation-inducing effect of the Pioneer Program, a non-subsidy, standard-based industrial policy implemented by the Chinese government in 2015, on upgrading the technology in photovoltaic industry. By using Pioneer Program as a quasi-natural experiment and employing the Difference-in-Differences model, we find that the Pioneer Program has significantly promoted enterprises' capability of innovating both on the quantity level and quality level. We also show that building more high-standard photovoltaic power stations can significantly enhance the innovation capability of enterprises. This paper provides a new perspective to a better understanding of China's industrial policies and the interaction between the government and the market.
By Jun Zhang; Fudan University
Presented by: Jun Zhang, Fudan University
4. Measuring Pollution’s Welfare Costs: Ambient Pollution versus Pollution Exposure Abstract Estimates of the health and welfare costs of particulate matter (PM) pollution often rely on ambient pollution concentrations. But pollution exposure can be far lower due to individuals adopting defensive behaviors such as reduced outdoor time and mask-wearing. Using data from a large scale field experiment in Northeastern China, we find that such avoidance behaviors are responsive to pollution and effective at lowering exposure. When these behaviors are ignored, the estimated marginal effects of PM pollution can be far lower than the true effects. We use daily data on outdoor time, mask-wearing, and the estimated mask efficiency to construct a measure of net pollution exposure, and using the randomized treatments as instruments for endogenous avoidance behaviors, we estimate the dose-response functions of both ambient pollution and exposure. Ambient-pollution-based approaches under-estimate the marginal health damages of pollution by roughly 60–90% across subgroups, with the largest gaps among individuals who defend most intensively. Our findings underscore the need to consider both ambient concentrations and avoidance behaviors in order to accurately measure the social costs of pollution.
By Jinhua Zhao; Cornell University
Presented by: Jinhua Zhao, Cornell University
Session 6: Invited 1.3: Econometrics July 28, 2026 15:50 to 17:10 Location: Malaysia Room (level 5)
Session Chair: HSIAO Cheng, University of Southern California
Session type: invited
1. Endogenous Panel Interactive Effects Models Abstract Many micro econometric analyses take a single equation approach. However, economists typically consider economic sectors are interrelated. The general (or partial) equilibrium of (a sector of) the economy is achieved through the automatic operation (say, free competition) of the parts that compose the system. We argue that without considering if an equation is not identified in the system, the estimation of such an equation could lead to meaningless curve fitting. Moreover, economic modeling is a simplification of reality, not a mimic of reality. Panel data, being multi-dimensions, provide the possibility to control the omitted variable effects through decomposing the stochastic errors into components, thus introducing restrictions on the error variance and covariance which provide the possibility to relax the identification conditions derived by the Cowles Commission. We also consider inference methods for an endogenous single equation panel interactive model including the limited information maximum likelihood and the methods of moments estimators such as the two stage least squares, the profile GMM and the transformed GMM. A small-scale Monte Carlos is conducted to demonstrate the feasibility of implementing these methods in a finite sample.
By HSIAO Cheng; University of Southern California
Presented by: HSIAO Cheng, University of Southern California
Session 7: Invited 1.4: Political Economy July 28, 2026 15:50 to 17:10 Location: Indonesia Room (level 5)
Session Chair: Danny Quah, National University of Singapore
Session type: invited
1. The Political Economy of Policy Narratives Abstract Economists are increasingly interested in the idea that beliefs are shifted through the use of policy narratives and there is increasing interest in how these ideas can be brought into studies of policy change. The presentation will discuss a specific approach where narratives affect policy preferences through motivated reasoning. The focus of the presentation will be on narratives that influence policy preference and hence policies that influence the size of government, a classic cleavage that has been widely studied in political economy models. To illustrate how narratives shifts are measurable, it will draw on on-going work with Adam Bzezinski and Jake Fazzio that formalizes these ideas and test their relevance using LLMs to analyse speeches given by policy makers in the US and UK.
By Tim Besley; London School of Economics
Presented by: Tim Besley, London School of Economics
2. Ailing competitiveness and entrepreneurship in the EU and transforming EU economic priorities Abstract The EU is aware that it has a fundamental problem with competitiveness (Draghi 2024). The war in Ukraine has made the problem dramatically important and its relevance increasingly serious because of internal policies (sanctions, tensions with China, the difficult pursuit of energy independence and ecological transition goals, slowdown of international cooperation agreements) and external events (Biden’s protectionist policies, Trump’s tariffs and mounting protectionism, increased energy cost, military expenditures and weapon imports). To this the conflict between the European Commission and national governments should be added, particularly because national interests diverge (due to different economic structures and policy priorities) and because the adjustment requires additional national competencies to be transferred to EU organs. The dramatic change of international economic relations, strengthened protectionist attitudes in the US, and the EU accelerated transformation led to the progressive dismantling of the neoliberal international order based on unconstrained markets, replaced by the revival of policies and government activism. Technological progress (green technologies, AI, ICT) became increasingly centered on governments and large organizations with large and deep financial endowments and research facilities. The progressive nature of these technologies and their far-reaching implications require much less entrepreneurship and much more organization and planning. This gives a competitive advantage to China and the military sector in Western economies. Under these conditions the role of private entrepreneurship and related innovation is bound to decrease further. Entrepreneurship and innovation are progressively replaced by planning and organization, which require deep and far-reaching institutional adaptation and increasing the professional and managerial quality of governments. To test this hypothesis and related observations and evidence, this paper offers a content analysis of all the country specific recommendations (CSRs) issued from 2011 to 2024 to all European member countries with the purpose of investigating the importance of innovation and entrepreneurship in the European strategy and the ways in which it is promoted by the European institutions through CSRs. The results indicate that entrepreneurship and innovation have never been priorities within the European Semester. Entrepreneurship has been indirectly supported by CSRs aimed at improving competitiveness and the efficiency of the business environment. However, entrepreneurship completely disappears from 2020. In the case of innovation, despite a dedicated policy area in the context of the CSRs, the relevance of this topic has been always limited, and its importance declined sharply after the COVID-19 pandemic. These findings underscore the structural lack of common industrial policy and the progressive elimination of entrepreneurship and innovation from the objectives of European institutions. This casts a disturbing light on the EU readiness to comply with recent calls for competitiveness and innovation.
By Bruno Dallago; University of Trento
Presented by: Bruno Dallago, University of Trento
3. ASEAN and the Middle-Power Moment: Forging Atlantic-Pacific Economic Cooperation (APEC 2.0) for the Digital Century Abstract Superpowers understand that mutual survival requires effective mechanisms to minimize the probability of wars (especially nuclear wars) among themselves. The first mechanism was the 1945 Yalta agreement between USA and Soviet Union to divide the world into spheres of influence. The second mechanism was the succession of arms control treaties between USA and Soviet Union (then Russia) after the 1962 Cuban missile crisis. The rise of China as a superpower in the first decade of the 21st Century has caused Russia and USA to allow their arms limitation treaty (New START) to lapse on February 5, 2026 because the above two mechanisms to minimize global nuclear catastrophe is ineffective without the participation of China. As Russia and USA envisaged future negotiations with China to arrive at a Yalta-type division of the world into spheres of influence and a trilateral arms limitation treaty, they are racing today to expand their spheres of influence to strengthen their hands before these trilateral negotiations occur. Ukraine, Greenland, and Iran are the unfortunate victims of this Russo-US geostrategic race. At the same time, the upward drift in Russo-Sino-US tension is increasing collateral damage on the rest of the world e.g. increased fragility in the supply chains, weaponization of the USD-based global payments system, and reduced benefits from the trade restrictions on goods from countries in other spheres of influence. The best outcome for a non-superpower is to be nonpartisan, and trade with every sphere of influence. Neutrality, however, is not achieved through self-declaration but through recognition by all three superpowers. A country is more likely to be accorded neutral status if it is a member of a neutrality coalition that can project collective force that matches those of the superpowers. As the superpowers would be vigilant in preventing the formation of this strong neutrality coalition in the first place, such a coalition must be formed relatively quickly, which means that the number of founding members must also be small. Furthermore, to soothe the discomfort of the superpowers, this coalition must have members which have close ties with the US, and some members with good relations with China. The Rest of the West (consisting of the 27 members of the European Union, UK, Canada, Japan, South Korea, Australia and New Zealand) and ASEAN – the major middle powers in Atlantic Europe and Pacific Asia -- should form the Atlantic-Pacific Sustainability Partnership (APSP) to maintain multilateral free trade, uphold the United Nations principles of peace and human rights, and protect global ecosystems; and obligate the rich APSP members to assist the economic development and green transformation of poor APSP members – with the economic pillar of APSP being Atlantic-Pacific Economic Cooperation (APEC 2.0) which deepens economic integration beyond the scope of the now broken Asia-Pacific Economic Cooperation (APEC 1.). As the collective GDP of APSP will be significantly larger than that of USA, China and Russia in a decade from now, each superpower would have an increasing incentive to join APSP to seek alliance against the others. If one joins, the others would quickly follow to avoid inevitable defeat from self-isolation. When this happens, APSP would have crowded out the Russo-Sino-US Cold War.
By Wing Thye Woo; University of California, Davis
Presented by: Wing Thye Woo, University of California, Davis
4. The Rest of Us: Incentives, not Power, in Rebuilding World Order Abstract Since the 2008 Global Financial Crisis, conventional wisdom has blamed China–US rivalry for rupturing world order. This paper argues otherwise: (1) less visible but more decisive forces---beyond geostrategic competition---better explain the rupture; and (2) the power hierarchy underpinning the multilateral rules based order is inconsistent with that order’s own realized successes. Most critically, if the benevolent hegemon transmogrifies into a bad actor, the same overwhelming power it once wielded for good can now be turned to harm. Recasting the problem beyond just geopolitical rivalry clarifies how to rebuild a more durable multilateral system that optimises security and prosperity. Incentives, not power, will drive such a system. The new order can be a flexible topology of pathfinder, incentive-compatible, G-minus, multilateral-enough coalitions, held together by inadvertent cooperation, rather than sweeping treaties or grand institutional re-design.
By Danny Quah; National University of Singapore
Presented by: Danny Quah, National University of Singapore
Session 8: Invited 1.5: Behavioral and Experimental July 28, 2026 15:50 to 17:10 Location: Philippines Room (level 5)
Session Chair: Erik Snowberg, The University of Utah
Session type: invited
1. How (not) to Test a Theory Abstract Behavioral Economics Theory has grown prodigiously over the past 40 years. However, measures to test those theories have lagged far behind these theoretical advances. In this talk I will discuss how lessons from physical measurement can be applied to measurement in the behavioral sciences. I will illustrate these points with examples of both good and bad practice in developing measures.
By Erik Snowberg; The University of Utah
Presented by: Erik Snowberg, The University of Utah
Session 9: Invited 1.6: Social and Developmental July 28, 2026 15:50 to 17:10 Location: Brunei Room (level 5)
Session Chair: Renate Schubert, ETH Zurich
Session type: invited
1. Learning about Development: Reflections on Six Decades of Indonesian Economic Development Abstract Indonesia's socio-economic transformation since the late 1960s has been dramatic. In 1965 Indonesia was a very poor country. It had disengaged from the global economy, nationalized virtually all foreign property, lost control of the macroeconomy, was hardly industrialized, and was politically polarized. The majority of its people lived in poverty and were malnourished. Sixty years later it is a moderately dynamic upper-middle income economy, globally integrated and recognised for its development achievements, and also for its six national elections in the democratic era. Destitution has been almost eliminated. This paper surveys the literature on the Indonesian economy over this period to understand, and learn from, the country's development record. It draws attention to both the continuities and the changes, analyses of and debates about the factors that have propelled economic development and those that have arguably retarded it. Among the former are the growth record itself, prudent macroeconomic management, staying fairly open to the global economy, poverty reduction, and holding the country together. Conversely, the continuing challenges include indifferent governance and institutional quality, environmental and natural resource management, the mixed record on human capital and technology upgrading, and some lagging regional development outcomes.
By Hal Hill; AO, ANU
Presented by: Hal Hill, AO, ANU
2. What Drives Development Success: New Institutional Economics vs. New Structural Economics Abstract This presentation compares New Institutional Economics (NIE) and New Structural Economics (NSE) to explore the drivers of development success. NIE emphasizes institutions as core determinants, but empirical evidence—such as similar growth rates between Latin America and North America from 1870–1960 despite different institutions—challenges this determinism. In contrast, NSE argues that economic strategy is pivotal. A nation’s growth depends on governments facilitating industries with latent comparative advantages, determined by its factor endowments, converting them into actual advantages via efficient markets and targeted state support. Latin America’s post-1960 stagnation stems from defying comparative advantages through import substitution, while 13 high-growth economies thrived by aligning policies with their endowments. The conclusion is that institutions are endogenous outcomes, and success lies in a market economy complemented by a facilitating state to drive structural transformation and inclusive growth.
By Justin Yifu Lin; Peking University
Presented by: Justin Yifu Lin, Peking University
3. Assessing Social Resilience through Archetypes: Methodology and Insights from Singapore Abstract Understanding social resilience dynamics in urban populations is essential for effective governance and disaster/crisis preparedness. This study introduces a framework for assessing social resilience through social archetypes, defined by shared capacities and perceptions, and examines how social resilience performance shifts under potential disruptions. Using survey data from Singapore at both national and town levels, we identify three archetypes with distinct social resilience profiles and demonstrate that high resilience under normal conditions does not always predict superior performance during disruptions.
By Renate Schubert; ETH Zurich
Presented by: Renate Schubert, ETH Zurich
4. Mature or Premature Deindustrialization? Infrastructure and Structural Transformation in the Philippines over Four Decades Abstract Long-run structural transformation from agriculture to non-agriculture is central to economic development, yet many late industrializers have experienced declining manufacturing shares at relatively low income levels, so-called premature deindustrialization. This paper studies a novel mechanism behind this pattern that predates the arrival of these modern technologies: labor-market frictions that limit access to modern-sector jobs, creating wage wedges and impeding mobility. We assemble unique individual-level “family dynasty” data spanning 1977–2017 for communities around Lake Laguna in the Philippines and exploit a quasi-experimental setting in which highway construction and subsequent industrial park development ”treatment” targeted the lake’s west side but largely bypassed the east. By combining long-term household tracking with Landsat satellite imageries, and population censuses, we implement a cohort-by-geography difference-in-differences design to estimate causal impacts on occupational choices. Also, we conduct a numerical analysis of aggregated structural transformation by adding sectoral aggregated statistics. We find that the place-based infrastructure investments have accelerated ’mature’ industrialization and ’canonical’ structural transformation by boosting modern-sector employment across generations. In contrast, occupational change in the untreated area appears consistent with a service-led transition prior to sufficient industrialization, suggestive of premature deindustrialization driven by limited access to modern manufacturing jobs. These findings can be explained by a quantitative general equilibrium model in which labor-mobility frictions can generate economy-wide misallocation and substantial efficiency losses. In other words, insufficient investments in transport infrastructure and industrial parks seem to contribute to premature deindustrialization.
By Yasuyuki Sawada; University of Tokyo
Presented by: Yasuyuki Sawada, University of Tokyo
Session 10: Invited 1.7: Macroeconomics, Labor and Household Consumption July 28, 2026 15:50 to 17:10 Location: Vietnam Room (level 5)
Session Chair: Partha Sen, Delhi School of Economics
Session type: invited
1. How Are Bequests Divided Among Children? The Case of Japan Abstract This paper analyzes how bequests are divided among children in Japan and what determines how they are divided using administrative data from inheritance tax returns filed during the 2014-21 period. We find that bequests in Japan are not divided equally among children, unlike in most other countries, and that males, especially eldest sons, tend to receive larger shares, even though the law dictates equal bequest division among children. This might be a vestige of social norms arising from Japan’s traditional family system, the so-called ie system. We also find that minor children, disabled children, children who lived close to (and presumably provided care to) the decedent, and children who take over the family business receive larger shares of the bequest than other children, which provides support for altruistic, strategic, and dynastic bequest motives.
By Charles Yuji Horioka; Kobe University    Yoko Niimi; Doshisha University
Presented by: Yoko Niimi, Doshisha University
2. Reshaping gender norms and building trust: Evidence from a community-based couple counseling RCT Abstract Traditional gender equity interventions, such as financial inclusion programs, vocational training, and cash transfers, often focus narrowly on women as isolated economic agents and fail to address the root causes of gender disparities, particularly the disproportionate burden of unpaid domestic labor on women. This study evaluates a novel couple- and community-based intervention designed to reshape intra-household labor allocation, gender stereotypes, and decision-making. Using a randomized controlled trial in Uttar Pradesh, India, we compare two approaches: (1) private couple counseling and (2) private counseling combined with community-based intervention that leverages public accountability and cooperative decision-making. Our findings show that both interventions significantly improve intra-household cooperation, with the community-based gender sensitive intervention yielding stronger and more persistent effects. Results affirm the potential of engaging men and the community in interventions to achieve improvements in gender equity.
By Tetsushi Sonobe; National Graduate Institute for Policy Studies (GRIPS)
Presented by: Tetsushi Sonobe, National Graduate Institute for Policy Studies (GRIPS)
3. Household Saving in Japan: The Past, Present, and Future Abstract This paper presents data on the level of, and trends over time in, Japan’s household saving rate, explores the determinants of Japan’s household saving rate, with emphasis on the impact of the age structure of the population, and makes projections about future trends therein. It finds that Japan’s household saving rate has not always been high either absolutely or relative to other countries, contrary to popular belief, and that, if we confine ourselves to the postwar period, it was only during the 26-year period from 1961 to 1986 that it exceeded 15%. Econometric analysis shows that past trends in Japan’s household saving rate can largely be explained by changes in the age structure of her population but that declines in the saving rate of the retired elderly are also a contributing factor. Moreover, it is likely that other factors such as the unavailability of consumer credit, the unavailability of social safety nets, high rates of economic (income) growth, tax breaks for saving, saving promotion policies, and high and rising land and housing prices are also partial explanations for why Japan’s household saving rate was so high during the 1961-86 period and why it has declined so much since the mid-1970s. As for future trends in Japan’s household saving rate, I speculate that it is likely to fall even further not only because of continued population aging but also because of further declines in the saving rate of the retired elderly.
By Charles Yuji Horioka; Kobe University
Presented by: Charles Yuji Horioka, Kobe University
4. INDIA’S GVC PARTICIPATION: A COMPARATIVE ANALYSIS ACROSS SECTORS Abstract There has been a fragmentation of production of goods internationally. Lower tariffs and transport costs have made this possible. China is seen to be vacating the labour-intensive end of the value chains, and moving up to more sophisticated production. Will India fill (partially, at least) this space? India has seen a declining share of GDP of value-added in manufacturing, and is heavily import dependent (both final and intermediate goods) on China. The Indian government has rolled out incentives for manufacturing, while signing free trade agreements with some major players. In this paper, we look at India’s performance in the GVCs in selected industries and do a comparative analysis with key competitor countries. Backward linkages dominate Indian industries. There is not much evidence of upgrading. There seems to be some effect of industrial policy in electronic and optical sector after 2020. A key competitor, Vietnam, is doing much better than India in filling the space that China is vacating.
By Partha Sen; Delhi School of Economics
Presented by: Partha Sen, Delhi School of Economics
Session 11: Invited 1.8: Banking and Finance July 28, 2026 15:50 to 17:10 Location: Cambodia Room (level 5)
Session Chair: Barry Eichengreen, UC Berkeley
Session type: invited
1. International Monetary System Reform: An East Asian Perspective Abstract For Robert Triffin, unilateral US abrogation of the 1944 Bretton Woods agreement in August 1971 implied a ‘non-system’ in its place. The ‘exorbitant privilege’ of the dollar system enjoyed by the US has nonetheless continued. The East Asian and other financial crises of 1997-99 were quite varied, but prompted a widespread desire for greater international monetary and financial system stability. Northeast Asian leadership from the Chiangmai meeting in 2000 has led to various mitigating initiatives including the ASEAN+3 regional swap arrangements and macroeconomic surveillance. Other monetary and financial authorities in the Global South have looked to region for continued leadership which has been slow due to subsequent geopolitical developments.
By K.S. Jomo; Khazanah Research Institute
Presented by: K.S. Jomo, Khazanah Research Institute
2. Global Currencies: History and Prospect Abstract This paper considers global currencies in history: their rise, reign and eventual fall. Cases considered range from the Owls and Alexanders of Ancient Athens to the stablecoins and central bank digital currencies of today and tomorrow, but special attention is paid to the international role of the U.S. dollar, and whether this role is likely to persist for the foreseeable future.
By Barry Eichengreen; UC Berkeley
Presented by: Barry Eichengreen, UC Berkeley
Session 12: Behavioral I - Individual Decision July 28, 2026 17:20 to 18:50 Location: Singapore Room (level 5)
Session Chair: Nattavudh Powdthavee, Nanyang Technological University
Session type: invited
1. The relationship between household debt and the Big Five personality traits Abstract This study investigates the relationship between household debt and the Big Five personality traits using data from the Korea Labor and Income Panel Study. The extensive and intensive margins of debt participation are analyzed through regression analysis. To address potential sample selection bias from non-random missing data, a Heckman selection model is employed. The results indicate that openness is negatively associated with the probability of debt-holding, while conscientiousness is positively associated. To enhance causal interpretation, panel models are additionally estimated, treating personality traits as predetermined. While personality traits do not significantly predict year-on-year changes in debt amounts, they remain a relevant predictor of debt participation. These findings suggest that personality-based financial profiling may help identify households more prone to incurring debt. The results are interpreted in the light of South Korea’s cultural context, particularly the influence of Chemyeon (social face), and compared with findings from Western societies.
By Taehyun Lee; Korea Employment Information Service; Korea University    Almas Heshmati; University of Economics Ho Chi Minh City, Vietnam
Presented by: Taehyun Lee, Korea Employment Information Service; Korea University
2. Complexity Aversion Abstract This paper proposes a model of decision-making under uncertainty in which an agent is constrained in her cognitive ability to consider complex acts. We identify the complexity of an act according to the corresponding partition of state space. The agent ranks acts according to the expected utility net of complexity cost. A key feature of this model is that the agent is able to update her complexity cost function after the arrival of new information. The main result characterizes axiomatically an updating rule for complexity cost function, the Minimal Complexity Aversion representation. According to this rule, the agent measures the complexity cost of an act conditional on the new information by using the cost of another act that gives exactly the same partition of the event but with the lowest ex-ante cost.
By Yuan Gu; Fuyao University of Science and Technology    chaohung chan; Fuyao University of Science and Technology
Presented by: Yuan Gu, Fuyao University of Science and Technology
3. Resource Allocation in Repeated Contest under Present Bias Abstract This study analyzes a situation in which two players with present bias repeatedly play a Tullock contest under resource constraints. When competition is long-lasting, the allocation of resources through time becomes essential. A rational player would plan inputs to maximize the sum of the present value of the expected payoff over the entire period. However, experiments have shown that typical decision-makers exhibit present bias and time inconsistency in preferences. We characterized an equilibrium in a repeated contest where players evaluate future payoffs using quasi-hyperbolic discounting.
By Kazuki Kumashiro; Okayama Shoka University    Shuichi Tsugawa; Ryukoku University
Presented by: Kazuki Kumashiro, Okayama Shoka University
4. Prosocial Advice and Spending Choices: A Campus Experiment Abstract Previous studies have shown that prosocial spending can effectively improve subjective well-being and even enhance social welfare. However, without intervention, people often underinvest in such choice due to psychological frictions that they underestimate its benefits. This study explores whether a piece of prosocial spending advice, either generated by AI or prepared by human experimenter with almost identical content, can weaken such psychological friction and increase the proportion of prosocial spendings. And we also examine whether its effectiveness depends on the advice source, given that people tend to have algorithmic aversion. We conducted a field experiment on Nanyang Technological University campus with 265 student participants aged 21 and above. Participants were randomly assigned within session to a no-advice control condition, an AI-generated advice condition, or a closely matched human-advice condition. Before the experiment, a Prolific pretest was used to select AI- and human-written advice that was similar in perceived warmth, clarity, reliability, specificity, and persuasiveness. Participants completed a morning survey, received S$10, made actual purchases on campus, and reported their transaction-level spending and subjective experiences in an evening survey. The primary outcome is the share of the total spending spent on prosocial behaviors, including gifts, shared items, and donations. Secondary outcomes include spending satisfaction and the change in self-reported happiness from morning to evening. We find that compared to the control condition, AI and human advice increased the prosocial spending share by 24.5 and 23.5 percentage points, respectively. The difference between the two advice conditions is not statistically significant. Moreover, our results also show no significant evidence that realized prosocial spending is associated with changes in happiness.
By Yue Han; Nanyang Technological University    Nattavudh Powdthavee; Nanyang Technological University
Presented by: Yue Han, Nanyang Technological University
Session 13: Development I July 28, 2026 17:20 to 18:50 Location: Thailand Room (level 5)
Session Chair: Tim Besley, London School of Economics
Session type: invited
1. Spatial Dynamics of Population Aging and Migration: Subnational Evidence from Thailand Abstract Thailand is experiencing one of the fastest demographic transitions toward aging, with 20\% of citizens aged 60 and above and historically low fertility rates. This study examines how internal and foreign migration shapes subnational demographic resilience. Using panel data from 7,255 tambons (2004--2019) and Method of Moments Quantile Regression (MMQR) with fixed effects, we estimate how migration affects population aging, child shares, fertility, and a demographic labor-pressure index, accounting for spatial dependence and granular controls. Results identify two key mechanisms: \textbf{structural resilience}, where migration shifts the age composition to reduce aging, and \textbf{fertility resilience}, where migrants boost local birth rates. Foreign migration most effectively lowers elderly shares in superaging tambons and raises fertility in high-fertility areas, while internal migration produces smaller fertility gains but eases labor pressures. The demographic role of migration unfolds differently across Thailand’s regions, reducing elderly shares in many Northern, Northeastern, and Southern tambons while reinforcing aging in some Central Region tambons at the upper tail of the aging distribution. Robustness checks using bootstrapped quantile regression, spatial dependence adjustments, and detailed tambon-level controls (2016–2019) confirm that both internal and foreign migration reduce population aging, particularly in tambons at the upper tail of the aging distribution. Migration thus fosters heterogeneous yet meaningful demographic adaptations across Thailand.
By min Hein; Thammasat University
Presented by: min Hein, Thammasat University
2. When manufacturing matters most: Structural transformation and productivity growth trajectories in developing and emerging economies Abstract Structural transformation is a central driver of economic development, yet recent challenges such as premature deindustrialization have raised critical questions about whether low-income economies can still follow traditional growth paths that rely on manufacturing expansion to drive productivity gains. Building on a theoretical model that incorporates learning-by-doing mechanisms, sectoral employment reallocation, and factor accumulation, we examine labor productivity growth trajectories using a panel of 31 developing and emerging economies over 1960-2019, detecting a data-driven structural break in 1982 that fundamentally altered productivity growth dynamics. To account for the potential heterogeneity in how structural transformation affects different types of economies, we employ quantile-based techniques to examine effects across different segments of the productivity growth distribution, moving beyond conventional approaches that focus on average effects and may obscure important distributional patterns. The unconditional quantile regression results identify manufacturing expansion as a key driver of productivity growth, with employment reallocation in this sector delivering twice the productivity benefits for slower-growing economies compared to high performers. The quantile decomposition further shows that observable characteristics and unobservable factors became increasingly important determinants of productivity performance following the structural break, with substantial heterogeneity across the distribution. Moreover, we construct counterfactual scenarios to investigate what outcomes low-performing economies could have attained had they adopted the characteristics, returns to factors, and unobservable capabilities of top performers. These unveil substantial untapped growth potential, with bottom quartile economies potentially achieving average productivity growth improvements of up to 2.7 percentage points.
By Michele Battisti; Università di Palermo    Antonio Francesco Gravina; Università di Messina    Matteo Lanzafame; Asian Development Bank
Presented by: Matteo Lanzafame, Asian Development Bank
3. Construction of an Evaluation Indicator System for the High-Quality Development of “Double First-Class” Universities from the Perspective of New Quality Productive Forces Abstract The high-quality development of Double First-Class universities is driven by reform and innovation, responding to the contemporary imperative for higher education to empower new quality productive forces and serving as a vital foundation for national high-quality development. From the perspective of new quality productive forces, this study clarifies the conceptual connotation of high-quality development in Double First-Class universities and further examines the value orientation of the corresponding evaluation indicator system. Drawing on a systematic literature review, this paper develops an exploratory five-dimensional evaluation framework for assessing high-quality development in Double First-Class universities, comprising talent cultivation, scientific and technological innovation, societal service and contribution, sustainable development, and international reputation. The Analytic Hierarchy Process is employed to determine the weights of each indicator. In response to practical challenges in current high-quality development—such as the lack of consensus on evaluation philosophies and the misalignment among evaluation stakeholders—this study revisits the intrinsic relationship between quality and evaluation. It proposes prioritizing quality and effectiveness in evaluation philosophy, promoting multi-actor co-governance among stakeholders, strengthening the dynamic adaptability of evaluation methods, and emphasizing ecological feedback in the application of evaluation outcomes. These measures aim to enhance the enabling role of evaluation in advancing high-quality development in Double First-Class universities, thereby injecting sustained momentum and vitality into the construction of a leading education system and the development of new quality productive forces.
By Huimin Peng; China University of Mining and Technology
Presented by: Huimin Peng, China University of Mining and Technology
4. Export Quality of Functional Materials in Japan: 2000–2023 Abstract This paper measures the quality of Japan’s functional materials exports using detailed trade data and examines its characteristics. Specifically, assuming that export quality is reflected in export unit prices, we attempt to measure export quality by estimating gravity equations. This study focuses particularly on functional materials, measuring the quality of exports for each item based on detailed six digit HIS code classifications. Japan’s export competitiveness in functional materials maintains an exceptionally high global standard, representing one of the few sectors possessing the “ability to earn overseas” in the world market. In this sense, quantitative analysis of export quality for functional materials is highly significant. This study represents the first such attempt in Japan and holds considerable academic value. Measurement results reveal that Japan maintains a top-tier global level of export quality, particularly for semiconductor materials and electronic components. Furthermore, the quality of exports for functional coating agents, paints, and inks, as well as functional films and sheets, has remained stable over time, maintaining a global ranking between 4th and 6th place. Considering that the quality of exports ranks highly globally and shows stable trends, functional materials play an extremely important role in Japan’s export strategy.
By Yoichi Matsubayashi; Kobe University    Dung Luong
Presented by: Dung Luong,
Session 14: Econometrics I July 28, 2026 17:20 to 18:50 Location: Malaysia Room (level 5)
Session Chair: Seok Young Hong, Nanyang Technological University
Session type: invited
1. Forecasting the VIX Index: An Interpretable Framework Using Statistical and Machine Learning Approaches Abstract 1. Introduction The pricing of financial assets is inherently linked to market participants' expectations of future uncertainty. The CBOE Volatility Index (VIX), commonly known as the "fear gauge," serves as a premier measure of market-implied volatility, reflecting 30-day forward-looking expectations derived from S&P 500 option prices. While machine learning (ML) methods have gained significant traction in financial modeling due to their ability to capture complex, nonlinear relationships, the existing literature remains overwhelmingly focused on realized volatility (RV). The application of advanced predictive algorithms to implied volatility - which contains substantially richer, forward-looking informational content - remains largely underexplored. This study addresses this gap by proposing a comprehensive, data-driven, and interpretable forecasting framework for the VIX index. 2. Contributions This research makes three primary contributions to the financial economics literature. First, we conduct an unprecedented large-scale benchmarking of 18 forecasting paradigms for implied volatility. Second, we introduce one of the most extensive predictor frameworks to date, evaluating 159 exogenous variables across daily and weekly horizons. Third, we implement a novel, multi-method interpretability approach to open the "black box" of complex algorithms, enabling the robust identification of the fundamental drivers of market fear. 3. Methodology The predictor space encompasses lagged VIX values alongside a diverse set of financial, macroeconomic, and sentiment indicators, including stock indices, currencies, commodities, yield spreads, and uncertainty measures. Out-of-sample forecasting performance is evaluated across daily (short-term) and weekly (smoothed expected volatility) horizons. We assess 18 distinct models organized into six methodological categories: benchmark models (RW, AR, HAR), statistical and regularization methods (PCA, BMA, LASSO), tree-based ensembles (RF, LGBM), general-purpose neural networks (MLP, KAN), deep learning models for time series (LSTM, TCN, N-BEATS, TSMixer, TiDE), and modern transformer-based foundation models (TFT, Chronos, TimeGPT). The statistical significance of predictive accuracy differences is rigorously validated using the model confidence set (MCS) procedure. Furthermore, feature importance is extracted using posterior inclusion probabilities (PIP) for BMA, selection frequency for LASSO, and shapley additive explanations (SHAP) combined with split feature importance for LGBM. 4. Results Empirical findings reveal significant divergences in model performance, strictly dependent on the forecasting horizon and the chosen loss function: •Daily Forecasts: The light gradient boosting machine (LGBM) emerged as the undisputed leader, achieving the lowest mean squared error (MSE) and an R2 of 0.930. However, the traditional HAR model demonstrated highly competitive performance, ranking first in absolute error minimization (MAE). Notably, pre-trained foundation models (Chronos, TimeGPT) failed to outperform classical baselines, ranking at the bottom of the distribution. •Weekly Forecasts: Transitioning to the smoothed weekly horizon induced a drastic shift. Deep learning architectures, particularly TiDE and TSMixer, dominated the MSE metric, while LGBM's performance deteriorated significantly. •The Random Forest Paradox: The weekly analysis exposed a fascinating statistical anomaly regarding the RF model. While RF ranked last (18th) in MSE, it completely dominated absolute metrics (MAE and MAPE), becoming the sole model retained in the MCS for these categories. This indicates that while RF excels at capturing the median weekly volatility level, it fundamentally fails to adapt to extreme VIX spikes, which are heavily penalized by squared metrics. •Directional Accuracy: Temporal aggregation caused directional accuracy (DA) to drop below the random walk threshold across all models, highlighting the inherent difficulty of classifying broader, multi-day volatility trends. 5. Conclusions This study demonstrates that there is no universal predictive architecture for the VIX index. The optimal model choice depends critically on the operational horizon and the specific loss function. While LGBM method excel in short-term daily point forecasting, specialized deep learning architectures are superior for smoothed multi-day horizons. Additionally, the divergence between absolute and squared error optimizations - exemplified by the RF model -underscores the necessity of aligning the forecasting algorithm with specific risk management and derivative pricing objectives. By combining high-dimensional data with interpretable ML, this framework provides both accurate forecasts and vital economic insights into volatility transmission mechanisms. JEL Classification: C45, C53, C58, G17 Keywords: VIX Index, Volatility Forecasting, Machine Learning, Interpretable AI, Deep Learning
By Grzegorz Dudek; Czestochowa University of Technology    Piotr Fiszeder; Nicolaus Copernicus University in Torun    Radosław Pietrzyk; Wroclaw University of Economics and Business    Paweł Pełka; Czestochowa University of Technology    Mateusz Kasprzyk; Czestochowa University of Technology
Presented by: Piotr Fiszeder, Nicolaus Copernicus University in Torun
2. How to Measure China’s Capital Outflow Control? Evidence from News and Large Language Models Abstract We develop a muti-frequency index of China’s capital outflow controls from Chinese news. Using a large language model, we classify articles as tightening, loosening, or neutral and aggregate these signals under a single coding protocol. The corpus covers China News Service and Economic Observer from 2000 to 2023. Compared with measures based on official announcements or structured policy documents, which are typically low frequency and binary, our index traces continuous movements in control intensity and can be compiled at monthly, quarterly, and annual frequencies. Validation shows that the index is positively associated with foreign exchange reserve growth and outward direct investment. Robustness checks against alternative textbased indices constructed with BERT and GPT-4o mini yield correlations above 0.8. As a brief illustration, we evaluate the index in forecasting offshore renminbi returns under a common out of sample protocol and find lower forecast errors together with higher directional accuracy when the index is included. The measure is reproducible and scalable, and it provides a timely input for monitoring capital outflow controls as well as a data foundation for subsequent macroeconomic analysis and identification.
By Qu Feng; Nanyang Technological University, Singapore    Xiaoling Zhang; Nanyang Technological University
Presented by: Xiaoling Zhang, Nanyang Technological University
3. When Sentiment Moves and Uncertainty Holds: The Accelerator–Anchor Structure of Volatility Abstract This paper examines how investor sentiment and economic uncertainty transmit into realized volatility when perceived risk diverges from realized volatility, generating an uncertainty–volatility disconnect. Exchange-traded funds (ETFs) provide a useful setting for this analysis because they offer timely, liquid, and internationally comparable measures of market-wide risk transmission across countries and sectors. Using a panel of 43,305 ETF-day observations, the paper aims to identify whether volatility propagation is state-dependent and whether sentiment and uncertainty operate through distinct channels when the disconnect between perceived and realized risk widens. Methodologically, the analysis combines two complementary approaches. First, ETF fixed-effects regressions with a heterogeneous autoregressive (HAR) structure are used to control for multi-horizon volatility persistence and to estimate the average state-dependent effects of sentiment, uncertainty, and global volatility conditions. Second, to relax linearity and capture intensity-dependent propagation, the paper implements an event-based continuous-treatment difference-in-differences design around the COVID shock and across disconnect regimes. The baseline HAR panel results yield two main findings. First, the global realized-volatility factor loads positively in low-disconnect conditions, but its transmission weakens as the uncertainty-to-volatility gap widens, indicating that global spillovers attenuate in disconnect states. Second, sentiment and uncertainty affect realized volatility asymmetrically: sentiment predicts lower next-day ETF realized volatility on average, but this effect weakens when disconnect is high, whereas uncertainty becomes strongly state-contingent and emerges as a first-order predictor of realized volatility in high-disconnect regimes. The event-based continuous-treatment difference-in-differences (DiD) estimates reinforce this interpretation by identifying causal, intensity-dependent responses to sentiment and uncertainty shocks. Uncertainty shocks generate smooth but concave dose-response functions with diminishing marginal effects in the upper tail, while sentiment shocks exhibit non-monotonic marginal responses consistent with overshooting and subsequent correction dynamics. Overall, the results suggest that sentiment mainly influences short-run volatility fluctuations, whereas uncertainty governs volatility persistence when perceived risk outpaces realized volatility. These findings carry policy implications for financial stability monitoring, especially in open and emerging-market settings, because subdued realized volatility may mask elevated fragility when uncertainty becomes disconnected from observed market risk.
By Zaafri Husodo; Universitas Indonesia    Muhammad Prasetyo; Universitas Indonesia    Victor Troster; Universitat de les Illes Balears (UIB)    Gazi Salah Uddin; Linköping University Sweden and Norwegian University of Life Sciences, Norway
Presented by: Zaafri Husodo, Universitas Indonesia
4. Unified Inference for Predictive Mean and Quantile Regressions via Empirical Likelihood Abstract We develop an empirical likelihood framework for testing return predictability in the conditional mean and conditional quantiles. A unified chi-square limit theory is established across a broad spectrum of predictor persistence, including stationary, mildly integrated, nearly integrated, unit-root, and mildly explosive cases. We provide two complementary approaches to handle the unknown intercept: (i) a sample-splitting approach under relaxed regularity conditions and (ii) a new two-stage method that improves efficiency and accommodates quantile inference, where sample-splitting is infeasible. We examine the finite-sample bias of the two-stage method, and propose a bias-correction scheme and gradually saturated weights that improve performance under high persistence. Simulation evidence demonstrates that our tests exhibit competitive size and power across persistence classes, with notable gains in quantile predictability. An empirical application to the U.S. stock market shows modest evidence of mean predictability, whereas quantile-based inference reveals stronger and economically relevant predictability in the tails of the return distribution.
By Seok Young Hong; Nanyang Technological University
Presented by: Seok Young Hong, Nanyang Technological University
Session 15: Education I July 28, 2026 17:20 to 18:50 Location: Indonesia Room (level 5)
Session Chair: Yang Tang, Nanyang Technological University
Session type:
1. Regulating Private Tutoring: A Quantitative Analysis of Human Capital and Inequality Abstract To study the regulation of private tutoring, this paper develops a quantitative partial-equilibrium overlapping-generations model with heterogeneous households, endogenous ranking-based college admission, and intergenerational human capital transmission. The model allows private tutoring to affect exam performance and productive human capital differently, making it possible to distinguish its competitive and productive roles. Calibrated to Chinese microdata and empirical estimates, the model is used to compare a complete ban on private tutoring, a ban with imperfect enforcement that allows black-market tutoring, and a tutoring tax that finances public education. The results show that a complete ban is generally costly in the benchmark economy, especially when tutoring contributes to productive human capital. When enforcement is imperfect, black-market tutoring partly mitigates these losses but also becomes a major source of additional inequality by favoring households with better access to informal tutoring channels. By contrast, a tutoring tax improves welfare relative to both laissez-faire and a ban while keeping mean child human capital close to the benchmark.
By Zixiao YANG; Hokkaido University
Presented by: Zixiao YANG, Hokkaido University
2. Optimal Education Design Abstract This paper studies the optimal design of education. The principal designs an education mechanism by offering an information structure and an educational system for a society. A grand mechanism combining information design and mechanism design can change the beliefs of the firms, while satisfying incentive compatibility for individuals joining the education mechanism. The main result establishes that the optimal education involves a partially informative signal, dominating both the fully informative signal and the fully uninformative signal. It also shows that an over-investment in human capital and an over-education may stem from a systematic expansion of higher education.
By Gea M. Lee; Singapore
Presented by: Gea M. Lee, Singapore
3. Left-behind Children, Human Capital Accumulation and Internal Migration Abstract Internal migration often entails a family co-residence margin that standard spatial analyses treat implicitly: when adults move for work, children may remain in the origin as left-behind children or move as migrant children. We develop an overlapping-generations spatial general-equilibrium model in which adults choose a work location and whether to bring children. Children’s human capital is produced from parental time, private material inputs, and school inputs. Left-behind children receive less parental time, whereas migrant children can face weaker school support when destination access is restricted. We calibrate the model to China, where hukou-based schooling rules systematically disadvantage migrant children. In the baseline calibration, counterfactuals show that fully removing these restrictions is optimal: output rises in the short run as workers reallocate toward more suitable locations, and long-run gains are larger because improved child co-residence and schooling access raise aggregate human capital in addition to improving spatial labor allocation. However, uniform relaxation can crowd destination educational resources and accelerate population outflows from some origins, reducing local output. We therefore quantify differentiated, city-specific relaxation policies and show that targeted designs can raise output across cities without harming resident children.
By Yang Tang; Nanyang Technological University    Jingwei Zhou
Presented by: Jingwei Zhou,
4. Efficiency assessment of the quality-related research (QR) funding: the case of England's Higher Education Abstract Quality-related research (QR) funding in England distributes funds to HEPs based on each HEPs’ research performance reported in the Research Excellence Framework (REF). The REF has, since its inception, seen two iterations – REF2014 and REF2021. The REF represents a clear example of quality of research output being linked to greater allocation of funding – which in turn is assumed to lead to further quality research output. Producing quality research is however challenging because academics face time and financial constraints; and HEPs must efficiently utilise the QR funding. However, there is no evidence on whether the QR funding allocation from the REF2014 results has been efficient in leading to quality research output in the REF2021. The focus of this paper is thus to assess whether the QR funding allocation, based on the REF2014, has led to HEPs operating more efficiently in the production of quality research. We employ the Network Slacks-Based Measure (NSBM) model to measure the efficiency of England’s HE research performance based on the REF data. These NSBM efficiency scores are then regressed in the second stage to determine sources of efficiency. Our findings reveal that QR funding contributes towards efficiency in research thus confirming the success of the REF performance-based funding approach. Our findings also suggest that HEPs can be successful in attracting funds by considering increasing the number of PhDs by publication, using their knowledge and experience to improve on previous impact case studies, and developing research collaborations with other HEPs. Keywords: Quality-related research funding; Research Excellence Framework; Efficiency; Higher Education Providers
By Boon Lee; Queensland University of Technology
Presented by: Boon Lee, Queensland University of Technology
Session 16: Financial I July 28, 2026 17:20 to 18:50 Location: Philippines Room (level 5)
Session Chair: M Kabir Hassan, University of New Orleans
Session type: invited
1. Foregone Growth and Missing IPO: the Effects of A Delisting Risk from the HFCAA Abstract This paper quantifies the impact of a stock market regulatory pressure on firms' investment and financing decisions during the recent U.S.-China geopolitical tension. Adopted in December 2021 by the SEC, the Holding Foreign Company Accountable Act (HFCAA) imposes a delisting risk for the U.S.-listed China Concept Stocks. At the intensive margin, we find that after the HFCAA, relative to the peers listed on the Hong Kong stock market, the growth rate of investment in innovation of the U.S.-listed Chinese firms has decreased by 4 to 12 percentage points. This finding is robust to the self-selection of firms' IPO location choice and is consistent with the heterogeneous impact of the HFCAA across firms with different delisting risk and reliance on equity finance. At the extensive margin, the post-HFCAA Chinese issuers in the U.S. market are significantly smaller and of lower quality, raising about 20 percent less in proceeds. The relative attractiveness of U.S. exchanges declines, with 7 to 10 percent of Chinese firms switching from U.S. to Hong Kong listings.
By Yawen Liu; Nanyang Technological University    Guiying Laura Wu; Nanyang Technological University
Presented by: Yawen Liu, Nanyang Technological University
2. Digital Transformation and Stock Price Crash Risk: Evidence from China Abstract This study examines how corporate digital transformation (DT) impacts stock price crash risk using a sample of Chinese listed firms (2000-2024). We hypothesize that DT mitigates crash risk by enhancing information transparency and optimizing resource allocation. Using text analysis of annual reports, we construct two DT measures: Digital Transformation Intensity (DTI) and Propensity (DTP). Crash risk is measured by negative return skewness (NCSKEW) and down-to-up volatility (DUVOL). Our panel regressions with fixed effects reveal a significant negative relation between DT and future crash risk. Results are robust to instrumental variables, propensity score matching, and alternative model specifications. Mechanism tests indicate DT reduces crash risk by improving information quality and enhancing resource allocation efficiency. The effect is stronger in firms with superior governance, greater digital maturity, and non-high-tech sectors, with Artificial Intelligence and Integrated Applications being the most effective technologies. This study contributes to literature by shifting the focus from operational benefits of DT to its role in mitigating extreme financial risk, and by identifying DT as a significant firm-level determinant of crash risk, particularly for emerging market firms in complex regulatory environments.
By Xinyan Feng; Macau University of Science and Technology    Min Sun; Macau University of Science and Technology    John Fan Zhang; Macau University of Science and Technology
Presented by: John Fan Zhang, Macau University of Science and Technology
3. Overreacting to Information Events: Composite Beliefs and Two-Step Updating Abstract Accurate probability judgments are central to economic decision-making, yet substantial evidence shows systematic departures from Bayesian updating. Most existing work studies beliefs about simple events (e.g., a single state), where inference maps directly from signals to posteriors. In many economically relevant settings, however, agents must assess composite events—such as whether an informative regime is present—where beliefs require aggregating probabilities across multiple underlying states. Because composite-event judgments naturally invite aggregation and decomposition, they may generate deviations that differ from single-state updating. Moreover, measured beliefs may depend on the elicitation procedure itself if the procedure makes intermediate conditioning salient. This study examines whether and how beliefs about a composite event deviate from Bayesian updating and whether such deviations depend on elicitation design. We conduct an incentivized urn-learning experiment with repeated draws within each trial. One urn produces uninformative signals (equal color composition), while two urns produce informative signals with opposite skews. Participants report the probability that the underlying urn is one of the informative urns (a composite event) after each draw. Deviations are measured relative to the Bayesian posterior implied by the objective prior and observed signal history. To identify the role of intermediate conditional reasoning, we compare two elicitation treatments that hold the information structure and incentives fixed. In the one-step treatment, participants directly report the probability of the composite event. In the two-step treatment, participants first report the conditional probability of one informative urn relative to the other, explicitly conditioning on the event that the urn is informative, and then report the probability of the composite event. We also vary the prior environment (a baseline-prior condition versus an equal-prior condition) to assess whether elicitation effects depend on the prior structure. In addition, we implement a benchmark treatment that elicits beliefs about a single state (one informative urn) rather than a composite event. Three findings emerge. First, deviations in composite-event beliefs from the Bayesian posterior evolve strongly within a trial and tend to drift upward as signals accumulate, indicating systematic departures from one-step Bayesian updating. Second, the elicitation format matters: making the intermediate conditional judgment explicit changes the time profile of deviations, with effects concentrated in particular periods and with direction and magnitude that depend on the prior environment. Third, deviations are specific to composite-event beliefs: the single-state benchmark exhibits distinct dynamics, suggesting that aggregation across states is an important source of systematic error. These results provide clean causal evidence that composite-event beliefs are not invariant to the elicitation procedure. They also complement recent theory emphasizing that deviations from Bayesian benchmarks can arise from the internal organization of inference (Nakasato et al., 2025), rather than solely from biased priors or biased signal perception. A finance implication is that the uninformative urn can be interpreted as a no-information-event regime and the informative urns as information-event regimes. If investors form beliefs sequentially—first classifying signals as informative and then inferring direction—information-event beliefs may spread rapidly, while no-information events may be over-attributed, creating temporary mispricing driven by noise. Keywords: Composite-event beliefs; belief elicitation; information events; Bayesian updating; sequential inference; mispricing; investor overreaction; learning; experimental finance JEL codes: G41; D83; D81; C91
By Munenori Nakasato; Aoyama Gakuin University    Hirotaka Fushiya; Aoyama Gakuin University    Tomoki Kitamura; Musashi University
Presented by: Tomoki Kitamura, Musashi University
4. A novel cash waqf model: Leveraging US non-profit and endowment frameworks Abstract This paper proposes a scalable cash waqf model that embeds Islamic charitable endowments within the United States non-profit and endowment infrastructure. Each waqf is organized as a donor-restricted endowment subfund of a single 501(c)(3) public charity governed by the Uniform Prudent Management of Institutional Funds Act (UPMIFA), combining perpetual preservation of principal with donor-purpose restrictions, fiduciary oversight, transparent reporting, and cy-pres flexibility. The model specifies the legal vehicle, Shariah governance architecture, purification and forced-divestment protocols, and a tiered cross-border compliance framework incorporating OFAC, AML/CFT, and foreign-grant requirements. A centralized online platform enables donors to support specific Shariah-compliant projects while professionally managing the pooled endowment and smoothing distributions across market cycles. Empirical viability is assessed through a conservative AAOIFI-based, point-in-time screening of the S&P 500 from January 2011 to December 2024, using QuantConnect/Morningstar fundamentals, SEC EDGAR XBRL data, and NLP-based qualitative compliance flags. Even under stricter-than-mainstream screening and unsophisticated portfolio construction, the leading large-cap strategies preserve the real value of the corpus, produce positive annual distributions, and generate 36-39 cents of charitable payout per dollar contributed over the sample window. The findings indicate that a US-anchored cash waqf platform can address longstanding governance, sustainability, and transparency constraints while offering a legally robust and empirically feasible model for Islamic social finance.
By M Kabir Hassan; University of New Orleans
Presented by: M Kabir Hassan, University of New Orleans
Session 17: Industrial Organization I July 28, 2026 17:20 to 18:50 Location: Cambodia Room (level 5)
Session Chair: Justin Lin, Peking University
Session type: invited
1. Input Price Discrimination and Innovation under Passive Partial Forward Ownership Abstract The objective of this paper is to examine how input price discrimination under passive partial forward ownership (PPFO) affects downstream producers’ incentives to invest in cost-reducing R&D and the resulting market outcomes. Based on a vertically related industry framework, this paper shows how PPFO affects the upstream input supplier’s pricing strategy and the strategic R&D investment of the producers. We consider a two-tier industry in which a monopolistic input supplier (hereafter, “supplier”) provides an essential input to two downstream producers (hereafter, “producers”) that compete in quantity. The supplier holds a minority equity stake in one of the producers without exerting control over its strategic decisions. Both producers can invest in cost-reducing R&D. A three-stage game is considered under uniform and discriminatory pricing regimes. With knowledge of whether the supplier engages in uniform or discriminatory pricing, producers choose R&D investment in the first stage, the supplier sets the input price(s) in the second stage, and producers choose their outputs in the third stage. The equilibrium concept employed is the subgame perfect Nash equilibrium, which is solved by backward induction. Our results show that the interaction between PPFO and pricing regimes generates different R&D incentives across pricing regimes. Under uniform pricing, the shared-profit effect leads to an asymmetry in producers’ R&D incentives. The cross-owned producer retains only a fraction of its R&D returns, while the independent producer can free ride on the cross-owned producer’s R&D through a lower uniform input price. As a result, the cross-owned producer’s R&D decreases, and the independent producer’s R&D increases as the degree of PPFO rises. In contrast, under discriminatory pricing, the supplier can set input prices across producers and internalize the shared-profit effect exclusively to the cross-owned firm. Therefore, the supplier offers a lower input price to the cross-owned firm to stimulate its output and enhance the profit derived. Anticipating this, the cross-owned producer has stronger incentives to invest in R&D, and its investment increases with the degree of PPFO. However, the independent producer has weaker incentives to invest in R&D due to a higher input price. Consequently, the ranking of R&D investment reverses across pricing regimes. The differences in cost-reducing R&D incentives generate distinct market outcomes. The input prices under discriminatory pricing decline with the degree of PPFO and are lower than the uniform input price under uniform pricing. Furthermore, under uniform pricing, the independent producer produces more output than the cross-owned producer. However, under discriminatory pricing, the cross-owned producer produces more output than the independent producer. Our results also characterize the supplier’s preference over pricing regimes. When the degree of PPFO is low, the supplier prefers uniform pricing because higher input prices generate higher revenue, and the derived shared profit is limited. However, as the degree of PPFO rises, the importance of shared profit increases, and discriminatory pricing becomes more attractive because the supplier can stimulate the cross-owned producer’s output and enhance the shared profit through an input price reduction. Thus, the optimal pricing regime of the supplier depends critically on the degree of PPFO. Finally, the welfare implications are examined. In the absence of PPFO, total output under discriminatory pricing is lower than that under uniform pricing due to weaker R&D incentives. Consumer surplus and social welfare are higher under uniform pricing than under discriminatory pricing when the degree of PPFO is low. As the degree of PPFO rises, total output under discriminatory pricing increases monotonically, mainly driven by the output expansion of the cross-owned producer. Consumer surplus and social welfare under discriminatory pricing dominate those under uniform pricing when the degree of PPFO is sufficiently high. Thus, the conventional view that price discrimination deters producers’ R&D incentives and is welfare-reducing may not hold when the vertical ownership structure is considered. This paper contributes to the literature by demonstrating that PPFO fundamentally reshapes the effect of price discrimination on producers’ cost-reducing R&D, market competition, and welfare. Our results underscore important policy implications that antitrust authorities should consider the degree of PPFO when evaluating input price discrimination. Keywords: Passive partial forward ownership, Price discrimination, Innovation, Competition, Welfare JEL classification: D43, L13
By Chih-Chen Liu
Presented by: Chih-Chen Liu,
2. Competing Narratives and Trading Imbalance: Evidence from MD&A-News Disagreement Abstract This paper examines how disagreement between managerial and external narratives affects trading imbalance around annual report disclosures. We measure disagreement using the tone gap between MD&A and short-window news coverage. We argue that when the two narratives diverge, investors face competing interpretations of firms’ future prospects. Rather than passively waiting for consensus, sophisticated investors actively adjudicate between these narratives and translate their judgments into one-sided trades. Consistent with this view, we find that greater disagreement is associated with a higher absolute buy-sell imbalance. This effect is driven mainly by large trades, suggesting an important role for investors with stronger information-processing capacity. Further analyses show that the effect is stronger when firm information is harder to process and when managerial credibility is lower. Overall, our evidence suggests that disagreement across soft-information channels increases trading imbalance by inducing sophisticated investors to arbitrate competing narratives.
By Ruixin Fan; Beijing Jiaotong University    Mingya Hu; Harbin Institute of Technology
Presented by: Mingya Hu, Harbin Institute of Technology
3. Conditions for Being Chosen: Cybersecurity-Related Organizational Capability and Firm Performance among SMEs Abstract This paper examines the impact of cybersecurity-related organizational capability on firm performance for Japanese small and medium-sized enterprises (SMEs). In many markets, cybersecurity is no longer merely an internal matter of risk management; it is increasingly becoming part of the conditions under which firms are screened, trusted, and retained by business partners. This shift is especially important for SMEs, which often face tighter resource constraints, weaker reputational buffers, and greater dependence on specific supplier and buyer relationships than large firms. For such firms, cybersecurity investment may matter not only because it reduces the expected costs of cyber incidents, but also because it affects market outcomes through external evaluation. The paper therefore asks whether observable cybersecurity-related organizational capability influences firm sales. The analysis is motivated by recent institutional changes in Europe and the United States. Regulatory and governance frameworks such as NIS2, the Cyber Resilience Act (CRA), DORA, and CMMC have strengthened the role of auditable cybersecurity-related capability in supplier screening, procurement, certification, and market access. These developments suggest a broader institutional shift in which cybersecurity and related governance practices increasingly function as non-price conditions for market participation. In this environment, the relevant economic question for SMEs is not only whether cybersecurity investment reduces expected loss, but also whether it affects firm performance through credibility, continuity, and trust in exchange relationships. Using panel data on Japanese SMEs, the paper focuses on two observable dimensions of cybersecurity-related organizational preparedness: the existence of an information-security policy and the implementation of technical security control measures. The empirical analysis relates firm sales to these variables in a pooled panel framework with prefecture and year fixed effects. The outcome variable, sales, does not directly measure whether a firm is selected or retained by business partners in a strict sense. However, it provides a useful product-market outcome because favorable supplier evaluation, smoother transactions, stronger credibility with counterparties, and improved organizational trust may plausibly be reflected in business performance. The results reveal a clear difference between the two dimensions of preparedness. More developed technical security control measures are positively associated with higher firm sales, whereas the relationship is weaker and less robust for the formal existence of an information-security policy alone. This pattern suggests that implemented organizational capability may matter more than declaratory commitment by itself. Firms may benefit not simply from stating that cybersecurity is important, but from actually developing operational safeguards that can support reliability and trust in market exchange. The paper interprets this result through two possible mechanisms. One is protective: firms with stronger technical safeguards may experience fewer disruptions, greater operational stability, and more reliable business processes. The other is selection-related: firms with more developed cybersecurity capability may be more likely to be trusted, retained, or preferred by buyers and other external stakeholders in market environments where security-related requirements are becoming more salient. Although the present empirical design does not separately identify these channels, the evidence is consistent with the possibility that both are relevant. More broadly, the contrast between formal policy and implemented capability is also consistent with the idea that external stakeholders may respond more strongly to realized organizational practice than to symbolic commitment alone. The contribution of the paper is threefold. First, it reconceptualizes cybersecurity capability for SMEs as an economically relevant organizational investment rather than as a purely defensive or regulatory burden. Second, it provides empirical evidence that implemented technical capability is more strongly linked to firm performance than formal policy alone. Third, it contributes to a broader conceptual understanding of how compliance-related organizational capability can affect market outcomes through non-price evaluation, trust formation, and continued participation in exchange relationships. By linking cybersecurity capability to firm performance in the SME context, the paper highlights a wider economic role of organizational preparedness in increasingly demanding market environments.
By Etsusaku Shimada; Iwate Prefectural University
Presented by: Etsusaku Shimada, Iwate Prefectural University
4. Crossing the Innovation Threshold: Capital Accumulation and R&D Activity Abstract This paper examines how capital accumulation shapes regional innovation by determining whether firms and regions can cross a critical capital threshold for R&D entry. I develop a simple two-period model in which firms decide whether to undertake research and development (R&D) in the presence of a fixed cost of innovation. In the model, the returns to R&D increase with productive scale, so the relationship between capital accumulation and innovation is inherently nonlinear. When the capital stock remains below a critical level, firms do not engage in R&D because they cannot profitably cover the fixed cost. Once the capital stock exceeds this threshold, however, innovation becomes viable and R&D activity rises with capital. Financial frictions reinforce this mechanism by restricting external borrowing, slowing capital accumulation, and delaying or preventing threshold crossing. To test these predictions, I construct a panel dataset for Chinese provinces and estimate a panel threshold regression in which innovation activity is proxied by R&D expenditure as a share of GDP. This empirical approach allows the effect of capital on R&D activity to vary across regimes defined by the level of capital accumulation. The estimation results suggest the presence of a threshold effect in the relationship between capital and innovation. When capital remains below the estimated threshold, its impact on R&D intensity is limited. Once the threshold is crossed, however, the marginal effect of capital becomes substantially larger, broadly consistent with the model’s central prediction. These findings suggest that regional disparities in innovation are shaped not only by differences in technological opportunities or industrial structure, but also by differences in the extent of capital accumulation. More specifically, the central implication of the paper is that R&D activity does not increase smoothly with capital, but becomes more active once the capital stock exceeds a critical threshold. The paper contributes to the literature by identifying this threshold mechanism linking capital accumulation to R&D. Financial frictions matter primarily because they affect whether firms or regions can reach that threshold. More broadly, the analysis provides a perspective on heterogeneity in regional innovation performance in China, while also offering a way to interpret the recent rise in R&D activity as part of a broader shift in the stage of development associated with capital accumulation.
By Tao Gu; Daito Bunka University
Presented by: Tao Gu, Daito Bunka University
Session 18: Labor I July 28, 2026 17:20 to 18:50 Location: Brunei Room (level 5)
Session Chair: Soo Keong Yong, Universiti Brunei Darussalam
Session type: invited
1. Closing the Psychological Distance: Effect of Social Interaction on Team Performance Abstract Social interaction in workplaces fosters mutual understanding and narrows psychological distances between team members. We model this interdependence in team production with complementary efforts, examining how social interaction improves team performance. Our theoretical framework predicts that social interaction enhances performance by reducing the prosociality gap—the differences in how much teammates care about each other—among team members, with stronger effects in teams with higher effort complementarity and loss aversion. We tested these predictions in a pre-registered experiment with 74 two-person teams performing a collaborative typing task. Treatment teams engaged in a structured pre-task social interaction, while control teams worked individually. Results confirm that social interaction significantly reduced the prosociality gap and improved team performance. We find that the reduction in the prosociality gap mediates the effect of social interaction on performance improvement. Furthermore, emotional perceptiveness-the ability to accurately infer a teammate's feelings-emerged as a particularly strong and positive mediator of the effect of social interaction, facilitating convergence in prosociality between teammates. Moderation analyses demonstrated that these positive effects were stronger in same-gender teams and teams with higher loss aversion. Our findings contribute to the team effectiveness literature by identifying specific psychological mechanisms through which social interaction enhances performance, offering implications for team composition and management practices. Keywords: team production, social interaction, prosociality, peer effects, emotional perceptiveness, lab experiment JEL Classification: C72; C92; D91; M54; J24
By Keisuke Hattori; Aoyama Gakuin University    Mai Yamada; Nihon University
Presented by: Mai Yamada, Nihon University
2. Pay Equity and Worker Outcomes: Evidence from New Zealand’s Social Worker Settlement Abstract We analyse the effects of the 2023 pay equity settlement for social workers on worker outcomes in New Zealand. Pay equity settlements are policy interventions that raise wages in female-dominated occupations to address gender-based undervaluation. We quantify the effects of the settlement using data from Stats NZ’s Integrated Data Infrastructure (IDI), which links population-wide administrative and survey data from government agencies and other organisations. We identify social workers using census occupation data, while tax records are used to track earnings and employment over time. Additional wellbeing indicators are derived from health service use and justice system data. We estimate effects using a difference-in-differences design, comparing social workers to unaffected employees before and after the settlement, and we examine heterogeneity by baseline earnings and demographic characteristics. We find that the pay equity settlement led to large, statistically significant increases in earnings and hourly wages, alongside reductions in benefit receipt and victimisation, and improvements in mental health.
By Lisa Meehan; Auckland University of Technology    Gail Pacheco; Auckland University of Technology    Thomas Schober; Auckland University of Technology
Presented by: Lisa Meehan, Auckland University of Technology
3. Demography on Fertility and Migration: A Quantitative Spatial Analysis Abstract By integrating individual life cycles with endogenous fertility decisions into a dynamic spatial economic framework, we analyze the interaction between fertility and migration, which jointly shape population size, distribution, and welfare. We apply this framework to China, a country characterized by a vast population, large-scale internal migration, and substantial regional variation in fertility. Counterfactual analyses suggest that halving excessive migration costs to major cities raises average welfare by 2.4%, while lowering inequality and total population by 4.8% and 4.7%, respectively. Moreover, China's 2025 universal birth subsidy may boost population and welfare, but accounting for spatial heterogeneity would significantly enhance its effectiveness.
By Ting Ji; Central University of Finance and Economics
Presented by: Ting Ji, Central University of Finance and Econom
4. Wartime Unemployment: A Comparative Study on the Russia-Ukraine War Abstract Does war impose a differential impact on nations involved in military conflict? This paper investigates the causal impact of war on unemployment, using the Russia-Ukraine war that begins in 2022 as a comparative case study. Using the synthetic control method to construct counterfactual trajectories, our findings reveal that Russia experienced a decline in unemployment in the first three years following the onset of the military action, averaging 0.8 percent below the no-war counterfactual, consistent with wartime labor mobilization and military expenditure. By contrast, Ukraine suffered a substantial rise in unemployment over the same period, averaging approximately 11.4 percent above its counterfactual benchmark. Our study contributes to the understanding of the economic costs of international conflict by documenting an asymmetric effect of war on labor markets in both the initiating and the target states.
By Soo Keong Yong; Universiti Brunei Darussalam
Presented by: Soo Keong Yong, Universiti Brunei Darussalam
Session 19: Macroeconomics I - Monetary July 28, 2026 17:20 to 18:50 Location: Vietnam Room (level 5)
Session Chair: Keen Meng Choy, Soka University
Session type:
1. Monetary Policy in a Small Open Economy - from Trilemma to Operational Execution: Evidence from Indonesia Abstract Indonesia has navigated significant external volatility during recent global tightening phases, characterized by capital outflows and currency depreciation. In response, Bank Indonesia (BI) has transitioned toward a ``pro-market'' policy mix by introducing self-issued securities: Bank Indonesia Rupiah Securities (Sekuritas Rupiah Bank Indonesia -- SRBI) and Bank Indonesia Foreign Currency Securities (Sekuritas Valas Bank Indonesia -- SVBI). This thesis provides a comprehensive theoretical and empirical analysis of these instruments, establishing a unified framework that connects strategic policy mandates with operational market microstructure. Standard New Keynesian models typically rely on the assumption of a perfect ``First-Stage'' of Transmission, where the central bank's policy rate maps one-to-one onto market rates through frictionless arbitrage. However, this model breaks from that convention by micro-founding the Operational Stage of monetary policy through the lens of a \textit{Separation Principle}. This principle allows the central bank to decouple its strategic signaling---the policy rate---from its operational implementation---liquidity absorption---thereby expanding the policy frontier in a small open economy. We argue that in an emerging market context, structural frictions—specifically the oligopsony power of systemic banks and the resulting structural excess liquidity —render the standard New Keynesian interest rate channel ineffective. By internalizing these frictions, this research provides a novel hierarchical approach to the ``Impossible Trinity,'' utilizing an \textit{Separation Principle} mechanism where market rates are spiked via SRBI quantity targets to defend the currency even while the policy rate remains conducive to domestic growth. This paper establishes the foundation through the ``Hierarchical Integrated Small Open Economy (SOE) Model.'' The framework demonstrates that in a regime of structural surplus, standard passive absorption fails to maintain policy control. It proves that tradable instruments like SRBI and SVBI are strictly necessary to generate the ``scarcity rents'' required to close the Interbank Decoupling Wedge ($\tau_t$). Crucially, the calibrated simulations reveal a substantial Welfare Gain compared to a Standard Taylor Rule benchmark. By avoiding the ``Taylor Recession''---where a blunt policy rate hike crushes the output gap to defend the currency---the optimal use of SRBI reduces the peak output contraction by approximately $0.50$ percentage points. This real-economy shielding translates directly into a significant reduction in the central bank's quadratic welfare loss (yielding a net gain of $+0.2928$ units), confirming that the quantity-based Separation Principle is strictly welfare-superior to a pure price-based defense. Furthermore, simulations identify a ``Structural Hedge'' in the central bank's post-pandemic balance sheet, suggesting that the quasi-fiscal costs of aggressive sterilization are naturally mitigated by the indexed variable-rate returns of the underlying government bond collateral.
By Frita Amrita; University of Reading
Presented by: Frita Amrita, University of Reading
2. Does Monetary Policy Matter Asymmetrically for Clean Energy Investment? Evidence from Malaysia Abstract This study examines the determinants of clean energy investment in Malaysia, with a particular focus on the asymmetric effects of monetary policy. In recent decades, rapid industrialization and urbanization have intensified energy demand, largely met through fossil fuels, thereby exacerbating environmental degradation, climate change, and threats to biodiversity and food security. As a developing economy vulnerable to climate risks, Malaysia faces increasing pressure to accelerate its transition toward a low-carbon future in line with its net-zero emissions target by 2050. This study investigates the role of monetary policy, urbanization, green growth, and green technology innovation in shaping clean energy investment. Using annual data from 1991 to 2022, the analysis employs a nonlinear autoregressive distributed lag (NARDL) model to capture asymmetric effects, complemented by a symmetric ARDL model and threshold regression for robustness. The NARDL results reveal a significant asymmetric effect of monetary policy on clean energy investment in Malaysia. In the long run, positive monetary shocks significantly reduce clean energy investment, while negative shocks are insignificant, which confirming asymmetry. In the short run, monetary easing exerts a negative and significant effect that suggests constrained investment responses. Green technology innovation consistently promotes clean energy investment, whereas green growth and urbanization are insignificant. In contrast, the symmetric ARDL model shows an insignificant effect of monetary policy, implying that linear specifications mask important dynamics, while green technology remains a positive determinant and urbanization becomes significantly negative. Robustness checks using a threshold model confirm that monetary policy negatively affects clean energy investment across regimes, with weak evidence of asymmetry. These findings provide valuable insights for policymakers in designing effective strategies to facilitate Malaysia’s transition toward a sustainable and resilient green economy.
By Kwang-Jing Yii; Swinburne University of Technology Sarawak Campus    Maggie May-Jean Tang; Swinburne University of Technology Sarawak Campus    Siew-Ling Liew; Swinburne University of Technology Sarawak Campus    Chin-Hong Puah; Faculty of Economics and Business, Universiti Malaysia Sarawak
Presented by: Kwang-Jing Yii, Swinburne University of Technology Sarawak Campus
3. Inflation Puzzle in Great Recession: A Semi-Structural Macroeconometric Perspective Abstract This paper applies a small-scale DSGE-VAR model, which is standing at a semi-structural macroeconometric perspective, to study the inflation puzzle that occurred during and after the Great Recession. Specifically, the inflation puzzle refers to the “missing inflation” and “missing disinflation”, reflecting the relative insensitivity of inflation dynamics to economic shocks compared with the changes in real economic activity, a phenomenon commonly described as the flattening of the Phillips curve. We apply the Bayesian approach to estimate the model in a rolling-sample way and obtain the time-varying estimates of interest, including the parameters within the VAR and DSGE models as well as the impulse response functions. The findings suggest that the model is suited to study the inflation puzzle. Importantly, the implied flattening of the Phillips curve can be traced back to the mid-1980s, indicating that the puzzle may have existed before the Great Recession. Regarding its underlying causes, we conclude that the inflation puzzle stems from the central bank’s aggressive stance toward monetary policy operations since the mid-1980s, particularly in countering the inflation fluctuations.
By Kuo-Hsuan Chin; Feng Chia University
Presented by: Kuo-Hsuan Chin, Feng Chia University
4. Debt Structure and the Changing Transmission of Global Shocks to Emerging Market Economies: Evidence from U.S. Monetary Policy Shocks and Global Risk Shocks Abstract Abstract: This paper examines how post–Global Financial Crisis (GFC) shifts in emerging market economies’ (EMEs) external financing—from cross-border bank loans to international bond markets, and from bank to non-bank lenders—have altered the transmission of global shocks. Using BIS banking and debt securities data and Arslanalp–Tsuda sovereign holder data, we document these structural changes for 18 EMEs over 2000–2024, with a particular emphasis on emerging Asia, where the shift from cross-border bank loans to international bond markets has been particularly pronounced. To assess macroeconomic effects, we estimate panel local projections with country fixed effects. We analyze two shocks: (i) a 10-basis-point U.S. monetary policy shock identified following Jarociński and Karadi (2020), and (ii) a global risk shock proxied by the VIX. To capture heterogeneity, we interact shocks with external bond dependence. We find that U.S. monetary tightening leads to larger and more persistent GDP declines in bond-dependent EMEs. In contrast, global risk shocks initially affect loan-dependent EMEs more strongly, reflecting the bank-lending channel. Since 2013, however, risk shocks increasingly transmit through bond markets, indicating a shift toward market-based financial transmission as non-bank investors have gained prominence. JEL codes: F30, F34, F42, G23 Keywords: capital flows, cross-border bank loans, international bond markets, nonbank financial institutions, global shocks, emerging market economies
By Masahiro Enya; Osaka Gakuin University
Presented by: Masahiro Enya, Osaka Gakuin University
Session 20: Asian I July 29, 2026 8:30 to 10:00 Location: Cambodia Room (level 5)
Session Chair: Jun Zhang, Fudan University
Session type: invited
1. When Global Capital Meets Local Regulation: Institutional Synergy and the BRI’s Impact on Singapore’s FinTech Ecosystem Abstract This study evaluates the causal impact of China’s Belt and Road Initiative (BRI) on cross-border FinTech venture capital allocation in Singapore. Using a strictly constrained Synthetic Control Method (SCM) with a pure, non-BRI donor pool, we identify a highly precise, event-driven structural break in capital inflows. Rather than a uniform trend, a massive, statistically significant investment premium occurred in 2017, perfectly coinciding with the formal signing of the bilateral BRI Memorandum of Understanding. We introduce the concept of “institutional synergy” to explain this phenomenon: the BRI’s external capital shock was profoundly magnified by Singapore’s internal absorptive capacity—specifically, the MAS FinTech Regulatory Sandbox launched in 2016. Our findings demonstrate that for international financial centers, capturing high-value digital spillovers requires adaptive domestic regulatory frameworks to successfully anchor global capital.
By Chen-Yu Li; National Taichung University of Science and Technology    NaiQian Zhang; Minjiang University    YuPin Hu; National ChiNan University
Presented by: Chen-Yu Li, National Taichung University of Science and Technology
2. Skills in Demand for the Accounting and Finance Profession: Evidence from Online Job Advertisements in Hong Kong and Singapore Abstract We apply the natural language processing techniques to analyse skills requirements in three samples of online advertisements for accounting and finance jobs in Hong Kong and Singapore. We find that employers’ demand for skills is consistent across the three samples and there is a remarkable pecking order of skills. While the skill requirements remain relatively stable over time, the demand for certain skills such as collaboration and team-working shows a strong increase in recent years. Moreover, there exist strong similarities but also notable differences between Singapore and Hong Kong. The findings are valuable to companies, tertiary institutions, and policy makers.
By Shaojun Zhang; The Hong Kong Polytechnic University
Presented by: Shaojun Zhang, The Hong Kong Polytechnic University
3. Quality Certification, Information Frictions, and Export Survival: Evidence from China Abstract In developing countries, export relationships are generally characterized by short survival durations, particularly in agricultural trade, where information frictions render trading ties more susceptible to disruption. From the perspective of information frictions, this paper investigates whether quality certification, as an institutionalized signal, can mitigate information asymmetry and enhance export survival. By matching ISO 22000 certification data with China's Annual Survey of Industrial Firms and the Chinese Customs Database, we construct a firm–destination panel dataset and employ a staggered difference-in-differences approach to identify the impact of quality certification on export relationship survival. The findings reveal that quality certification significantly reduces the probability of export market exit, thereby prolonging the duration of trade relationships. Mechanism analysis indicates that this effect primarily arises from the alleviation of information frictions: certification provides a verifiable quality signal that lowers transaction uncertainty and strengthens buyer trust. Further analyses show that the certification effect is more pronounced in contexts characterized by greater geographic distance, more intense industry competition, and high-income destination markets, suggesting that the role of certification strengthens systematically with the degree of information frictions. Meanwhile, certification also substantially raises firm compliance costs, underscoring a trade-off between signaling benefits and cost constraints. This study demonstrates that, within the context of developing countries, reducing information frictions constitutes a vital mechanism influencing export survival, thereby providing new micro-level evidence for understanding the dynamic features of agricultural trade.
By Xianhui Geng; Nanjing Agricultural Uniersity
Presented by: Xianhui Geng, Nanjing Agricultural Uniersity
4. Loose Costs: The Causal Impact of Urban Morphology in China on Criminal Offenses Abstract Abstract：In the subsequent phases of urbanization, China's urban development is undergoing a transition from incremental expansion to the optimization of existing urban infrastructure. However, the prevailing expansion model, which has historically relied on "land-based fiscal revenue," has resulted in pervasive urban sprawl, thereby precipitating a series of socioeconomic challenges. In light of these circumstances, the optimization of urban morphology and the development of "compact cities" have emerged as policy priorities. However, the full scope of their impact on social governance, particularly public safety, remains to be thoroughly examined. The objective of this study is to address this knowledge gap by conducting an empirical examination, from the perspective of "policy economics," to ascertain the causal effects of urban morphology on public safety levels and their underlying mechanisms. This study utilizes land cover data from the European Space Agency (ESA) for the period 2006–2020, employing scientific calculation to determine the spatial structure index (SSI)—defined as the average distance between any two points within a city—for 285 prefecture-level cities in China. The number of urban crimes, serving as a proxy for public safety levels. To address issues of endogeneity, we use the historical population size of a city to predict potential urban areas by a linear regression forecasting model and then calculate city shape index by this predicted area as the IV. The findings from both the baseline analysis and the robustness tests consistently indicate that a loose urban morphology significantly increases crime rates, thereby exerting a clear negative impact on public safety. The primary theoretical contribution of this study lies in the development and validation of an integrated "government-society" two-dimensional mechanism framework. The study posits that a dispersed spatial structure undermines public safety through two channels: The phenomenon under scrutiny has been demonstrated to exert a deleterious effect on the efficacy of government governance. This is primarily evidenced by a relative paucity of police resources, which in turn engenders a crowding-out effect on government spending on public conveniences. Consequently, this has the effect of constricting the provision of public services. The second element to consider is the reduction of social interaction. In urban areas characterized by sparse population density, there is often a concomitant decline in nighttime activity. This decline can result in a reduction of natural surveillance, which may have implications for public safety and urban planning. Concurrently, extended commutes and diminished interaction impede the accumulation of social capital, thereby eroding informal social control networks. A subsequent heterogeneity analysis yielded refined directives for policy design. The development of digital government can effectively offset efficiency losses caused by dispersed police forces. In areas with high population mobility, the impact of a dispersed urban morphology on crime rates is more pronounced, suggesting a need to strengthen social integration policies. This study offers novel evidence from developing countries for the interdisciplinary field of urban economics and criminology. Moreover, the study's conclusions provide direct policy guidance for China's current urban morphology planning and governance modernization reform. The text emphasizes the necessity of incorporating public safety into the core considerations of spatial policy, and of synergistically advancing the development of "compact cities" and "safe cities" through the optimization of spatial structures and the enhancement of social interaction.
By Ning Ma; Southeast University    Xiuyan Liu; Southeast University    Lu Chen; Southeast University
Presented by: Ning Ma, Southeast University
Session 21: Econometrics II July 29, 2026 8:30 to 10:00 Location: Singapore Room (level 5)
Session Chair: Qu Feng, Nanyang Technological University, Singapore
Session type:
1. Consistent generalized method of moments estimation of spatial autoregressive models based on non-Gaussian distributions Abstract This paper proposes the generalized method of moments (GMM) estimation of the spatial autoregressive (SAR) model using generalized linear and quadratic moments based on non-Gaussian distributions. We investigate both the cases with homoskedastic and heteroskedastic innovations. The proposed GMM estimator of parameters of interest is consistent and asymptotically normal under regularity conditions. It is computationally simple and can have significant efficiency improvement upon popular estimators of the SAR model. In the homoskedastic case, we provide conditions for the existence of best moments that generate a GMM estimator with the minimum asymptotic variance. Simulation experiments show that the considered GMM estimator performs well in finite samples.
By Fei Jin; Fudan University
Presented by: Fei Jin, Fudan University
2. A Structural Model of Volatility Term Structure: Deviations from the Square-Root-of-Time Rule under Trend-Following Behavior Abstract Medium- and long-horizon volatility measures are central to risk management, derivative pricing, and portfolio allocation. In practice, however, these measures are often obtained by scaling short-horizon volatility using the square-root-of-time rule (SRTR). This rule is valid only under the assumption that returns are independently and identically distributed, a condition that is frequently violated in financial markets. A large empirical literature documents systematic deviations from SRTR and proposes reduced-form corrections based on jumps, heavy tails, or time-series dynamics. While these approaches improve empirical fit, they do not provide a structural explanation for the joint emergence of return autocorrelation and volatility term structures. This study develops a simple structural model in which heterogeneous trading behavior generates both return autocorrelation and deviations from square-root volatility scaling. The model features sequential trade arrivals and three types of market participants: informed traders, trend followers, and noise traders. A key parameter is the proportion of trend-following traders. In this environment, trend followers induce serial dependence in order flow, which translates into return autocorrelation. This persistence, in turn, affects how volatility aggregates across time horizons. The model yields two central predictions. First, return autocorrelation is governed by the share of trend followers and is independent of the fraction of informed traders. Second, the volatility scaling factor becomes an explicit function of this behavioral composition, implying that volatility no longer scales with the square root of time when trend-following behavior is present. As a result, a single latent parameter jointly determines intraday return autocorrelation and the volatility term structure, providing a structural explanation for observed deviations from SRTR. The model also delivers a testable empirical implication: the proportion of trend followers, although unobservable, can be inferred from the relationship between short- and long-horizon volatility and should be systematically related to observed return autocorrelation. To test this implication, the paper uses high-frequency data on the Nikkei 225 index, sampled at 5-second intervals from August 2017 to October 2022. Short- and long-horizon volatility measures are constructed within intraday windows, and the implied proportion of trend-following traders is recovered from the model-implied volatility scaling relationship. Empirical results strongly support the model’s predictions. The inferred share of trend followers is positively and significantly associated with intraday return autocorrelation. Moreover, this relationship is state dependent. Trend-following behavior is more pronounced in favorable market conditions, such as bull markets and low-volatility regimes, and weaker when market noise is elevated. Instrumental variable estimates, using lagged autocorrelation as an instrument, confirm these patterns where identification is feasible. These findings suggest that belief-driven trading behavior plays a central role in shaping both price dynamics and volatility scaling. Overall, this study provides a structural, behavior-based interpretation of volatility term structures that complements and extends existing reduced-form approaches. By linking high-frequency trading behavior to medium- and long-horizon risk measurement, the paper offers a unified framework for understanding deviations from the square-root-of-time rule and highlights the importance of endogenous belief composition in financial markets. Keywords: Volatility term structure, Square-root-of-time rule, Trend-following behavior Return autocorrelation, High-frequency data, Heterogeneous agents, Market microstructure JEL Codes: G12, G17, D84, C58
By Hirotaka Fushiya; Aoyama Gakuin University    Tomoki Kitamura; Musashi University    Munenori Nakasato; Aoyama Gakuin University
Presented by: Hirotaka Fushiya, Aoyama Gakuin University
3. The Boundary of High-Frequency Trading and Low-Frequency Trading in the Limit Order Book Abstract This paper proposes a method to distinguish High-Frequency Trading (HFT) limit orders using the duration of limit orders. Through a survival analysis we observe that 85% of the submitted limit orders are canceled within 10.5 seconds. Orders outstanding within or beyond 10.5 seconds have extremely different sensitivities to microstructure changes on transaction costs and stock values. The likelihood of execution significantly rises since order submission, but stops rising after 10.5 seconds. These results are consistent with HFT’s features in SEC’s compilation and confirm the 10.5 seconds as the cutoff point to distinguish HFT.
By Kun Li; Beijing Normal University
Presented by: Kun Li, Beijing Normal University
4. The AH Premium is NOT A Puzzle: Evidence from A Quasi-experiment Abstract The substantial price differences between China's dual-class A and H shares have been considered as the consequence of market segmentation. This paper shows that as a specific channel of market segmentation, China's capital outflow controls depress the demand for H shares by domestic investors, thus inflate the price ratio of A and H shares. To empirically identify the causal effect of capital controls on the AH price premium, we leverage the Shanghai-Hong Kong Stock Connect launched in 2014 as an exogenous policy change, which allows cross-border investment under certain conditions. Consistent with our model predictions, this partial capital account liberalization reduces the AH price premium by at least 30%.
By Qu Feng; Nanyang Technological University, Singapore    Guiying Laura Wu; Nanyang Technological University    Mengying Yuan; South China University of Technology
Presented by: Qu Feng, Nanyang Technological University, Singapore
Session 22: Environmental I July 29, 2026 8:30 to 10:00 Location: Thailand Room (level 5)
Session Chair: Yang Zhang, University of Macau
Session type: invited
1. The credibility mechanism of Environmental Credit Rating influencing the high-quality development of enterprises: evidence from China based on three-dimensional credit theory Abstract Environmental Credit Rating imposes pressure on enterprises to promote environmental conservation and sustainable development through a credibility mechanism. Drawing on the three-dimensional credit theory, this study aims to examine the credibility mechanism of Environmental Credit Rating influencing the high-quality development of enterprises in terms of its three environmental credibility dimensions: environmental integrity, environmental compliance, and environmental contract observance. The robustness of the analyses is ensured through the application of a staggered Difference-in-Differences model along with the mediating effect and moderating effect analysis with a data set of 3,178 listed companies in China from 2012 to 2022, amounting to 24,214 observations. The research conclusion suggests that Environmental Credit Rating can exert a self-regulatory effect, compliance constraint effect, and incentive-guidance effect on enterprises. Among the three distinct effects, the self-regulatory effect is most influential and can be enhanced by an enterprise’s scale; the negative compliance constraint effect may be further bolstered by command-control environmental regulations, while the incentive-guidance effect can be reinforced by market-incentive environmental regulations. The primary focus of environmental credibility is environmental integrity, which differs from traditional credibility that prioritizes contract observance. These findings provide suggestions for optimizing the utilization of environmental credit evaluation policies and developing indicators for Environmental Credit Rating. Based on enhancing the comprehension of the impact path of Environmental Credit Rating on microagents, this research also provides a distinct perspective for analyzing the influence mechanism of novel governance tools characterized by information disclosure, such as corporate social responsibility reports, environmental reporting, and ESG ratings.
By Weili Zhao; Henan University of Economics and Law    Li Wang; Henan University of Economics and Law    Yilin Li; Henan University of Economics and Law
Presented by: Weili Zhao, Henan University of Economics and Law
2. The Future of Gulf Finance: Converging Signals from Fintech and Green Markets Abstract This study investigates the dynamic relationship between fintech innovation, green finance, and financial market behaviour in the Gulf Cooperation Council (GCC) economies. Employing a time-varying parameter vector autoregression (TVP-VAR) model alongside topic modelling of official green finance frameworks, we examine how fintech-related assets, particularly blockchain and digital finance indices, interact with green finance indicators, commodity markets, and regional stock indices. Results reveal an intensification of cross-domain connectedness, with fintech and clean energy indices emerging as influential volatility transmitters across GCC markets. Static and dynamic connectedness measures indicate structural reconfiguration in systemic risk transmission, while regression analysis confirms the increasing explanatory power of fintech and green assets relative to conventional drivers. A complementary textual analysis of policy frameworks reveals consistent references to transparency, ESG governance, digital infrastructure, and technological ambition, indicating a strategic integration of fintech into sustainable finance architectures. Together, these findings provide novel evidence of convergence between digital and green financial domains in the region, with implications for financial diversification, regulatory coordination, and the future design of climate-aligned investment systems.
By Mehmet Sahiner; University of Dundee
Presented by: Mehmet Sahiner, University of Dundee
3. Electric vehicles reduce driver injury severity but increase risk for other road users Abstract Electric vehicles (EVs) are approximately 20% heavier than internal combustion engine (ICE) vehicles due to battery mass and structural reinforcements. While this added mass enhances protection for EV occupants, it increases the kinetic energy transferred to other road users during collisions, exacerbating injury severity. We quantify the disparity in safety from more than 300,000 two-vehicle collisions in California, United States (US). Our findings show that while EV drivers face an 18% lower risk of serious injury or fatality, the risk for those colliding with EVs increases by 13% - an effect driven primarily by vehicle weight. Our estimates suggest that the external accident costs of EVs offset roughly one-third of their environmental benefits, indicating that EV adoption continues to improve overall social welfare. We anticipate our findings to have policy implications on regulating the weight of vehicle fleet as vehicle electrification becomes increasingly important to reduce transport carbon and pollution emissions.
By Cheng Keat Tang; Nanyang Technological University
Presented by: Cheng Keat Tang, Nanyang Technological University
4. Climate Risk Exposure Dampens Price Responsiveness in Electric Vehicle Charging Behavior Abstract Effective pricing is crucial for managing EV charging demand and supporting decarbonization, yet the influence of environmental risk on users’ price sensitivity is poorly understood. This paper examines how EV charging responds to price changes and whether responses differ by climate risk exposure. We use comprehensive 15 minute charging records from the citywide public parking network in Macao SAR—covering all EV users (including electric bikes) and all charger speeds—and exploit a citywide charging price adjustment as a quasi natural experiment. Difference in differences and triple difference estimates reveal substantial price elasticity: price reductions increase charging activity, while the introduction of charging fees significantly suppresses it. Crucially, elasticity is lower in flood prone, low lying areas, implying that users in climate vulnerable locations place greater weight on reliability and environmental risk, thereby muting their responsiveness to economic incentives. These findings document systematic heterogeneity in behavioral responses to energy pricing and show that climate adaptation considerations can materially weaken the effectiveness of price based demand management. The results inform the design of EV infrastructure investments and tariff structures in coastal cities facing rising climate risks.
By Yang Zhang; University of Macau
Presented by: Yang Zhang, University of Macau
Session 23: Financial II July 29, 2026 8:30 to 10:00 Location: Vietnam Room (level 5)
Session Chair: Huailu Li, National University of Singapore
Session type: invited
1. Car Impact on Credit Growth: A Comprehensive Assessment of Global, Advanced, and Emerging Market Countries Abstract This paper explores the dynamic relationship between banking sector resilience, credit growth, and economic output across 110 advanced and emerging economies. Using a two-stage empirical approach, it assesses both the indirect impact of banks’ capital adequacy ratios (CAR) on GDP growth through credit expansion and the direct impact of CAR on GDP. Panel Ordinary Least Squares (PLS) and Generalised Method of Moments (GMM) estimations are used to address endogeneity, feedback loops, and persistence in financial and macroeconomic variables. Results show that the indirect channel dominates where higher capital adequacy supports sustainable credit growth, which in turn stabilises GDP, especially in emerging markets where financial intermediation remains bank-focused. Conversely, the direct link between CAR and GDP growth is generally weak, indicating that the macroeconomic impact of capital regulation mainly works through the credit channel rather than directly affecting output. Additionally, advanced economies show weaker CAR–credit sensitivities due to more diversified financial structures, while emerging markets face stronger effects—highlighting the importance of pre-emptive capital buildup to help reduce downturns. The findings have significant macroprudential policy implications. Capital buffers act as stabilisers that absorb shocks and support lending during crises, as demonstrated during the COVID-19 pandemic when flexible CAR policies prevented credit contractions. For emerging markets, countercyclical capital accumulation is crucial to improve financial resilience before stress periods, while advanced economies benefit more from targeted capital and liquidity tools to manage cyclical risks. Overall, the study highlights the importance of integrating capital-based macroprudential frameworks with monetary and fiscal policies to strengthen systemic stability and promote growth.
By Aditya Taruna; The Australian National University
Presented by: Aditya Taruna, The Australian National University
2. Barbarian or Vanguard? : Private Equity Buyout and Physician Opioid Prescription Abstract The paper studies how private equity (PE) buyouts of physician groups affect physicians’ opioid prescribing behaviour. Using a difference-in-differences approach, we find that physicians in PE-owned physician groups relatively decrease their opioid prescription rates after the buyout. We further identify regulatory and litigation risks as the primary mechanism: the effect is most pronounced in states that adopt more stringent opioid monitoring programs and after a key legal precedent involving the False Claims Act increased the litigation risk for PE firms. Moreover, we document heterogenous responses across different types of PE firms. First, PE firms with fewer financial constraints ex ante are associated with a greater reduction in opioid prescription intensity. Second, PE firms with a stronger preference for corporate social responsibility (CSR) also have a larger reduction effect on physician opioid prescriptions.
By Chen Lin; The University of Hong Kong    Shihua Qin; Lingnan University    Xiang Shao; FUDAN UNIVERISTY    Jianfei Zhu; The University of Hong Kong (HKU)
Presented by: Jianfei Zhu, The University of Hong Kong (HKU)
3. Institutional Learning Effects Induced by Foreign Capital Inflow Expectations and Business Environment Construction: Evidence from the Diffusion of Investment Facilitation Policies in China’s Pilot Free Trade Zones Abstract Harnessing the catalytic role of opening-up in driving institutional reform is crucial for fostering a high-quality business environment. Focusing on the institutional learning behaviors of Chinese local governments, this study categorizes policy supply into pre-establishment and post-entry phases for enterprises. Based on the evolution of investment facilitation policies in Pilot Free Trade Zones (PFTZs)—transitioning from local innovation to pilot implementation and subsequent nationwide replication—this study utilizes policy texts to examine how expectations of foreign capital inflows influence the quantity, speed, and degree of innovation of local policy issuance. The findings indicate that: (1) Foreign capital inflow expectations serve as a vital catalyst for institutional learning. Specifically, a 1% increase in contracted foreign investment projects leads to a marginal increase of 0.132 in the number of investment facilitation policies issued. (2) Local governments engage in adaptive policy adjustments tailored to local socio-economic characteristics. A 1% increase in local contracted foreign investment projects extends the policy adoption period by 5.8% (approximately 5.7 months) while decreasing policy text similarity by 5.34%. (3) Institutional learning progresses through three distinct stages: In the autonomous learning stage, institutional learning exhibits "leapfrogging" traits, where larger economic disparities relative to other regions further incentivize policy issuance. In the induced learning stage, an increase in policies issued by neighboring cities prompts local governments to expand their own policy adoption. In the compulsory learning stage, local governments engage in policy competition with neighbors, resulting in significant policy differentiation. (4) Regions with higher levels of openness demonstrate stronger incentives for institutional innovation. Under the demonstration effect of PFTZs and the replication of institutional frameworks, these regions facilitate broader institutional diffusion, enhancing the business environment and openness in other areas. This fosters a virtuous cycle where opening-up drives reform, and reform further promotes opening-up. This study provides a theoretical framework and empirical evidence for the mechanism of reform-through-opening, offering critical policy implications for advancing a unified national market and optimizing the business environment.
By Siyi Pan; Fudan University    Suhua Tian; Fudan University
Presented by: Siyi Pan, Fudan University
4. Risk for Men, Discounts for Women: Gendered Advice and Pricing in Retail Brokerage Abstract We study how financial intermediaries jointly set portfolio risk and transaction prices for otherwise identical male and female retail investors. Using 10,752 in-person audit meetings at all securities brokerage branches in a Chinese city, we observe investment recommendations and negotiated commission discounts across two sequential meetings and contrasting market states. Advisors systematically steer women into safer portfolios: relative to comparable men, female clients are more likely to receive fully conservative bundles and, when equities are included, are advised to hold 15–25 percentage points less equity. Pricing moves in the opposite direction. Conditional on bundle composition, women receive commission discounts that are 5–10 percentage points larger, especially at return meetings and in bearish markets. Survey evidence suggests these patterns reflect belief-based statistical discrimination over retention risk rather than financial sophistication or bargaining behavior.
By SUMIT Agarwal; National University of Singapore    Kevin Lang; Boston University    Kaiwen Leong; Griffith University    Huailu Li; National University of Singapore    Zhanyu XU; Fudan University
Presented by: Huailu Li, National University of Singapore
Session 24: International I - International Finance July 29, 2026 8:30 to 10:00 Location: Malaysia Room (level 5)
Session Chair: Fred Seunghyun Maeng, Nanyang Technological University
Session type: invited
1. Uncertainty and volatility: A Markov-switching GARCH-MIDAS approach Abstract We propose a flexible specification that encompasses virtually all GARCH-MIDAS models proposed in the literature. Our specification accounts for asymmetry and regime-switches in the volatility dynamics. In the empirical application, we examine the relationship between S&P 500 returns volatility and macroeconomic uncertainty. We show that our model provides more accurate volatility forecasts than the nested GARCH-MIDAS models at forecast horizons of 1 day, 2 weeks, 1 month, 2 months and 3 months. Furthermore, our findings suggest that while high-frequency uncertainty indices are suitable for short-horizon forecasts, low-frequency uncertainty proxies provide better forecasts at longer horizons.
By Yao Rao; The University of Liverpool
Presented by: Yao Rao, The University of Liverpool
2. Higher moments pricing with heterogeneous investors in foreign exchange markets Abstract Using monthly exchange‐rate data for 37 countries from January 1985 to August 2024, we compare several asset pricing models for currency excess returns. We construct a four‐factor model including market, carry, momentum, and value factors, then extend it to five- and six-factor models by adding the output‐gap and inflation factors. Through time‐series and cross‐sectional asset‐pricing analyses, we assess each model's ability to explain currency excess returns. Empirical results show that the five‐factor specification effectively captures return variation and that the inclusion of the inflation factor enhances explanatory power. We further explore a higher moment model composed of market, realized volatility, and skewness factors, finding that it initially exhibits relatively low explanatory power and systematic pricing errors. After smoothing extreme observations, both goodness-of-fit and pricing-error measures improve significantly, highlighting extreme events’ impact on higher‐order moment pricing.
By Chien-Hsiu Lin; National Chengchi University, Taiwan
Presented by: Chien-Hsiu Lin, National Chengchi University, Taiwan
3. Default, Inflation Expectations, and the Currency Denomination of Sovereign Bonds Abstract This paper studies optimal debt management by currency in inflation-targeting emerging countries. First, I document new evidence that these countries tilt their borrowing towards foreign currency when sovereign risk rises. Second, I develop a New Keynesian model with sovereign default, and show how the currency denomination of debt is shaped by sovereign risk contingent on fiscal-monetary interactions in default crises, which involve optimal deviations from the inflation target. Local currency debt hedges consumption fluctuations, while foreign currency debt reduces governments’ incentive to raise (expected) inflation that generates distortions. Quantitatively, these tradeoffs capture the new evidence and explain up to 35 percentage points of the foreign currency debt share. Optimal debt management reduces inflation, default frequency, and spreads.
By Fred Seunghyun Maeng; Nanyang Technological University
Presented by: Fred Seunghyun Maeng, Nanyang Technological University
4. Product Quality and Export Responses to Exchange Rate Movements: Evidence from Taiwan Abstract This study investigates the relationship between Taiwan’s four-digit industry-level bilateral exports and exchange rate movements, with a particular focus on the role of export quality. Following Khandelwal et al. (2013), export quality is defined as the portion of a product’s market share in a destination that cannot be explained by its price. Quality measures are first estimated annually at the HS six-digit product level for each market and then aggregated to the four-digit industry level using the approach of Feenstra and Romalis (2014). The empirical results yield four main findings. First, an appreciation of the New Taiwan Dollar (NTD) relative to destination currencies reduces both export volumes and prices, although this effect is observed only for destinations outside China and Southeast Asia. Second, higher export quality mitigates the negative impact of currency appreciation on export volumes; however, this moderating effect does not extend to export prices, suggesting that exporters may adjust product composition in response to exchange rate fluctuations. Third, the role of quality is more pronounced in technologically sophisticated industries with longer product ladders, where higher quality more effectively offsets the adverse effects of currency appreciation on trade volumes. Fourth, the income level of destination countries matters: for advanced economies, higher quality weakens the negative relationship between exchange rates and export volumes, whereas this mitigating effect disappears in non-advanced destinations.
By Hao-Chung Li; National Chengchi University
Presented by: Hao-Chung Li, National Chengchi University
Session 25: Public I - Fiscal July 29, 2026 8:30 to 10:00 Location: Indonesia Room (level 5)
Session Chair: Donghyun Park, SEACEN
Session type:
1. Social Engagement through Public Investment: Impact of Education, Health, and Capital Spending on Economic Growth Abstract This study examines how public investment in human and physical capital contributes to Gross Domestic Product (GDP) growth, particularly focusing on social expenditure. While the literature finds mixed evidence, few studies simultaneously examine social and physical capital within a unified identification framework. The analysis uses an unbalanced panel of 158 countries from 1980 to 2024. A two-way fixed-effects model is first employed to estimate within-country relationships between public expenditure and GDP growth while controlling for unobserved heterogeneity and global shocks. To address endogeneity arising from reverse causality, simultaneity, and dynamic persistence, the study further applies the System GMM estimator, which relies on lagged internal instruments to strengthen causal identification.The fixed-effects results reveal strong and statistically significant positive associations between GDP growth and public expenditure on education, health, capital formation, and employment. Social expenditure—particularly health spending—shows robust contemporaneous effects. However, the System GMM estimates indicate that education and health spending lose statistical significance once endogeneity is addressed, while capital formation and employment remain consistently significant. These contrasting results suggest that social spending may influence growth primarily through spending quality and institutional effectiveness rather than expenditure levels alone.By integrating fixed-effects and System GMM approaches within a unified framework, this study provides one of the most comprehensive global assessments of how human- and physical-capital investment contribute to long-term growth. The findings highlight the importance of improving the efficiency and governance of social expenditure, particularly in developing economies where growth payoffs depend heavily on institutional capacity.
By Warattaya Chinnakum; Faculty of Economics, Chiang Mai University
Presented by: Warattaya Chinnakum, Faculty of Economics, Chiang Mai University
2. The Bystander Effect and Social Norm in Security Public Goods: Theory and Empirics Abstract Many witnesses saw or heard the attack, but none of them called the police or came to her/him aid. Such a incident previously prompted inquiries into what became known as the “bystander effect” or "Genovese syndrome". Thus, though police station exists, nobody informs the incident to police. Everybody just simply looks it around the incident. That is, nobody provides security public goods. All are likely free riders for security public goods. The security public goods involve danger, such as in rescuing, fighting robbery, drugs, murder, terrorism, etc. Standard public goods: donations to charity, hospitals, and education. The purpose of this paper is to examine the "bystander effect" and the “social norm” suppressing it in the context of public security, where private public goods such as reporting and public goods such as police are provided. We develop a "security public goods" model to explore what (social norm, police, income, brutality of the incident) and how suppress the bystander effect. We also conduct the empirical analysis based on a "security public goods" model.
By Tatsuyoshi Miyakoshi; Gifu Shotoku-gakuen University
Presented by: Tatsuyoshi Miyakoshi, Gifu Shotoku-gakuen University
3. Fiscal Policy at the Effective Lower Bound Abstract This paper explores how a temporary consumption subsidy affects the economy and public welfare when interest rates are stuck at the effective lower bound (ELB). Using a New Keynesian model that accounts for situations when the lower bound is binding, and solved with the OccBin method, the analysis focuses on when the policy is put in place, measuring its impact as it happens rather than at the start of a downturn. The findings suggest that consumption subsidies can boost output and inflation much more during an ELB episode than in a model that ignores the lower bound. Evaluating welfare with a standard quadratic loss function, the study finds that acting quickly with fiscal policy may result in significant welfare improvements. Overall, the results highlight the importance of considering real-world constraints and the timing of policies for understanding fiscal intervention during economic slowdowns.
By Pakpicha Pathompituknukoon; Kasetsart University    Panupong Sukkerd; Kasetsart University
Presented by: Pakpicha Pathompituknukoon, Kasetsart University
4. Global fragmentation, fiscal policy, and economic growth: a cross-country analysis Abstract This paper studies the macroeconomic implications of geopolitical risks and the role of fiscal sustainability in mitigating them. Our empirical analysis exploits a comprehensive database covering 121 countries from 1985 to 2023. We find that, in countries without fiscal rules, geopolitical fragmentation leads to a persistent decline in output and a surge in the debt-to-GDP ratio. However, in countries with fiscal rules, both output and debt are stabilized in the medium- to long-run. Moreover, fiscal rules have a more pronounced effect in countries with high central bank independence, suggesting a novel monetary-fiscal complementarity. We further explore various dimensions of cross-country heterogeneity, including economic development, political institutions, and climate risks. Finally, fiscal rules promote inclusive growth by mitigating adverse distributional effects of geopolitical risks.
By Gazi Salah Uddin; Linköping University Sweden and Norwegian University of Life Sciences, Norway     Anh H. Le; Goethe University Frankfurt    Naoki Yago; University of Reading    John Beirne; Asian Development Bank    Donghyun Park; SEACEN
Presented by: Donghyun Park, SEACEN
Session 26: Standard of Living, Well-being, Altruism and Happiness July 29, 2026 8:30 to 10:00 Location: Brunei Room (level 5)
Session Chair: M Kabir Hassan, University of New Orleans
Session type: invited
1. Feeding Health Early: The Child Health Impact of Free Nutrition Package Program Abstract Early-life undernutrition remains a major constraint on child health and human capital formation. Yet causal evidence on whether large-scale infant and young child nutrition interventions in developing countries generate lasting benefits is still limited. This paper exploits the staggered rollout of China’s Free Nutrition Package Distribution (FNPD) Program as a quasi-natural experiment and combines it with data from the China Family Panel Studies (CFPS) to examine the medium- and long-term effects of early-life nutritional intervention on child development using a cohort difference-in-differences approach. The results shows that early-life exposure to the FNPD program significantly improves child health outcomes, as reflected in higher height-for-age z-scores and weight-for-age z-scores, as well as lower probabilities of hospitalization and reduced hospitalization expenditures. Mechanism analysis suggests that these effects are driven not only by direct nutritional supplementation, but also by subsequent adjustments in household health-related behaviors: the program improves household dietary diversity and reduces the likelihood of parental smoking and drinking. Further analysis reveals that the effects are more pronounced for girls and for children from less-educated families. Beyond health outcomes, the FNPD program also significantly improves children’s cognitive-related outcomes, as evidenced by better Chinese and Maths performance. In addition, the program generates positive spillover effects on older siblings within the household, improving their health outcomes and Chinese language performance. Overall, the findings suggest that public nutritional interventions in early life yield substantial and persistent health returns, promote children’s human capital accumulation, and help reduce developmental inequality to some extent.
By Yihan Wu
Presented by: Yihan Wu,
2. Macro Consequences of Diet Quality and Health Abstract Healthcare spending constituted the largest share (27\%) of the federal budget amounting to $1.7 Trillion, rising annually at the unsustainable rate of 7.5%, and 90% of this spending has been used to treat chronic diseases. Chronic diseases burden 60-70% of the population with the prevalence expected to increase. I establish three key empirical results: better diets are correlated with less chronic diseases, better diets are costlier, chronic diseases impact earnings. At first, including these results as features into a simplified two-period model, I identify a structural wedge between private and social optimal choices of diet quality. Households under-invest in diet quality because they do not internalize the fiscal externalities of public health costs and lost tax revenue, and are budget constrained. I then evaluate three policy designs related to food subsidies: item-specific restrictions, price incentives, and in-kind transfers. I demonstrate analytically that restrictions and price subsidies are largely ineffective due to the fungibility of subsidies for infra-marginal recipients and the price inelasticity of diet quality respectively. In-kind transfers of high quality diets as in the recent "Food-Is-Medicine" movement correct for the externalities as it directly results in socially optimal diets. Next, I expand the simplified model into a full general equilibrium Aiyagari model with heterogeneity in assets, productivity, and health, calibrated to US data. I find that replacing existing benefits with high quality food bundles improve population health by 7-20% and medical spending by 1.6-4.4% of GDP, with productivity improving by 0.5-3.2%. Targeting the policy at income thresholds is better for aggregate welfare and generates a pareto improvement between the rich and the poor. On the other hand, targeting the policy by health status is better for GDP, productivity, and health but is highly distributive. Finally, the policy is fiscally responsible across the different target thresholds.
By Jonas Ho; University of California - Irvine
Presented by: Jonas Ho, University of California - Irvine
3. Economic Shocks, Household Adjustment, and the Stability of Life Satisfaction Abstract Large economic shocks are commonly associated with declines in subjective well-being, yet evidence from recent crises suggests that average life satisfaction can remain surprisingly stable. This paper investigates why substantial economic disruption does not always translate into proportional welfare losses. Using panel data from the Slovak Household Finance and Consumption Survey (2017–2021) merged with regional variation in shock severity, we combine a fixed-effects difference-in-differences approach with mediation analysis to distinguish between economic exposure and transmission mechanisms. The difference-in-differences results show no significant average decline in life satisfaction despite pronounced economic adjustment. However, the impact of shock severity is strongly distributional: households at the upper end of the pre-shock income and consumption distribution experience larger income and spending reductions. When contemporaneous economic variables are introduced, income changes remain positively associated with life satisfaction, while consumption and wealth display weaker direct effects. The mediation analysis reveals that although shock severity significantly altered income and discretionary consumption patterns, these changes translated only weakly into well-being outcomes. Crucially, saving behavior plays an important buffering role. Higher-income households reduced saving substantially more than lower-income households, suggesting that income shocks were absorbed primarily through saving decumulation rather than through sharp reductions in consumption. This consumption-smoothing response limited the transmission of economic disruption into subjective welfare. Consistent with this mechanism, bootstrapped indirect effects are statistically insignificant across mediators and baseline quintiles. Taken together, the findings suggest that resilience during large shocks arises not from the absence of economic change but from household adjustment mechanisms that weaken the propagation of shocks into lived experience. By distinguishing between exposure and transmission, the paper contributes to a broader understanding of how macroeconomic disturbances affect well-being. The results underscore the importance of income stabilization policies and household financial flexibility in mitigating the welfare consequences of economic crises. JEL Code: D91, I31, D12, C23, E32 Keywords: Subjective well-being; Economic shocks; Household behavior; Distributional effects; Panel data; Mediation analysis
By Biswajit Banerjee; National Bank of Slovakia and Ashoka University, India    Peter Toth; National Bank of Slovakia
Presented by: Biswajit Banerjee, National Bank of Slovakia and Ashoka University, India
4. The Dual Mandate: A Quality-Based View on Climate 1 Exposure and Shariah-Compliant Investing Abstract This paper examines the financial performance of investment strategies that combine two major ethical investment mandates: Shariah-compliant investing and climate-sensitive portfolio construction. Using U.S. equity data from 2010 to 2025, the study integrates firm-level Shariah compliance ratings with climate exposure measures to construct dual-screened portfolios and compare their performance with matched conventional counterparts. Employing Fama-French factor models, long-short portfolio strategies, event-study analysis, and firm-level regressions, the paper documents a nuanced interaction between Islamic finance principles and climate risk pricing. The findings reveal a significant Shariah quality premium, concentrated primarily among the highest-quality A-rated compliant firms, which generate persistent risk-adjusted abnormal returns, especially under normal market conditions. The results also suggest that even lower-rated compliant firms benefit from leverage constraints embedded in Shariah screening, creating a quality floor that limits downside risk. At the same time, the study finds a persistent climate risk premium within the Shariah-compliant universe, where high-climate-risk firms outperform low-climate-risk firms. These findings show that the dual mandate does not produce a simple ethical-financial synergy; rather, it creates a meaningful trade-off between climate risk mitigation and return enhancement. The paper contributes to Islamic finance, ESG investing, and asset pricing literature by showing that Shariah screening functions as a governance and quality filter, while climate exposure remains a distinct priced risk factor.
By M Kabir Hassan; University of New Orleans
Presented by: M Kabir Hassan, University of New Orleans
Session 27: Technology and Innovation I July 29, 2026 8:30 to 10:00 Location: Philippines Room (level 5)
Session Chair: Naoyuki Yoshino, Keio University
Session type: invited
1. Research on the Impact of Artificial Intelligence Technology Innovation on Green Development Abstract Abstract: In the process of industrialization, balancing economic growth with environmental protection is a major challenge for developing countries. The forecasting and optimization capabilities of artificial intelligence (AI) offer a new perspective to resolve this dilemma. Based on panel data from 282 Chinese cities between 2007 and 2022, this paper constructs a comprehensive evaluation index for urban AI technology innovation using the entropy method, calculates urban green development efficiency using the super-efficiency SBM model, and empirically examines the impact of AI technology innovation on green development and its underlying mechanisms. The findings are as follows: (1) AI technology innovation significantly promotes green development efficiency. After adding control variables and controlling for city and year fixed effects, a one-unit increase in the level of AI technology innovation increases green development efficiency by approximately 0.8704 units. This conclusion remains robust after introducing instrumental variables to address endogeneity issues and conducting a series of robustness checks, including introducing lagged variables and winsorization. (2) Mechanism analysis reveals that AI technology innovation promotes green development primarily through three pathways: enhancing automation of goods production, driving automation of ideas production, and reducing pollutant emissions. The conclusions of this study provide empirical support for incorporating AI into green development strategies and leveraging AI technology innovation to empower environmental governance. Keywords: Artificial Intelligence; Green Development; Green Total Factor Productivity; Automation of Goods Production; Automation of Ideas Production; Pollutant Emission Reduction JEL Codes: Q55, O33, O44
By Ruiheng Liu; Southeast University    Zhengning Pu; Southeast University
Presented by: Ruiheng Liu, Southeast University
2. Government Venture Capital and Digital Technology Innovation: Comparing the Roles of the State and the Market Abstract Digital technology innovation is characterized by high capital intensity and long cycles, urgently requiring support from patient capital capable of overcoming intertemporal maturity mismatches. Based on matched data of Chinese government venture capital events and critical digital technology patents from 2008 to 2022, this paper empirically examines the impact of government venture capital, as a form of institutionalized patient capital, on digital technology innovation. The study finds that government venture capital significantly enhances the output of critical digital technology patents. Mechanism analysis indicates that government venture capital primarily alleviates financing constraints through a signaling mechanism and provides knowledge spillovers by promoting high-tech industrial agglomeration and industry-university-research collaboration. However, there exists a deviation between theory and practice: constrained by the rigid requirements for the preservation and appreciation of state-owned assets, government venture capital fails to fulfill the theoretically expected risk-taking function in practice, instead exhibiting risk-averse tendencies. Further analysis reveals that reducing local reinvestment requirements, a form of institutional friction, significantly strengthens the innovation-driving effect of government venture capita, reflecting a dynamic balance between a competent government and an efficient market. Furthermore, government venture capital primarily improves the impact depth rather than the knowledge breadth of digital patents, with significant effects in industries such as semiconductors and information technology. This paper reveals the role of the government in promoting venture capital and digital technology innovation within the Chinese context, providing empirical evidence for building a financial system compatible with technological innovation.
By Yu Qian; Southeast University    Zhengning Pu; Southeast University
Presented by: Yu Qian, Southeast University
3. Technological Complementarity, Spatial Resource Misallocation, and the Economic Value of Innovation: On the Potential Gains from Optimal Matching Abstract Against the backdrop of innovation-driven development shifting from quantity expansion to quality improvement, this paper examines how the matching efficiency between firms’ technological advantages and urban technological structures affects the economic value of innovation from the perspective of spatial resource misallocation. Based on matched data on Chinese A-share listed firms and city-level patents from 2004 to 2024, this paper constructs a firm-city-year measure of technological complementarity and uses capital market reactions during the patent grant window to measure the economic value of innovation. The results show that technological complementarity significantly enhances the economic value of innovation, indicating that a higher degree of matching between firms’ technological advantages and urban technological structures is conducive to generating higher economic returns from innovation outcomes. Mechanism tests show that technological complementarity mainly works through three channels: strengthening local knowledge network embeddedness, improving firms’ innovation capabilities, and reinforcing the pull of government procurement. Heterogeneity analysis further shows that the above effects are more significant in high-tech industries, central cities, and regions with high transportation accessibility. Further counterfactual estimation suggests that actual resource allocation still systematically deviates from the attainable frontier of technological matching, implying considerable room for value gains through better matching between firms and cities. If spatial frictions are reduced and the matching relationship between firms and cities is optimized, the economic value of innovation could still increase by about 5.19% to 5.36%, corresponding to a potential aggregate increment of about RMB 2.55 trillion to RMB 2.65 trillion. This paper provides micro-level evidence for understanding the spatial misallocation of innovation resources and the potential gains from optimized matching.
By Li Zijun; China Southeast University
Presented by: Li Zijun, China Southeast University
4. Has the Declining Birth Rate Narrowed the Skill Premium? - Evidence from China Abstract Despite growing concerns over China's persistently declining birth rate and its profound socioeconomic implications, research has yet to sufficiently examine its impact on the skill premium. This study explores the impact of the urban birth rate on the skill premium using data from the 2013 and 2018 China Household Income Project (CHIP) and the China City Statistical Yearbook. We find that a decline in the urban birth rate is expected to narrow the skill premium. Innovation suppression and the rising cost of living serve as key mechanisms through which the declining birth rate influences skill premium. Specifically, a lower birth rate dampens urban innovation, which helps reduce the substitution of low-skilled labor and increase their relative demand, thereby narrowing the skill premium. In addition, a lower birth rate depresses housing prices, which facilitates the inflow of high-skilled labor into cities and expands their relative supply, further compressing the skill premium. Heterogeneity analysis reveals that the narrowing effect of the declining birth rate on the skill premium is more pronounced in western regions, non-public sectors, and younger cohorts. Overall, this study not only contributes to the understanding of the economic consequences of demographic transitions, but also enriches the literature on the determinants of skill premium. Keywords: Birth Rate; Skill Premium; Innovation Suppression; Living Cost JEL: J13; J31; R23
By Chengwei Ma; Southeast University    Xin Gu; Southeast University
Presented by: Chengwei Ma, Southeast University
Session 28: (Plenary) Distinguished Albert Winsemius Lecture: Dale Whittington July 29, 2026 10:30 to 11:50 Location: Ballroom 1 (level 3)
Session Chair: Euston Quah, Nanyang Technological University
Session type: plenary
1. Designing a national benefit–cost analysis system Abstract A government can establish a ‘national benefit–cost analysis (BCA) system’ by (1) mandating through either executive or legislative action that BCA be conducted for some designated set of public investments and regulations and (2) creating an institutional structure to support this legal or administrative requirement for the regular, ongoing evaluation of the benefits and costs of new proposed investments and regulations. This paper describes 12 issues that should be considered in the design and establishment of a national BCA analysis system and 4 approaches for combining these 12 design decisions to craft a strategy for establishing a national BCA system. The literature suggests that the results of ‘standalone’ BCAs are not highly valued or used by decision-makers. This is in part because the quality of BCAs is often poor due to a lack of qualified analysts to conduct BCAs, analysts’ overly optimistic estimates of benefits and underestimates of costs, and analysts’ strategic misrepresentation of results. This paper suggests that a well-designed national BCA system—assisted by generative AI—may be able to overcome some of the problems associated with ‘standalone’ BCAs.
By Dale Whittington; University of North Carolina
Presented by: Dale Whittington, University of North Carolina
Session 29: MTI Plenary: Green economy, Sustainability, Environment and Climate Change Issues July 29, 2026 13:00 to 14:20 Location: Ballroom 1 (level 3)
The Ministry of Trade and Industry (MTI) is Singapore’s main economic agency. Its mission is to drive productivity-led growth, safeguard and expand Singapore’s economic space, and build a future-ready economy where firms thrive, so as to create good jobs and opportunities for Singaporeans. Headquartered in MTI, the Economist Service (ES) is a professional scheme for economists in the Singapore public sector. The ES is dedicated to shaping public policy through sound economic thinking and rigorous policy-oriented economic research. Its economists serve in many agencies across the public sector and work on issues across a wide range of policy domains such as economic, social, infrastructure and the environment. This year marks the 25th Anniversary of the ES.
Session Chair: Dale Whittington, University of North Carolina
Session type: panel
Discussants:      Robert Stavins, Harvard University      Jinhua Zhao, Cornell University      Renate Schubert, ETH Zurich      Naoyuki Yoshino, Keio University      SUMIT Agarwal, National University of Singapore
Session 30: MAS Plenary: Changing Global Monetary Landscape July 29, 2026 14:30 to 15:40 Location: Ballroom 1 (level 3)
Session Chair: Jun Yang, Nanyang Technological University
Session type: invited
Discussants:      Ahmet Aysan, Hamad Bin Khalifa University      James Forder, Balliol College Oxford      Barry Eichengreen, UC Berkeley
Session 31: Plenary: Momentum of the Chinese Economy (China Changing or Changing Global) July 29, 2026 16:10 to 17:20 Location: Ballroom 1 (level 3)
Session Chair: Qu Feng, Nanyang Technological University, Singapore
Session type: invited
Discussants:      Justin Yifu Lin, Peking University      Jun Zhang, Fudan University      Wing Thye Woo, University of California, Davis
Session 32: Asian II July 29, 2026 17:30 to 19:00 Location: Cambodia Room (level 5)
Session Chair: Zheng Fang, Singapore University of Social Sciences
Session type: invited
1. Effects of industrial policy devices for capital investment: Lessons from Japan’s cases Abstract Governments sometimes adopt policies to promote industrial activities for various purposes, such as to enhance economic growth, which was widely seen in the last half of the 20th century. Recently, the purpose of such interventions has broadened in scope, from green transition, supply chain resilience, and the challenges of good jobs to geopolitical competition. Juhász et al. (2024) explain this situation as “industrial policy has indeed retuned and is on the rise.” Because of the miraculously rapid growth, East Asian cases are a focal point of the literature, and the role of policy in this high growth is still controversial. Recent studies consider policy details when conducting empirical examinations and offer a more nuanced understanding of the effects of industrial policy, in contrast to the mixed conclusions of earlier studies, some of which are skeptical about the effects of industrial policy on economic growth (Juhász et al. 2024). In practice, industrial policies comprise various policy tools together rather than a single representative industrial policy, and institutions and tools involved vary across countries and periods. Researchers cannot easily specify which government actions constitute industrial policy except in cases where industrial policies are implemented in a systematic way. In the post-war period, Japan implemented economic policies in a systematic manner, aiming at achieving economic growth by promoting capital investment in the private sector. To encourage capital investment, the Japanese government employed various policy tools, including direct controls on investment, controlling banking activities, and public lending to various tax incentives. Although the effectiveness of these policies is controversial, the recent trend of drawing on microlevel data has allowed us to reconsider the effects of past industrial policies. This study examines the effects of major industrial policy tools to encourage capital investment during the high-growth era in Japan based on a newly constructed firm-level database. The database covers relatively large firms that led capital investment and thus, the economic growth of Japan, from the 1950s to the 1970s. Various accelerated depreciation schemes known as “special depreciation” were an important policy tool that targeted a broad range of manufacturing sectors. Hatase and Matsubayashi (mimeo) calculate the impact of various policy tools on the user cost of capital during the high-growth period of Japan and find that special depreciation played a considerable role as well as reductions in corporate tax rates, whereas nontaxable allowances and reserves played only a minor role. For the studied samples, the average gap between the user cost of capital with and without tax incentives was 1.5 percentage points, of which 0.9 percentage point was attributable to special depreciation. To examine whether policies encouraging capital investment were successful, analyzing the effects of the complete policy package is essential. This study gauges the effects of the various industrial policy tools adopted by the Japanese government for capital investment. In addition, to evaluate the effects of economic policies for growth, the relationship between policy adoption and corporate sales growth is examined. We consider two possible channels through which policy devices affect capital investment: first, a reduction in the user cost of capital and second, easing liquidity constraints. Traditionally, tax incentives have been considered to reduce user costs of capital and thus, accelerate capital investment. Major policy devices, including special depreciation, improve cash availability for firms and can boost capital investment by easing liquidity constraints. We estimate an accelerator-type investment equation covering the tax device variables and liquidity constraint terms with a sample period between 1956 and 1972. We then examine whether firms that obtained cheaper funding for investment through policy tools contributed to achieving the intended policy goals and enhancing growth. Empirical evidence shows that such policy devices promote capital investment by reducing the user cost of capital and easing firms’ liquidity constraints. The results of the empirical tests of the relationship between the application of policy devices and sales growth of each firm indicate increased sales, suggesting the probability of the achievement of final policy goals, thus promoting growth, to some extent. (References) Hatase, Mariko and Yoichi Matsubayashi (mimeo), “Interest rates, prices, tax incentives and user cost of capital: Experiences of Japanese firms in the high- growth era.” Juhász, Réka, Nathan Lane, and Dani Rodrik (2024), “The New Economics of Industrial Policy,” Annual Review of Economics Vol.16, pp.213–42.
By Mariko Hatase; Hitostsubashi University    Yoichi Matsubayashi; Kobe University
Presented by: Mariko Hatase, Hitostsubashi University
2. Expressway Privatization Neutrality in Japanese Municipal Manufacturing Abstract This study investigates how the 2005 privatization of Japan’s expressways affected manufacturing at the municipal level by employing a multi-period difference-in-differences event-study methodology. By incorporating demand-side perspectives on privatized expressways, it extends earlier analyses (Kaino & Hidaka, 2024, 2025; Mizutani & Uranishi, 2008). Using Japan’s extensive reliance on road freight, we proxy municipalities’ exposure to privatization via their access to expressway junctions. These proximity-based treatment measures are expected to capture privatization-induced changes in manufacturing activity. The empirical results indicate privatization neutrality for manufacturing. Increases in manufacturing costs and shipment values are of comparable magnitude, implying offsetting effects, as reflected in the absence of statistically significant post-privatization changes in gross value added. Consequently, concerns regarding widespread adverse spillovers appear overstated. The reform’s configuration and the limited substitutability of expressways in freight transport resulted in the privatization-neutrality by satisfying the conditions outlined by theoretical frameworks such as Matsumura & Okumura (2013) and Kawasaki (2023).
By Youjin Oh; Institute of Science Tokyo
Presented by: Youjin Oh, Institute of Science Tokyo
3. The impact of multi-dimensional Regional Cooperation Initiatives (RCI) on Inclusive Development : Implications for the Asia-Pacific economies Abstract Regional cooperation initiatives (RCI) encompass multiple agendas including trade and investment, infrastructure connectivity, institutional arrangements, movement of people, regional value chains, environmental cooperation, and cross-border digital integration. This paper contributes to the empirical literature on deeper RCI by examining the Asia and Pacific Regional Cooperation and Integration Index (ARCII) and assessing the effects of multidimensional RCI on job creation and income inequality. Job creation is measured using the employment-to-population ratio, while income inequality is captured by the Gini index at the country level. Using annual data from 2006 to 2023 for 173 economies across six subregions, the study evaluates the multidimensional impacts of RCIs on labor market and distributional outcomes, utilizing a panel data framework incorporating fixed effects, controlling for potential endogeneity. The analysis further distinguishes between intra-regional and interregional RCIs and focuses on four ARCII dimensions with sufficient data coverage—trade, infrastructure, institutions, and human mobility to ensure empirically robust results. Both intra- and interregionally, the empirical evidence confirms that RCI improves job creation in Asia and the Pacific, and that dimension of infrastructure drives it intra-regionally. Empirical evidence of RCI on inequality in Asia and the Pacific is more nuanced, with only the institutional dimension decreasing it significantly, interregionally. The findings provide evidence-based insights to inform the design and prioritization of RCI-related policies in Asia and the Pacific, focusing on infrastructure connectivity and institutional RCI initiatives to facilitate inclusive development.
By Sanchita Basu Das; Asian Development Bank    Rahul Sen; Auckland University of Technology Business School
Presented by: Rahul Sen, Auckland University of Technology Business School
4. ESG performance and labor cost stickiness: Evidence from China Abstract Using data from Chinese publicly listed firms between 2010 and 2022, this study examines the relationship between ESG performance and labor cost stickiness, as well as the mechanism underlying this relationship – whether through stakeholder protection or agency conflicts channels, a debate that remains unresolved in the literature. Our findings demonstrate that ESG performance exhibits a positive relationship with labor cost stickiness, and this relationship is primarily driven by stakeholder protection rather than managerial self-interest. The effect is particularly pronounced among firms operating under conditions of high environmental uncertainty, strong industry competition, or during growth stages. Moreover, ESG performance contributes to employee retention stickiness rather than wage stickiness. Collectively, these findings support the interpretation of ESG as an implicit labor protection mechanism, especially in contexts with weaker formal institutional safeguards.
By Zheng Fang; Singapore University of Social Sciences
Presented by: Zheng Fang, Singapore University of Social Sciences
Session 33: Behavioral II July 29, 2026 17:30 to 19:00 Location: Singapore Room (level 5)
Session Chair: Eugene Or, Singapore University of Social Sciences
Session type: invited
1. Perceived Financial Wellbeing of Households and the Role of National Culture: A Cross-Country Analysis Abstract An individual or a household's financial well-being happens when they are able to take care of their expenses and feel financially secure in the present and in the future (Salignac et al., 2020). National culture, a societal-level construct, is found to be associated with the range of financial behavior that could influence the financial well-being of a household, such as savings, borrowings, insurance, and investments, to name a few (Ahunov & Van Hove, 2020; Bialowolski et al., 2023; Kwok & Tadesse, 2006; Peterson et al., 2015). However, the relationship between a household’s financial well-being and the national culture still remains underexamined in the extant literature. The extant literature (Netemeyer et al., 2018; Salignac et al., 2020) has considered financial resilience, i.e., the ability to come up with money in case of unexpected expenses, and financial worry, i.e., the feeling of limited worry in financial matters, as two of the key aspects of an individual's financial well-being. The current study explores the role of national culture in explaining the cross-country heterogeneity in the perceived financial well-being of households by examining the association of national culture with the above-mentioned two aspects of financial well-being, i.e., perceived financial resilience and perceived financial worry of households. For this purpose, this study utilizes a nationally representative sample from the World Bank's Global Findex 2021 database (Demirgüç-Kunt et al., 2022), and the dimensions of national culture proposed by Hofstede (2010). The Global Findex 2021 database has measured the financial resilience of households in terms of a unidimensional indicator, which measures the perceived ability of respondents to come up with money equivalent to 1/20th of the GNI within the next thirty days. Further, the Global Findex 2021 database has also measured the perceived financial worry of respondents for matters such as unexpected medical expenses, monthly bills and expenses, and old age. Empirically, this study has deployed a multilevel regression model to examine the role of national culture in explaining the cross-country heterogeneity for the two distinct aspects of perceived financial well-being of households, i.e., perceived financial resilience and perceived financial worry. Further, the study has also employed the series of robustness checks, which include: a) the inclusion of macroeconomic or country-level factors that could have an influence on the perceived financial well-being of respondents, b) gender, education, and income-based sub-samples, and c) regression estimates based on Bayesian statistics. Our results indicate that there are indeed cross-country differences in both of these factors, viz., perceived financial resilience and perceived financial worry, that are associated with national culture. In particular, we observed a significant positive association of perceived financial resilience with individualism and long-term orientation. In the case of perceived financial worry, the association was significantly positive for power distance and masculinity, while it was negative for individualism and long-term orientation. The findings of this study provide insights into the possible impact of national culture on the financial well-being of households that may inform policy interventions. Countries that are high in Individualism may employ more laissez-faire policies while creating a support net for the extremely vulnerable households. In more collectivistic cultures, social norms and community leaders may be needed to guide the behavior of individual households. In case of low long-term orientation and high masculinity, interventions to promote a prudent financial attitude are likely to be helpful. In countries with high power distance, more democratic and transparent financial rules may reduce financial worry. To the best of our awareness, ours is among the first studies to observe such an association between perceived financial well-being and the dimensions of national culture, and the implications are new. However, there are a few limitations as well with our study, such as: a) subjectivity bias leading to over- or underestimation of dependent variables; b) non-inclusion of personal and behavioral factors, such as personality, money attitude, financial knowledge and capability, etc., as the Global Findex 2021 database didn’t measure the same; and c) ours are not causal estimates.
By Rahul Verma; Indian Institute of Technology Kanpur    Devlina Chatterjee; Indian Institute of Technology Kanpur
Presented by: Rahul Verma, Indian Institute of Technology Kanpur
2. Crisis, Compassion, and Capital: The Economics of Global Charitable Giving Abstract Do major crises create new charitable capital, or do they primarily reallocate donor attention? We study this question using the universe of nearly 50,000 projects across 201 countries on GlobalGiving between 2003 and 2025. Exploiting the Russo-Ukrainian war as an exogenous shock to global humanitarian attention, we show that funding to Ukraine-related projects increased dramatically following the war, while funding to non-Ukraine projects declined. The response operates primarily through donor participation rather than donation size, indicating that crises reshape who gives as much as they reshape how much people give. The evidence further suggests that crises generate both new charitable resources and crowd-out of less salient causes, rather than representing either pure additionality or pure substitution. We also develop and test a framework showing that crises reshape charitable giving through both donor preference shifts and narrative competition. The dominant effect is a broad shift toward disaster-response and identifiable-beneficiary appeals, while crowding-out is concentrated in a limited set of narrative frames heavily associated with the crisis. Finally, we document substantial geographic disparities in charitable funding and show that crisis-driven attention amplifies these inequalities, widening funding gaps across regions. Taken together, our findings suggest that charitable giving operates in an attention-constrained market where major crises reshape both the level and distribution of philanthropic capital.
By Naman Agrawal; National University of Singapore
Presented by: Naman Agrawal, National University of Singapore
3. Ethnic Disparities in Sentencing: Evidence from First-Time Drink-Driving Offenders in New Zealand Abstract This paper examines ethnic disparities in court sentencing using administrative data on first-time drink-driving offenders in Aotearoa New Zealand. Leveraging objective measures of offence severity from recorded alcohol levels and rich linked socio-demographic data, we provide a clean test of differential treatment. Māori offenders are 2.5 percentage points more likely to receive sentences exceeding a monetary fine than comparable New Zealand Europeans. Disparities are larger among female offenders, vary across courts, and decline over time, disappearing in recent years. The findings highlight how disparities in lower-level, high-volume offences can arise within structured sentencing frameworks and inform policy debates on proportionality and criminal record consequences.
By Serene Chua; New Zealand Policy Research Institute    Kabir Dasgupta; Federal Reserve Board    Alexander Plum; Auckland University of Technology
Presented by: Serene Chua, New Zealand Policy Research Institute
4. Lifetime Costs of Drug Abusers in Singapore Abstract This study quantifies income losses attributable to drug abuse and incarceration using a fixed-effects regression framework. First-time abusers experience a 2.42% annual wage growth which is lower than the 3.5% national benchmark for comparable non-abusers. Annual wage growth slows to only 2.35% for second-time abusers. Chronic abusers with three or more-time arrests experience near-stagnant wage trajectories with an annual growth rate of 1.28%. By retirement age of 63, cumulative income losses are S$598,306 for first-time abusers, S$1.05 million for two-time abusers, and more than S$1.25 million for chronic abusers with three or more-time arrests. In additional to wage losses, drug abusers also incur substantial out-of-pocket expenditures on drugs and imposes considerable emotional costs on family members. Together with the income losses, the unit value per drug offence ranges from S$666,900 to S$1.7 million, depending on the abuser’s profile.
By Euston Quah; Nanyang Technological University    Eugene Or; Singapore University of Social Sciences    Jun Rui TAN; Nanyang Technological University    Tsiat Siong Tan; Singapore University of Social Sciences    Wai Mun Chia; Nanyang Technological University
Presented by: Eugene Or, Singapore University of Social Sciences
Session 34: Development II July 29, 2026 17:30 to 19:00 Location: Thailand Room (level 5)
Session Chair: Jinhua Zhao, Cornell University
Session type: invited
1. Productivity differences and the relative price of capital in a two-sector growth model Abstract This paper investigates the conditions for balanced growth with falling investment-goods prices based on a two-sector neoclassical growth model. Some research analyzes the conditions for the falling investment-goods prices on the balanced growth path in a one-sector model. However, in a one-sector framework, one can usually treat with the general price level, but not with investment goods prices. To deal with falling investment goods prices, a two-sector framework is a more natural setting. We develop a two-sector neoclassical growth model with heterogenous factor-augmenting technical changes in the investments-goods and consumption-goods sectors to analyze what types of conditions are required to satisfy the falling investment prices on the balanced growth path. We then empirically investigate the validity of these balanced growth conditions using the time series data from 1994 to 2021 in the United States and Japan. Our theoretical analysis has two main results. First, investment goods prices on the balanced growth path can decline when the labor-augmenting technical progress in the investment-goods sector is larger than that in the consumption-goods sector. This implies that the difference in labor productivity growth in each sector makes the changes of investment goods prices. Second, a capital dis-augmenting technical change in the consumption-goods sector, implying a capital-output ratio increasing in this sector, can make the falling investment goods prices. Finally, our empirical analysis based on IO tables in Japan and the United States shows that the differences of both labor productivity and capital productivity in those two sectors are almost consistent with our theoretical results.
By Hideyuki Adachi; Kobe University    Tamotsu Nakamura; Kobe University    Yasuyuki Osumi; University of Hyogo    Atsushi Miyake; Kobe Gakuin University
Presented by: Yasuyuki Osumi, University of Hyogo
2. The Multidimensional Poverty Reduction Effects of Digital and Traditional Financial Inclusion: Evidence from Indian Households Abstract Abstract This study aims to investigate the heterogeneous impact of traditional and digital financial inclusion on households’ multidimensional poverty in India, using the NABARD All India Rural Financial Inclusion Survey dataset. In doing so, the households’ multidimensional poverty deprivation index is constructed. Additionally, the traditional and digital financial inclusion scores of households are computed. For empirical investigation, ordinary least squares (OLS) is used to examine the impact of financial inclusion on household multidimensional poverty. However, a simultaneous quantile regression model (SQR) is applied to examine whether the impacts of financial inclusion on multidimensional poverty are uniform or vary across different households’ multidimensional deprivation quintiles. To ensure robustness of the result, the study used Propensity score matching (PSM) to address the selection bias endogeneity problem, also conducted sensitivity analysis to check the consistency of the results after altering the financial inclusion cutoff. Afterwards, conducted dominance analysis to determine the relative importance of financial inclusion indices and financial inclusion indicators individually in reducing poverty. The findings reveal that financial inclusion significantly contributes to the reduction of household multidimensional poverty, while DFI plays a disproportionately greater role in alleviating poverty than OFI and TFI. Meanwhile, the SQR estimates indicate that the poverty-reducing effects of financial inclusion are stronger among moderately deprived households compared to least or most deprived households. Our sensitivity and dominance analysis is consistent with these results. Based on our findings, we suggest that if policymakers' key objective is to reduce multidimensional poverty, greater emphasis should be placed on expanding digital financial inclusion. Moreover, offering bundles/packages of financial inclusion products instead of offering single FI products or services.
By SUMIT KUMAR; Indian Institute of Technology Indore
Presented by: SUMIT KUMAR, Indian Institute of Technology Indore
3. PALM OIL EXPANSION, DEFORESTATION, AND RURAL POVERTY: NONLINEAR EVIDENCE FROM INDONESIAN PROVINCIAL PANEL DATA Abstract Indonesia is the world's largest palm oil producer, and the rapid expansion of industrial oil palm plantations has become one of the leading drivers of tropical deforestation. While the palm oil sector is widely promoted as a source of economic growth and rural poverty reduction, its long-term welfare effects remain inconclusive. Existing studies report conflicting evidence, suggesting that the relationship between palm oil expansion and poverty may be nonlinear rather than strictly positive or negative. This study examines the nonlinear relationship between industrial palm oil-driven deforestation and rural poverty using a balanced panel dataset of 22 Indonesian provinces from 2010 to 2024 (330 province-year observations). The dependent variable is the natural logarithm of the number of rural poor, while the main explanatory variable is annual deforestation attributable to industrial palm oil concessions derived from satellite-based Trase data. Control variables include real regional GDP, average years of schooling, life expectancy, the open unemployment rate, population density, and total deforestation. The empirical analysis employs a two-way fixed effects model with Driscoll–Kraay standard errors to account for heteroskedasticity, serial correlation, and cross-sectional dependence. A quadratic specification is estimated to test for nonlinear effects. Additional robustness checks include lagged specifications and an exploratory System GMM model. The results reveal a statistically significant U-shaped relationship between industrial palm oil-driven deforestation and rural poverty. At relatively low levels of deforestation, expansion is associated with lower rural poverty, reflecting short-run employment and income effects. However, beyond an estimated turning point of approximately 213 hectares of annual concession-level deforestation, additional deforestation is associated with increasing rural poverty. The nonlinear relationship remains robust across both contemporaneous and lagged specifications and is further supported by the Lind–Mehlum U-test. In contrast, the simple linear relationship becomes statistically insignificant once temporal dynamics are introduced and is likewise not supported under the System GMM specification. These findings suggest that the welfare effects of palm oil expansion depend on the intensity of deforestation rather than expansion itself. The study contributes to the literature by combining satellite-verified deforestation data with a nonlinear panel framework and highlights the importance of threshold-based land-use governance to balance economic development with environmental sustainability and rural welfare.
By Dewinar Caesarin; Gadjah Mada University    Poppy Ismalina; Gadjah Mada University
Presented by: Dewinar Caesarin, Gadjah Mada University
4. Income Support Policy and Labour Income in a Developing Country: A cross-sectional analysis on the effect of Prakerja Policy in Eastern Indonesia Abstract Recent studies have highlighted the effect of exogenous shocks, such as Covid-19 pandemic, on emerging expansionary fiscal measures in both developed and developing countries. While these fiscal interventions may vary in each country, income support policies (ISPs) substantially emerged as the most adopted fiscal policy during the pandemic. Similarly, Indonesia also implemented an income support policy, known as Prakerja, in addressing the adverse effect of pandemic on the labour income. This study further investigates the effect of Prakerja on labour income in Eastern Indonesia. Using the Indonesia National Labour Force Survey (SAKERNAS) 2024, we employed a cross-sectional analysis to compare the labour income across two labour cohorts, which is the participant of Prakerja and the non-participants of Prakerja. The results show that participants of Prakerja significantly has 1.4 percent higher income than the non-participants of Prakerja in Eastern Indonesia. However, our analysis shows that other factors, such as age, gender, years of schooling, and employment status may also significantly contributes to labour income. These findings offer an initial baseline for understanding how fiscal interventions may impact labour income during exogenous shocks. Therefore, integrated policy framework is required to amplify the impact of income support policy on labour income and welfare.
By Rifi Djuuna; Universitas Negeri Gorontalo
Presented by: Rifi Djuuna, Universitas Negeri Gorontalo
Session 35: Environmental II: Efficiency, Productivity and Sustainability July 29, 2026 17:30 to 19:00 Location: Malaysia Room (level 5)
Session Chair: Joanna Poyago-Theotoky, University of Salento
Session type: invited
1. How Much Can Coordinated Demand-Side Management Ease Critical Mineral Constraints in China’s Energy Transition? Abstract Critical mineral constraints have moved from the margins of energy research to the center of the decarbonization debate. Yet most existing studies still ask a relatively narrow question: given a predetermined, supply-led transition pathway, how much critical minerals will be required? This question is important, but it is not fully solution-oriented. Once mineral demand is treated as a passive by-product of capacity expansion, the policy response is quickly reduced to an upstream agenda of securing more supply through mining, imports, refining, and geopolitically resilient supply chains. A more fundamental question remains underexplored: can the transition pathway itself be redesigned so that it requires fewer critical minerals? This paper addresses that question in the context of China’s net-zero power transition. It asks to what extent coordinated demand-side management (DSM) can relax critical mineral constraints without relaxing the decarbonization objective itself. The paper starts from a consequential proposition: critical mineral scarcity is not only a supply problem; it is also a problem of demand design. Whether mineral constraints become binding depends not merely on how much renewable and storage capacity is built, but also on how much electricity demand must be served, how rapidly capital stocks turn over, and how mineral-intensive the chosen technological configurations remain. The core hypothesis is that the mineral effect of DSM is not simply additive, but multiplicative across stages of the transition. Measures that moderate demand growth, improve efficiency, and enhance demand flexibility reduce the scale and reshape the temporal profile of the power system that must be built. Measures that extend equipment lifetimes slow capital turnover and reduce replacement inflows. Measures that raise recycling rates, lower material intensity, and substitute away from mineral-intensive technologies further reduce the mineral content of each remaining unit of expansion. Existing studies typically examine only one of these margins at a time. As a result, they may overstate the inevitability of mineral bottlenecks by overlooking the compounding effects of coordinated intervention across demand formation, stock turnover, and material composition. To examine this proposition, the paper develops an integrated provincial-resolution framework (D³M-CM Model) for China that links power-system planning, stock-driven material flow analysis, and critical mineral accounting. The power-system module embeds three demand-side levers directly into a multi-stage generation, storage, and interprovincial transmission expansion model with operational constraints: macroeconomic demand moderation, end-use electricity savings, and demand response. Importantly, the underlying optimization logic is held constant across scenarios, so that any reduction in mineral demand is not obtained by assuming that planners will tolerate arbitrarily higher system costs or weaker reliability simply to privilege demand-side options. The resulting province- and technology-specific capacity stocks are then translated into annual inflows of new equipment, which represent the actual source of mineral demand. At this stage, lifetime extension is introduced as a further demand-side strategy by slowing asset replacement. Finally, these inflows are converted into requirements for more than twenty critical mineral resources—including lithium, nickel, cobalt, copper, and rare earth elements—and are further adjusted through alternative assumptions on recycling, dematerialization, and material substitution. The contribution of the paper is therefore not merely to improve mineral accounting, but to reframe the policy problem. Rather than asking how China can secure enough critical minerals for a fixed transition trajectory, the paper asks whether a different trajectory can achieve carbon neutrality with systematically lower primary mineral requirements. This reframing is especially important in the Chinese context, where the transition is highly heterogeneous across provinces, technologies, and load structures. Mineral bottlenecks are unlikely to emerge uniformly. In some provinces, the main pressure may stem from rapid demand growth; in others, from inflexible load profiles, fast capital turnover, or particularly mineral-intensive technology choices. National aggregates therefore conceal the more policy-relevant questions: where do mineral constraints become binding, through which channels do they propagate, and which portfolios of demand moderation, efficiency improvement, flexibility, lifetime extension, recycling, dematerialization, and substitution provide the greatest relief? The paper makes three contributions. First, it shifts the critical-minerals debate from upstream supply security to downstream demand governance. Second, it bridges two literatures that are often disconnected: energy-system optimization and material-flow analysis. Third, it provides a policy-relevant framework for assessing whether coordinated DSM can expand the feasible space of China’s carbon-neutral transition under mineral scarcity. The full paper will report province-specific, technology-specific, and mineral-specific results for 2025–2050, and identify which combinations of demand moderation, flexibility, lifetime extension, recycling, dematerialization, and substitution are most effective in reducing cumulative primary mineral demand.
By Zewen Ge; Xiamen University Tan Kah Kee College
Presented by: Zewen Ge, Xiamen University Tan Kah Kee College
2. The Irrelevance of ESGMandates in Complete Markets Abstract We study ESG mandates in a production economy with complete financial markets. Agents face a quadratic penalty for deviating from ESG mandates. In equilibrium, Arrow–Debreu securities render stock payoffs redundant: agents use AD claims to insure consumption and adjust stock holdings only to avoid ESG penalties. Prices and allocations are unaffected by ESG mandates, only portfolio compositions respond. The economy exhibits ESG neutrality.
By Qian Wu; Duke Kunshan University
Presented by: Qian Wu, Duke Kunshan University
3. Public support for climate change mitigation policies: the influence of perceived personal policy benefits and global risk perceptions Abstract Asian governments have committed to timebound targets to achieve Net Zero carbon emissions. Far-reaching policies will be required to meet these targets, and public support will, in turn, be critical to the adoption and successful implementation of these policies. Previous work has shown that individuals with greater concern about climate change are more likely to support mitigation policy. However, people may exhibit lower support for specific emissions reductions policies construed in concrete terms than they do for policy construed in abstract terms like policy targets. A possible explanation is that personal impacts are more salient for individuals when policies are construed in concrete terms. The political feasibility of shifting from symbolic goal-setting to policy adoption may therefore be shaped by individuals’ perceptions of the personal costs/benefits of specific policies as well as their concern about climate change. This study employs data from a survey of 13,547 respondents conducted in 14 Asian economies in 2024 to examine the influence of perceptions of personal policy benefits, climate risk perceptions and other individual attributes on support for three specific climate change mitigation policies: public investment in low-carbon infrastructure, emissions regulations for buildings and appliances, and imposition of a carbon tax on businesses and households. Three analytical methods are employed: latent profile analysis, multilevel regression and mediation analysis. Latent profile analysis identified four distinct groups or ‘publics’ in Asia with different levels and patterns of policy support. Comparing the group opposed to all three policies with the group highly supportive of the three policies revealed large and significant differences between the groups in terms perceived personal benefits as well as global risk perceptions. Multilevel regression analyzing support for each policy separately shows that perceived personal benefits of specific policies are a significant determinant of policy support, controlling for policy familiarity, climate change risk perception and demographic characteristics. Perceived personal benefits also play a mediating role. Mediation analysis demonstrates that many factors including policy familiarity, specific climate change concerns and some demographic characteristics, influence support indirectly by shaping perceived benefits. Specifically, income exerts a substantial indirect effect on carbon tax support via perceived benefits, whereas education and risk perception operate predominantly through direct, normative pathways. The analysis suggests that in Information, Education and Communication interventions should prioritize messaging around the “solution space” over risk-centric information. Clearer communication about the mechanics and projected impacts of the policies themselves—specifically their cost-effectiveness and expected impacts on daily life can mitigate the “concreteness discount” and equip people to make informed judgements about policies based on their own priorities and values. Communication strategies should also reflect the cognitive demands of different policy types. The findings indicate that acceptance of carbon taxes may depend more on addressing individuals’ “pocketbook” concerns, whereas support for regulatory and investment-based policies can be more effectively mobilised through risk communication and appeals to collective responsibility.
By Tra TRINH; National University of Singapore
Presented by: Tra TRINH, National University of Singapore
4. ‘Green’ antitrust with environmental standards Abstract We explore the interplay of competition and environmental policies to address the question of whether ‘green’ antitrust has beneficial effects in terms of both environmental and consumer welfare performance. We focus on one particular environmental policy tool, an emissions cap (emissions standard), and explore three particular configurations: competitive ‘green’ R&D, collaborative ‘green’ R&D in the form of a joint lab, and the benchmark case of no ‘green’ R&D. Firms compete in the product market by selling a homogeneous product, either by setting prices (Bertrand competition) or quantities (Cournot competition) while facing convex costs. In the case of Bertrand competition we find that the joint lab outperforms the other configurations, while in Cournot competition the joint lab is the preferred configuration for rather large environmental damages.
By Marie-Laure Cabon-Dhersin    Joanna Poyago-Theotoky; University of Salento    Natacha Raffin; ENS, Université Paris-Saclay
Presented by: Joanna Poyago-Theotoky, University of Salento
Session 36: Financial III - Banking July 29, 2026 17:30 to 19:00 Location: Indonesia Room (level 5)
Session Chair: Barry Eichengreen, UC Berkeley
Session type: invited
1. Bank Capital and Profitability: Evidence from Australia and Singapore Abstract Abstract: This paper investigates the profitability implications of bank capital composition, with a particular focus on Tier 2 capital, in Australia and Singapore. Using a semi-annual panel of seven major listed banks from 2010–2024, this paper distinguishes between total capital, Capital Adequacy Ratio (CAR), and Tier 2 Capital. Baseline results indicate that Tier 2 capital is negatively associated with Return on Assets (ROA), with a one percentage point increase in Tier 2 capital reducing ROA by approximately 0.04 percentage point on a semi-annual basis, indicating a persistent profitability trade-off associated with subordinated debt instruments, whereby regulatory buffers strengthen resolution capacity but impose costs on bank performance. Using a Difference-in-Differences (DiD) framework, the study also examines the impact of the 2019 announcement of the Australian Prudential Regulation Authority (APRA) Loss-Absorbing Capacity (LAC) framework. Results show that Australian banks increased Tier 2 capital buffers by approximately 2.5 percentage points more than Singaporean banks following the announcement, alongside a relative decline in ROA of approximately 0.2 percentage points compared to Singaporean banks in the post-announcement period. In separate panel specifications, changes in CAR (ΔCAR) are negatively associated with ROA in pooled estimates but positively associated with ROA for Singaporean banks under Two-Stage Least Squares (2SLS) estimation. Under 2SLS estimation, book capital is negatively associated with changes in net interest margins (NIM) in the pooled sample, while a statistically significant inverted U-shaped relationship is observed for Singaporean banks. Keywords: Bank capital; Bank profitability; Capital adequacy ratio; Tier 2 capital; Return on assets JEL Classifications: G21, G32, C23
By Qi Min Loke; University of Canberra
Presented by: Qi Min Loke, University of Canberra
2. Does speed bump resolve the problems of mini flash crashes? Evidence from NYSE American Abstract In recent years, the emergence of mini flash crashes has become a distinctive concern within contemporary electronic trading markets, garnering attention from scholars, market participants, and regulators alike. These rapid, unforeseen market disruptions have been attributed to the breakneck pace of trading activity. This study employs data from the NYSE Trade and Quote database (TAQ) to examine the efficacy of implementing a “speed bump” mechanism in mitigating the risks associated with mini flash crashes. Utilizing machine learning techniques to estimate the likelihood of mini flash crashes occurring within the NYSE American market, this analysis offers empirical insights. The findings of this research demonstrate that the introduction of a speed bump mechanism can indeed reduce the probability of mini flash crashes. However, it is noteworthy that this mitigation strategy also leads to an influx of noise traders and bring slow traders back to the market, with positive market sentiment.
By Bo Liu; Huron University College at Western University
Presented by: Bo Liu, Huron University College at Western University
3. Cash, cards, and conflicts: how risk and financial innovation shape India’s currency demand Abstract This paper aims to examine the effect of geopolitical risk (GPR) and financial innovations—debit card (DC) and credit card (CC) on currency demand in India after the global financial crisis of 2008 for the recent period from 2012M04 to 2024M12. To this end, we estimate the impulse response functions using a novel method of the local projection model. We also perform an out-of-sample forecast comparison for currency demand using the vector autoregression (VAR) framework vis-à-vis the univariate benchmark naïve random walk model. As expected from the theory, there is an increase in currency demand, as a precautionary purposes, to an exogenous shock in the GPR. Concerning financial innovations, there has been a decrease in currency demand due to an impulse in the DC and CC. This is evident in the literature on money demand, wherein the component of money holding behaviour reduces to an increase in financial innovation. Moreover, credit card usage has a bigger impact on currency demand than debit card usage. Finally, the VAR-based forecast consistently outperforms the naïve benchmark model across all forecast error measures, indicating the superiority of the multivariate model over the univariate. These results imply that policymakers need dynamic currency management practices that should be responsive to the GPR and financial innovations.
By Masudul Adil; Indian Institute of Technology Bombay
Presented by: Masudul Adil, Indian Institute of Technology Bombay
4. Interoperability in the Payment Market and Its Impact on Bank Competition and Financial Inclusion: The Case of Cambodia Abstract Digital payment systems have emerged as a transformative force in developing economies, with the potential to lower transaction costs, deepen financial intermediation, and broaden access to formal financial services. A key policy lever in this space is interoperability — the ability of distinct payment providers and platforms to transact seamlessly with one another. While interoperability can intensify price competition and reduce user fees, it may also compress margins and dampen providers' incentives to invest in agent networks and infrastructure. The net effect on financial inclusion and market competition is therefore theoretically ambiguous, and ultimately an empirical question. This paper addresses that question in the context of Cambodia, a highly dollarized developing economy that has undergone significant payment system reform in recent years. In October 2020, the National Bank of Cambodia (NBC) launched Bakong — an interoperable, dual-currency retail payment infrastructure supporting QR and account-to-account transfers in both Khmer riel (KHR) and U.S. dollars. In July 2022, NBC further introduced KHQR, a unified QR standard adopted across banks and payment service providers, significantly lowering cross-platform frictions. Together, these reforms represent one of the most comprehensive payment system modernization efforts in Southeast Asia, and provide a rare opportunity to study the causal effects of interoperability on a financial system in a developing economy context. This paper examines how Bakong and KHQR affect Cambodia's financial system along three key dimensions. First, we study the impact on the outreach of financial institutions — specifically, whether Bakong participation expands deposit accounts, borrower numbers, loan and deposit amounts, and ATM presence across districts. Second, we examine competitive dynamics in deposit markets, focusing on whether Bakong drives convergence of market shares and leads to higher deposit rates and lower payment fees. Third, we investigate currency choice, asking whether Bakong's dual-currency infrastructure shifts deposit holdings and transactions from U.S. dollars toward Khmer riel, with important implications for Cambodia's dedollarization agenda. To address these questions, we employ a combination of reduced-form and structural empirical methods. For the outreach and competition analyses, we exploit the staggered rollout of Bakong participation across banks, estimating dynamic treatment effects using the Sun and Abraham (2021) event-study framework, with not-yet-treated and never-treated banks as controls. This approach avoids the pitfalls of two-way fixed effects estimators under heterogeneous treatment effects and traces the full dynamic path of Bakong's impact following adoption. We further examine distributional effects using a quantile difference-in-differences design following Callaway and Li (2019), assessing whether Bakong disproportionately benefits smaller banks — consistent with increased competition and market share convergence. Rural–urban heterogeneity analyses are conducted throughout to assess whether effects are concentrated in underserved or more competitive markets. For the currency choice analysis, we adopt a structural demand estimation framework building on Berry, Levinsohn, and Pakes (1995, 2004). By embedding Bakong participation into a structural demand system for bank deposits with an explicit currency dimension, we quantify substitution patterns between KHR and USD deposits, recover price elasticities of deposit demand, and assess how payment technology reshapes demand across banks and currencies. This structural approach addresses the endogeneity of deposit pricing, yielding consistent estimates of the key parameters of interest. Our empirical analysis draws on two main data sources. For the outreach and competition analyses, we use administrative panel data from the NBC Network Information Exchange (NBC-NIX) and the Cambodia Microfinance Association's Network Information Exchange (CMA-NIX), covering commercial banks, specialized banks, and microfinance institutions at the bank–district–quarter level from 2019Q4 to 2024Q1. For the currency choice and structural demand analyses, we use supervisory balance-sheet reports submitted to NBC, providing bank-level deposit and loan stocks broken down by currency, maturity, and sector. Both datasets are merged with bank-level Bakong adoption dates to construct the staggered treatment indicators central to our identification strategies. This study makes three contributions. It provides the first causal assessment of how a nationwide interoperable payment system with dual-currency functionality shapes currency choice and deposit market competition in a developing economy. It generates policy-relevant elasticities to evaluate pricing and financial inclusion trade-offs. And it offers evidence to inform dedollarization strategies that leverage payments interoperability rather than administrative restrictions to promote local currency use, with lessons applicable to other developing countries pursuing similar payment system reforms.
By Daiju Aiba; Japan International Cooperation Agency
Presented by: Daiju Aiba, Japan International Cooperation Agency
Session 37: Labor II July 29, 2026 17:30 to 19:00 Location: Philippines Room (level 5)
Session Chair: Yoko Niimi, Doshisha University
Session type: invited
1. Intangible Capital and Labor Income: Firm-Level Evidence from India Abstract The relationship between capital deepening and labor income shares is much studied, but there is little evidence that distinguishes between traditional forms of capital, such as machinery and equipment, and intangible ‘knowledge-based’ capital, such as software, research and development (R&D), organizational culture, and brand value. Using balance sheet data from over 30,000 companies in India between 2001 and 2021, this paper finds a significant positive relationship between both tangible and intangible capital, on the one hand, and labor income share, on the other hand. The positive relationship between intangible capital assets and labor income share can be attributed to the positive impact of intangibles on both labor productivity and employment, which is indicative of complementarities with jobs. Furthermore, the positive link between intangible capital assets and labor income share is stronger for firms operating in sectors with high skill, R&D, or ICT intensity, which is indicative of complementarities with skills.
By Abdul Azeez Erumban; University of Groningen    Gaurav Nayyar; World Bank    Shu Yu; The World Bank
Presented by: Shu Yu, The World Bank
2. Gender identity and married women’s labour supply and housework: Evidence from East Asia Abstract How do gender identity norms shape household behavior, and do similar norms generate similar responses across societies? This study examines the widely held belief that a wife should not earn more than her husband and investigates how couples adjust to potential deviations from this norm across different institutional contexts. Building on Bertrand et al. (2015), we conceptualize household responses as adjustments along three behavioral margins: wives’ labor force participation, the distribution of earnings within couples, and the allocation of non-market work. The key explanatory variable is the likelihood that a wife earns more than her husband, constructed from counterfactual income distributions within demographic groups. Identification exploits variation in this likelihood across groups defined by age, education, and region. We estimate logit, OLS, and ordered logit models and complement the analysis with permutation (placebo) tests. Using data from the East Asian Social Survey (China, Japan, and South Korea; 2006 and 2016), we provide a unified cross-country comparison. Despite broadly similar gender norms, the results reveal striking differences in how households adjust. In China, responses are concentrated in labor market outcomes, particularly in the suppression of wives’ realized earnings. In South Korea, adjustments occur mainly through labor force participation, especially in the earlier period. In contrast, in Japan, responses are primarily observed within the household, through changes in the allocation of non-market work. These findings show that similar gender identity norms do not necessarily lead to similar behavioral outcomes. Instead, households adjust along different margins depending on institutional and social contexts. More broadly, the results highlight the importance of jointly analyzing market and non-market behavior to understand the economic consequences of gender norms. Keywords: Gender identity norms, Identity economics, Behavioral margins, Female labor supply, Housework, Relative income JEL Classification: D13, J16, J22, Z13
By Kazuyasu Sakamoto; Gunma University    Yoko Morita; Nagoya City University
Presented by: Yoko Morita, Nagoya City University
3. Human Capital Leakage and Economic Performance Abstract Wars, political upheavals and consistent exits of skilled labor forces have historically disrupted the flow of human capital, with significant implications for economic development. This study examines the economic implications of human capital leakage in Southeast Asia by estimating and comparing the macroeconomic costs associated with human capital leakage. It develops a typology distinguishing involuntary and voluntary human capital leakage, thereby providing a comparative framework for understanding how different forms of human capital loss affect long-run economic performance. This study estimates the macroeconomic consequences of human capital leakage through counterfactual GDP modelling under maintained partial-equilibrium assumptions. Cambodia and Malaysia are used as presentative cases for involuntary and voluntary human capital leakage, respectively. The results show that involuntary human capital leakage is associated with abrupt, sharp and persistent level disruptions in economic output, while voluntary human capital leakage produces gradual divergence through cumulative erosion of skill intensity. By juxtaposing these two dimensions through a voluntary–involuntary human capital leakage typology, this study demonstrates that human capital leakage—whether sudden or gradual—carries measurable macroeconomic consequences. These findings demonstrate that different forms of human capital leakage generate distinct macroeconomic trajectories that are not fully captured within existing single-mechanism frameworks. The analysis highlights the importance of distinguishing between mechanisms of skilled labour exit when interpreting development outcomes and designing policy responses.
By Youngho Chang; Singapore University of Social Sciences    Jacqueline Tan; Singapore University of Social Sciences
Presented by: Jacqueline Tan, Singapore University of Social Sciences
4. Firm-Level Automation and Demand for Accounting Labor: Evidence from Online Job Postings in China Abstract This paper studies how firm-level automation affects demand for accounting personnel in China. Using a large dataset of online job postings from 2016 to 2023, we construct firm-year measures of accounting hiring through NLP-based classification of job titles and descriptions. The results show that higher automation significantly reduces firms' recruitment demand for accounting personnel. Mechanism analysis reveals that automation raises education requirements and prompts longer, more detailed job descriptions. This reflects a shift in labor demand toward workers with stronger human capital endowments. Heterogeneity analysis shows that the negative effect is concentrated among labor-intensive firms and state-owned enterprises. We further find that automation is associated with a declining labor income share but higher average wages per worker, suggesting that automation redistributes income away from labor as a whole while raising earnings among those who remain employed.
By Wenjing Qin; Southeast University    Yahan Wei; Southeast University    Xin Gu; Southeast University    Lan Du; Monash University
Presented by: Wenjing Qin, Southeast University
Session 38: Macroeconomics II July 29, 2026 17:30 to 19:00 Location: Brunei Room (level 5)
Session Chair: Charles Yuji Horioka, Kobe University
Session type: invited
1. Age and Job Satisfaction Relationship in Korea: A Longitudinal Study Abstract This paper examines how job satisfaction varies with age in the Korean workforce. Existing studies have relied on cross-sectional data and focused on Western contexts. This study, grounded in career plateau theory, addresses these gaps. Using a longitudinal unbalanced panel dataset comprising 153,773 participants over 20 years in Korea, the study employs both random-effects and fixed-effects and quantile regressions to account for individual heterogeneity and time-variant factors. The findings reveal a U-shaped relationship between age and job satisfaction. These results emphasize the importance of considering individual differences alongside fixed individual heterogeneity and temporal variations in understanding job satisfaction.
By Taehyun Lee; Korea Employment Information Service; Korea University    Almas Heshmati; University of Economics Ho Chi Minh City, Vietnam
Presented by: Taehyun Lee, Korea Employment Information Service; Korea University
2. The Perceived Government Budget Constraint Abstract We conduct a survey with an information-provision experiment to examine whether households' macroeconomic expectations are consistent with the intertemporal government budget constraint (GBC). Using respondents' forecasts of the debt-to-GDP ratio, inflation, interest rates, the primary balance, and real GDP growth, we compute the discrepancy between the left- and right-hand sides of the intertemporal GBC---which we refer to as the GBC wedge. We find that the GBC wedge is dispersed and, on average, non-zero. We also find that households revise their macroeconomic expectations in response to information provision in a way that is inconsistent with the intertemporal GBC.
By Takuji Fueki; Hitotsubashi University    MASASHI HINO; The University of Tokyo    Mitsuru Katagiri; Waseda University    Munechika Katayama; Waseda University    Taisuke Nakata; University of Tokyo
Presented by: MASASHI HINO, The University of Tokyo
3. Seniority, Savings, and Stagnation: A Macro Perspective on Wage Systems and R&D Investment Abstract Many developed countries are facing serious challenges due to falling fertility rates and aging populations. These demographic changes are shrinking the labor force and reducing overall savings, as more individuals begin to draw down their savings. This trend slows capital accumulation and weakens long-term economic growth. In addition, a shrinking population of scientists within the labor force can be expected to constrain research and development (R&D) investment and further dampen economic growth. Beyond these familiar effects, population decline also impacts innovation through a less obvious channel: the seniority-based wage system common in many OECD countries. In such systems, younger workers are typically paid less than their actual productivity. The difference becomes retained earnings for companies, which are often invested in R&D. Empirical evidence shows that firms use these retained earnings to fund R&D activities. Therefore, as the number of young workers declines, retained earnings shrink, leading to stagnant investment in innovation. This means population decline not only reduces the number of scientists but also slows internal finance for R&D investment. In order to explore this relationship, we develop a two-period overlapping generations model in which growth is driven by exogenous technological progress and endogenous human capital accumulation. In this model, individuals work during both youth and adulthood. Young workers earn wages below their marginal productivity, and the gap is used to finance intra-firm R&D. This setup links seniority-based wages directly to innovation-driven growth. Our findings reveal that population decline significantly hinders economic development. Furthermore, when companies pay young workers wages closer to their productivity, retained earnings fall, and R&D investment slows—ultimately impeding growth. In labor markets with fewer young people, firms that raise wages to attract young workers, as has been observed in numerous Japanese firms, may unintentionally contribute to long-term stagnation. In conclusion, the interaction between demographics, wage structures, and innovation investment plays a critical role in shaping economic outcomes. Tackling population decline requires more than boosting fertility rates or immigration. It demands a broader strategy that includes rethinking wage systems and strengthening corporate R&D investment to maintain sustainable growth.
By Hiroyuki Hashimoto; University of Hyogo    Atsushi Miyake; Kobe Gakuin University
Presented by: Atsushi Miyake, Kobe Gakuin University
4. Capital Misallocation and Earnings-based Borrowing Abstract Abstract: Existing literature in capital misallocation and credit markets typically explains capital misallocation by the asset-based borrowing constraint: firms can only borrow up to a fraction of the value of their assets. In practice, the majority of U.S. corporate debt is constrained by earnings, not assets. This paper studies how earnings-based borrowing shapes capital allocation and efficiency. Using the Enron–Arthur Andersen accounting scandal as the first natural experiment on earnings-based financial frictions, I find causal evidence that a 10-percentage-point decline in a firm’s share of newly issued earnings-based borrowing increases the firm's marginal revenue product of capital (MRPK) growth by 6.6 percentage points more for the high-MRPK than the low-MRPK firms. A simple model formalizes the mechanism: earnings-based borrowing channels funds toward more productive firms and compresses the dispersion of MRPK, as productive firms tend to have higher earnings. In a calibrated quantitative general equilibrium heterogeneous-firm model, the Enron shock reduces aggregate TFP by 0.45% through the tightening of the earnings-based borrowing constraint. In contrast, a comparable tightening of the asset-based borrowing constraint would lower TFP by only 0.1%. Taken together, the evidence highlights earnings-based borrowing as a key credit margin that supports allocative efficiency and limits misallocation. JEL codes: D24, D25, G32, O47 Keywords: earnings-based borrowing, capital misallocation, allocative efficiency, MRPK, corporate debt, financial frictions, heterogeneous firms, TFP, natural experiment
By Yuhao Qian; London School of Economics
Presented by: Yuhao Qian, London School of Economics
Session 39: Urban I July 29, 2026 17:30 to 19:00 Location: Vietnam Room (level 5)
Session Chair: Yeow Hwee Chua, Nanyang Technological University
Session type: invited
1. Freight Hubs and the Geography of Production Abstract In 2022, trucks carried $13.2 trillion of all goods shipped in the US – $7.2 trillion in manufacturing shipments alone. The cost of moving these goods is not uniform and depends on shipment size: full truckloads move point-to-point, while smaller shipments must route through hub-and-spoke consolidation networks. Yet trade models have largely abstracted from freight network structure, treating transport costs as distance-based iceberg, and otherwise featureless. As a result, how freight network structure shapes delivered input costs – and thereby the spatial distribution of manufacturing – remains largely unexplored. In this paper, I study how the hub-and-spoke structure used for freight consolidation shapes where manufacturing locates. I first document evidence that hub proximity reduces freight rates; and then formalize freight as a shipment-size dependent technology and embed bi-modal transport choice into a quantitative spatial general equilibrium model. I show that (i) hub proximity confers cost advantages that are larger for firms with smaller shipments; (ii) intermediate-input sourcing amplifies (or partially offsets) these advantages through a bad-neighbor/good-neighbor channel; and (iii) the resulting spatial distribution of manufacturing differs substantially from the distance-only iceberg benchmark. These three findings reveal a new role for freight network structure in economic geography – one that standard iceberg trade costs cannot capture. Following the “buses versus taxis” distinction in the transport literature—itinerary-based networks versus on-demand point-to-point dispatch – I emphasize an analogous segmentation within trucking. Truckload (TL) shipments – typically large, homogeneous loads – move point-to-point on dedicated dispatch, with marginal costs driven primarily by linehaul distance. Less-than-truckload (LTL) shipments, by contrast, consolidate small and heterogeneous freight through hub-and-spoke terminal networks because small consignments are rarely economical to move directly. This routing introduces a network component of trade costs – detours, terminal handling, and dependence on hub proximity – that is largely orthogonal to bilateral distance. The implication is that delivered prices can vary sharply with network position. I implement this argument in two steps, linking a reduced-form equation to a structural spatial equilibrium. On the empirical side, I collect posted freight-rate quotes from one of the largest online freight-rate aggregation platforms, and assemble a panel of TL and LTL rates for standardized shipment characteristics across routes connecting 50 randomly selected US ZIP codes. I then construct geospatial measures of LTL hub proximity by mapping consolidation terminals using satellite imagery – leveraging the characteristic cross-dock footprint and bay-door layout of LTL facilities. The baseline specification relates freight rates to origin–destination distance and measures of hub proximity, while absorbing origin and destination fixed effects, so identification comes from cross-route differences in network exposure. The estimates show that distance predicts rates in both TL and LTL markets, but hub proximity is an additional determinant for LTL: rates are lower when destinations are closer to consolidation hubs, and this hub gradient is strongest on shorter routes where hub-and-spoke routing implies relatively large detours. In ongoing work, I complement this with an instrumental-variables strategy that uses historical railroad infrastructure to predict contemporary hub locations and leverages archival pre-deregulation carrier directories (1979) to measure network placement before the 1980 Motor Carrier Act reshaped the industry. On the theory side, I model freight as a shipment-size dependent technology with a discrete modal choice: large shipments travel point-to-point (TL), while small shipments are consolidated through a hub-and-spoke route (LTL), generating detours and terminal-handling wedges orthogonal to bilateral distance. I embed this transport block into a quantitative spatial general equilibrium model with intermediate inputs, so hub proximity affects both firms’ selling costs and their delivered input price index for a given hub network. Fixed terminal costs and truck indivisibilities generate density economies in consolidation, making hub proximity valuable independently of OD distance. With intermediates, these advantages are amplified through sourcing: hub-proximate firms face lower costs when buying from other hub-proximate suppliers, reinforcing spatial concentration. In ongoing work, I close the model by jointly determining manufacturing locations and hub placement, and quantify the welfare value of hubs and the welfare loss from suboptimal hub/manufacturing allocations. These findings contribute to the literature on trade costs, economic geography, and firm sorting across space. While recent work has studied how heterogeneous firms sort across locations (Gaubert, 2018; Fajgelbaum and Gaubert, 2020) and how transport costs shape spatial equilibria through road networks (Allen and Arkolakis, 2014; Allen, Atkin, Cleves, and Hernandez, 2024) and shipping markets (Brancaccio, Kalouptsidi, and Papageorgiou, 2020), the role of hub-and-spoke consolidation in shaping manufacturing location remains unexplored. The framework has implications for infrastructure policy: investments in hub capacity or placement have spatial consequences that extend beyond logistics efficiency to the geography of manufacturing itself.
By Ritabrata Bose; Arizona State University
Presented by: Ritabrata Bose, Arizona State University
2. Powering the Vertical City: Electricity Supply Uncertainty in the High-Rise Housing Market Abstract Powering the Vertical City: Electricity Supply Uncertainty in the High-Rise Housing Market Abstract A stable electricity supply is critical to high-rise cities. This paper studies how perceived electricity-supply uncertainty, triggered by Taiwan’s 2017 power crisis, affects housing prices and migration in a high-rise, downtown urban area. The crisis involved two weeks of electricity rationing followed by the August 15 large-scale blackout that affected nearly six million households. Using within-building comparisons across floors, we find that the upper-floor price premium declines after the crisis, with larger effects in neighborhoods with more elderly residents, older buildings, and mid-income areas. The upper-floor discount is stronger in more electricity-intensive neighborhoods and during periods of tighter grid conditions, consistent with heightened perceived reliability risk. We also find reduced in-migration to low-income, high-rise neighborhoods and slower growth in taxable income in these areas, suggesting that infrastructure risk can reinforce spatial inequality. Keywords: Risk perception; housing market; electricity supply uncertainty; migration; electricity crisis; 7.29 Power Rationing Crisis; 8.15 Blackout
By Yajie SUN
Presented by: Yajie SUN,
3. Housing Market Signals and Beliefs about Social Mobility Abstract We study how housing market signals shape beliefs about social mobility. Using a survey experiment that exogenously varies information on house price changes and housing policies, we elicit beliefs about future mobility at the bottom and the top of the income distribution. We find that increases in house prices and housing taxes reduce perceived upward mobility for individuals at the bottom, while leaving beliefs about mobility at the top unchanged. In contrast, information about slower house price growth and housing subsidies has no effect on mobility beliefs. These asymmetric responses are difficult to reconcile with affordability-based explanations and instead support a reference-dependent account of belief formation, in which worsening housing conditions receive disproportionate weight in shaping perceptions of economic opportunity.
By Yeow Hwee Chua; Nanyang Technological University    Wenyi Zhang; Nanyang Technological University
Presented by: Wenyi Zhang, Nanyang Technological University
4. When Buyers Exit: Foreign Buyer Taxes in Segmented Housing Markets Abstract We study how housing markets adjust to large increases in buyer-side transaction taxes. Exploiting the unexpected doubling of Singapore’s foreign buyer tax from 30 to 60 percent in April 2023, we implement a difference-in-differences design comparing foreign and local buyers across finely defined housing market segments. The reform triggers a sharp and persistent exit of foreign buyers, with transaction volumes falling by 26 percent relative to locals. Adjustment is highly segmented: transactions decline by 30 to 50 percent in high-end and mainstream segments where foreign participation was concentrated, while lower-end segments are largely unaffected. We find no evidence of substitution toward cheaper properties or reallocation across regions. Net-of-tax transaction prices adjust modestly and only where foreign buyers previously acted as marginal participants, indicating adjustment through selective exit rather than reallocation.
By Yeow Hwee Chua; Nanyang Technological University    Jiayi Wu; Nanyang Technological University
Presented by: Yeow Hwee Chua, Nanyang Technological University
Session 40: AI and Digital Markets I July 30, 2026 8:30 to 10:00 Location: Cambodia Room (level 5)
Session Chair: Guiying Laura Wu, Nanyang Technological University
Session type: contributed
1. International Trade in a Digital Era: The Case of US Movie Exports Abstract One of the most transformative technologies of the last three decades is digitization. We investigate how it reshapes international trade by examining US movie exports, an industry with unusually good measures of digital transformation and product quality. We document three empirical findings. First, we confirm that digitization weakens the gravity effect. Second, we show a new data pattern: digitization also weakens the Washington Apples effect. The relative advantage of higher-quality products in reaching far-away market over lower-quality varieties is reduced as digitization is increased. Third, digitization weakens the relative advantage of the big producers. The share of movies by smaller producers in exports rises as digitization progresses.
By Haichao Fan; Fudan University    Yichuan Hu; Tongji University    Lixin Tang; Jinan University    Shang-Jin Wei; Columbia University
Presented by: Lixin Tang, Jinan University
2. Industrial intelligence and firms’ labor income share: The moderating role of employee digital penetration Abstract 工业智能正在重塑企业内价值的分配方式，但其分配后果在理论上仍不明确。在此背景下，工业智能如何重塑劳动收入份额已成为一个重要的研究议题。本研究将企业采用工业机器人纳入劳动收入份额分析框架。研究探讨了工业智能对收入分配的影响。结果显示，工业智能显著提升了企业的劳动收入份额。本研究基于社会技术系统转型理论，构建了一个多层次分析框架。该框架涵盖微观、中观和宏观层面因素。研究结果表明，工业智能通过技能结构优化、产业升级以及企业在分工中的地位提升，重塑了劳动收入结构。研究还将员工数字化渗透引入分析。结果表明，员工数字渗透率越高，工业智能对劳动收入份额的积极影响越弱。进一步分析显示，工业智能对劳动收入份额具有显著的反U形效应。然而，其线性效应在时间推移中具有一定程度的持续性。总体而言，本研究扩展了关于工业智能经济影响的文献。它还提供了关于数字化与智能化双重转型下企业内部收入分配变化的实证证据。
By Xinyu Dou; China University of Mining and Technology    Ziyuan Sun; China University of Mining and Technology
Presented by: Xinyu Dou, China University of Mining and Technology
3. Generative AI and Firm Employment Adjustment: Evidence from Chinese Listed Firms Abstract This paper estimates the impact of generative artificial intelligence (GenAI) adoption on firm-level employment in China. We assemble a novel dataset by merging millions of online job postings from three leading Chinese job boards—51job, Zhaopin, and Liepin—with comprehensive employment and financial records from 3,244 publicly listed firms spanning 2014–2024. Using a dictionary-based approach to identify GenAI-related recruitment and the timing of firm-level adoption, we find that approximately 11 percent of listed Chinese firms had adopted GenAI by the end of 2024. The results further show that adopters were more likely to be in the market services sector, larger, and often state-owned. We then assess the labor implications of GenAI adoption using staggered difference-in-differences (DiD) and event-study methodologies. The DiD estimations reveal that GenAI adoption correlates with a 2–3 percentage-point reduction in employment growth. The finding is robust to alternative estimators, various approaches to handling extreme values, placebo tests, and alternative measures of GenAI adoption. Notably, the adverse effect on employment growth is predominantly observed in manufacturing firms, particularly within production and technical functions. Moreover, private and larger firms exhibit more pronounced declines in employment growth following GenAI adoption. (Preliminary version. Please do not cite or circulate without the authors’ permission.)
By Lixing Li; Peking University    Zhencen Liu; World Bank    He Wang; The World Bank    Shu Yu; The World Bank
Presented by: Zhencen Liu, World Bank
4. Estimating the Real Effect of Endogenous Digital Technology Adoption Abstract This paper develops a model on firms’ optimal decisions in digital technology adoption. We test the model using an endogenous treatment effect framework, which simultaneously estimates which firm characteristics lead to adoption and what is the outcome of the adoption. We then apply the model to a panel of Chinese publicly listed firms, with a refined measure on digital technology adoption that passes a set of validity tests. While observable firm characteristics suggest a positive selection that is often documented in existing literature, we find unobservable factors suggest a negative selection and lead to a “refugee sorting”. Adopters gain market share, reduce production costs, enhance productivity, substitute capital for labour, and achieve a significantly higher profit. None-adopters are those initially more advantageous firms in unobservable factors. Our empirical findings are consistent with the model mechanism where digital technology acts as a great equalizer.
By Mengyuan Cai; Nanyang Technological University    Guiying Laura Wu; Nanyang Technological University
Presented by: Guiying Laura Wu, Nanyang Technological University
Session 41: Development III July 30, 2026 8:30 to 10:00 Location: Singapore Room (level 5)
Session Chair: Jr-Tsung Huang, National Chengchi University
Session type: invited
1. The Price of Resilience: Extreme Weather, Labor Adaptation, and Birth Rates in Rural China Abstract This paper examines how extreme precipitation affects fertility and whether local adaptation capacity shapes this response. Using fertility histories reconstructed from the 2015 1% National Population Sample Survey and county-level precipitation records for rural China during 2000–2014, we exploit within-county variation in lagged precipitation extremes while controlling for province-year shocks. Both extreme dry and wet conditions reduce subsequent fertility. The preferred estimate indicates a decline of approximately 3 births per 1,000 rural registered-address women aged 20–49. The effect is nonlinear and remains robust across alternative precipitation measures, fertility outcomes, exposure windows, and model specifications. The mechanism results link the fertility decline to agricultural income losses and working-age migration, while providing no evidence that changes in measured adult health explain this response. The effect is concentrated in areas with greater agricultural exposure and weaker adaptation capacity. These findings show that the demographic consequences of climate shocks depend on households’ economic adjustment opportunities and local capacity to absorb agricultural risk.
By Xiling Lei; Southwestern University of Finance and Economics    Weijian Lao
Presented by: Xiling Lei, Southwestern University of Finance and Economics
2. Economic Development with an (Un)limited Supply of Labor in a Global Economy: Emigration and Rising Wages Abstract Lewis assumes an unlimited supply of labor in the subsistence sector and argues that labor migration without upward pressure on subsistence wages enables industrial expansion. This paper treats developing economies collectively as the subsistence sector in a global economy context. Using the data from 96 countries between 1990 and 2022, I estimate wage elasticities with respect to emigration. The results show that labor emigration significantly increases wages in origin countries, and the effect is stronger in economies with larger migrant shares. Further results show wages in Africa are more sensitive to emigration than in Asia. I feed the wage elasticity estimates into the dynamic general equilibrium model to assess broader economic implications. Reducing migration barriers improves global efficiency and welfare. However, a fundamental trade-off exists in developing countries. While welfare improves, labor emigration causes output losses by raising labor costs and weakening incentives for capital accumulation, thereby stalling industrialization. The findings highlight a tension between global labor mobility and industrial development in capital-scarce economies.
By Sokchea Lim; John Carroll University
Presented by: Sokchea Lim, John Carroll University
3. Sectoral and Geographic Determinants of Automation Adoption in Thai Manufacturing: Evidence from Firm-Level Data and Industrial Capability Perspectives Abstract Firm-level evidence from Thai manufacturing shows that automation adoption is associated with improved firm performance and shifts in labor demand, raising broader questions about the determinants of technological adoption in developing economies. Existing studies primarily conceptualize automation as a short-term investment decision, leaving its roots underexplored in long-term industrial capability accumulation. This paper develops an industrial capability framework to analyze the determinants of automation adoption in Thai manufacturing. It argues that automation is shaped not only by firm-level characteristics but also by sectoral accumulation of technological, organizational, and human capital capabilities and by the geographic environments in which firms operate. The empirical analysis combines multiple waves of the Thai manufacturing census in 2012, 2017, and 2022 to construct pre-automation measures of industrial capabilities. Linking these measures to automation adoption in 2022, the study examines the roles of sector-level indicators, including productivity, capital intensity, research and development intensity, and workforce composition, alongside location-specific characteristics. Preliminary findings indicate that automation adoption is shaped by pre-existing industrial capabilities, research and development intensity, firm-level human capital, and regional industrial ecosystems. These results highlight the central role of long-term capability building and spatial industrial policy in shaping technological upgrading and extending the automation literature by demonstrating that adoption is fundamentally embedded in sectoral and geographic structures rather than being a purely firm-level decision.
By Prawit Banjong; National Statistical Office
Presented by: Prawit Banjong, National Statistical Office
4. Spillover effects of climate physical risks through intercountry production and financial ties Abstract Climate physical risks are intensifying and pose a major obstacle to global sustainable development. Although countries are deeply interconnected through trade, capital flows and industrial specialization, it remains unclear whether these linkages facilitate the cross-border transmission of climate physical risks. Here, using global input-output data and cross-border capital flow records, we integrate spatial econometric models with improved spatial weight matrices and complex network methods to quantify the spillover effects of climate physical risks through production and financial networks. Our results show that climate physical risks generate significant negative spillover effects through cross-border production and financial linkages, with production networks serving as the primary spillover channel. Climate type and geographic location influence the strength of spillover effects across the dual network. Countries differ markedly in their levels of risk spillover and risk bearing. We highlight the critical gap of assessing local shock effects without considering broader economic linkages, and we therefore advocate for climate risks management policies that account for global economic interconnections.
By MIAO CHEN; Southeast Unversity
Presented by: MIAO CHEN, Southeast Unversity
Session 42: Empirical I July 30, 2026 8:30 to 10:00 Location: Thailand Room (level 5)
Session Chair: Jiaoying Pei, University of Cambridge
Session type: invited
1. Dynamic Yardstick Competition: A Study of Japanese Railway Industry Abstract This study examines the investment and effort decisions of natural monopolies within the context of yardstick regulation. Yardstick regulation involves regulators assessing monopolies by comparing their performance to similar firms in the industry. Theories in mechanism design suggest that yardstick regulation can mitigate cost inefficiencies. This paper aims to investigate this claim by examining the private rail operators in the Japanese railway industry. To assess the effect of regulation, I formulate a dynamic structural model for natural monopolies and clarify the mechanism behind yardstick competition. By conducting a counterfactual analysis, this paper provides policymakers with empirical evidence for incentive-based regulation. JEL: D22, L22, L51
By Jhongyi Huang; The Ohio State University
Presented by: Jhongyi Huang, The Ohio State University
2. Research on the “SAFE” Effect of Pension Financial Asset Allocation on Silver Consumption: Evidence from China Abstract Amid accelerating population aging and the push for high-quality development of the silver economy, whether pension financial asset allocation can unlock elderly consumption potential is a critical question. Using data from the China Household Finance Survey (CHFS), this study investigates the impact of pension financial asset allocation on silver consumption and its underlying mechanisms. The results show that pension financial asset allocation significantly increases total household consumption among the elderly, with a notably stronger effect on developmental and enjoyment-oriented consumption than on subsistence consumption, thereby facilitating the upgrading of elderly consumption patterns. Mechanism analysis identifies four pathways: enhancing social interaction, increasing investment returns, improving financial literacy, and boosting subjective well-being, which we term the "SAFE" effect. Heterogeneity tests further indicate that this promotional effect is particularly pronounced in central-western regions, northeastern regions, rural households, low-income families, and less-educated households, suggesting that pension financial asset allocation generates stronger marginal improvements for vulnerable groups. This study provides micro-level empirical evidence for improving the pension financial system and unlocking the consumption potential of the elderly.
By YUFEI LIU; Shanghai Normal University    Yi Yin; Shanghai Normal University    Xiaokun Chang; Ningbo University of Finance & Economics
Presented by: YUFEI LIU, Shanghai Normal University
3. The impact of Digitalization and Non-Tariff Barriers on Services Trade: An empirical investigation Abstract This paper examines the dual necessity of advancing digitalization development and dismantling non-tariff barriers (NTBs) to catalyze services exports, hitherto not explored in the empirical literature. We argue that while the level of digital infrastructure and technology adoption determines a nation's technical capacity to export, the removal of policy restrictions and regulatory hurdles—specifically those targeting digital trade and professional services—is the critical prerequisite for market entry and scalability. We adopt a structural gravity framework, incorporating panel data with fixed effects for 55 economies between 2014 and 2022. We add value to the empirical work by evaluating digitalization through an intensity index constructed from the OECD Inter-Country Input-Output (ICIO) tables, computing sector-level ICT intermediate input shares in total intermediate inputs. Non-tariff barriers are evaluated through the STRI index which provides annual, sector-specific regulatory restrictiveness scores for a broad panel of OECD and non-OECD economies. Our empirical strategy implements a three-way sequential interaction between digitalization, STRI and a variable that distinguishes between domestic and international trade. Our findings suggest a synergistic effect: the simultaneous improvement of digital readiness and the reduction of regulatory barriers significantly boost the volume of both traditional services and digitally deliverable services. To assess the empirical validity of our findings, we augment the model undertaking a range of heterogeneity tests, and check for robustness. We demonstrate that the relationship is particularly strong for trading nations with higher digital intensity, significantly enhancing Services trade exports, particularly impacting middle- and high-income countries. Our findings reveal a positive association between digital economy indices and overall service exports as well as those that are digitally deliverable, suggesting that advancements in digital infrastructure, market dynamics, conducive regulatory environment through lowering service trade restrictiveness barriers and governance in partner countries facilitate the same. These insights guide specific policy recommendations, highlighting the need for strategic international cooperation, regulatory coherence, and infrastructure investment to improve service trade and harness digital globalization’s full potential.
By Sadhana Srivastava; Infinite Sum Modelling USA    Peiyu Xu
Presented by: Sadhana Srivastava, Infinite Sum Modelling USA
4. An Improved Inference for IV Regressions Abstract Empirical instrumental variables (IV) studies often report separate results based on low-dimensional instruments and many base instruments. This paper proposes a combination test that integrates these commonly reported statistics. The test linearly combines a cluster-robust Wald statistic based on low-dimensional IVs with leave-one-cluster-out Lagrangian multiplier (LM) and Anderson-Rubin (AR) statistics constructed from many IVs. We establish joint asymptotic normality and asymptotic optimality of the proposed test. The procedure yields costless efficiency improvements, automatically adapts to weak identification of many instruments, and is accompanied by a practical rule of thumb for assessing efficiency gains. Keywords: Many Weak Instruments, Shift-Share Instruments, Combination Test. JEL classification: C12, C36, C55.
By Liyu Dou; Singapore Management University    Pengjin Min; Singapore Management University    Wenjie Wang; Nanyang Technological University    Yichong Zhang; Singapore Management University
Presented by: Pengjin Min, Singapore Management University
Session 43: Environmental III July 30, 2026 8:30 to 10:00 Location: Malaysia Room (level 5)
Session Chair: Asif Siddiqui, Nanyang Technological University
Session type: invited
1. Dynamic effects of working from home on carbon emissions: Fresh findings from Chinese households Abstract Working from home (WFH) is increasingly advocated as a sustainable employment strategy to mitigate CO2 emissions. While there is no consensus on the effect of WFH on emissions in studies. Based on panel data from the China Family Panel Studies (CFPS) for the years 2010 to 2020, this study adopts an Autoregressive Distributed Lag (ARDL) model within the Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) analytical framework. It provides empirical evidence on the dualistic effects of WFH on household indirect emissions in short and long terms. WFH is measured by family members engaged in primary employment, utilizing telephones and computers, excluding self-employed individuals. The findings indicate that a unit increase in WFH correlates with a 4.5% reduction in emissions in short term due to decreased commuting. Conversely, in long term, a unit increase leads to a 12% rise in emissions, driven by shaping lifestyles to be more carbon-intensive. These insights prompt policymakers to focus on promoting sustainable behaviors among telecommuters, particularly within households earning less than CNY 124.3 thousand annually.
By Shuhong Zheng; Hubei University of Economics
Presented by: Shuhong Zheng, Hubei University of Economics
2. Patent Shuffling: Internal Green Technology Transfers and Strategic Greenwashing under Environmental Regulation Abstract Environmental regulations and ESG assessments have rendered green transformation a survival imperative for preserving institutional legitimacy. Yet substantive greening entails prohibitive costs, incentivizing firms to employ strategic greenwashing as a shortcut. While external scrutiny deters overt deception, whether firms turn to internal group networks as a more covert channel remains underexplored. Drawing on panel data for Chinese listed firms from 2006 to 2023, this study examines whether intra-group green technology transfer (IGPT) facilitates such greenwashing. We find that IGPT improves firms' external environmental ratings without commensurate reductions in pollution emissions. Stricter environmental regulation amplifies this divergence: under heightened pressure, IGPT is associated with both higher ratings and worse pollution outcomes. Mechanism tests reveal that IGPT attracts external resources that are not directed toward environmental governance, while simultaneously enriching disclosures to enhance impression management. Additional analyses indicate that improved ratings offset regulatory penalties in capital markets, further confirming the opportunistic nature of this behavior. These findings caution regulators and investors to scrutinize actual pollution control processes rather than relying solely on green signals or ratings.
By Han Guoying; Southeast University
Presented by: Han Guoying, Southeast University
3. Financial development, Environmental regulation, and Firms’ Pollution emission: evidence from China Abstract This paper examines how banking sector reforms in China between 1998 and 2007 affected firms’ pollution emissions by easing credit constraints. Exploiting variation in local bank competition and sectoral financial dependence, we find that banking deregulation significantly reduces air pollution emissions (SO₂ and waste gas), while having limited effects on water pollutants (COD and wastewater). We document three mechanisms: (i) financial deregulation lowers firms’ borrowing costs, easing financing constraints; (ii) firms invest in both abatement equipment and energy-efficient technologies that improve air-pollution performance; and (iii) firms shift their asset mix away from collateral-intensive tangible assets without expanding output. The results highlight that financial liberalization facilitates selective technology adoption that reduces pollution, especially for air pollutants subject to stronger regulatory pressure, but does not automatically extend to water pollution. Our findings underscore the importance of financial sector reforms as a complement to environmental policy in emerging economies.
By zhao li; Shanghai University of International Business and Economics.
Presented by: zhao li, Shanghai University of International Business and Economics.
4. Floods and the housing market in Malaysia Abstract This essay examines whether annual flood exposure is associated with residential housing market outcomes in Malaysia. Although a substantial body of research has documented the capitalization of environmental risks into housing markets in developed countries, evidence from developing economies remains limited. To address this gap, the study combines high-resolution satellite-derived flood observations with nationwide residential housing transaction data at the 1 km × 1 km grid level and employs a dynamic difference-in-differences framework to estimate the effects of annual flood exposure on housing prices per floor area and transaction volume over time. Additional analyses examine heterogeneity across major property types and assess the robustness of the results by accounting for potential spatial spillover effects from neighboring flooded areas. Across the full sample and all robustness specifications, the findings provide little evidence that annual flood exposure is associated with economically meaningful or persistent changes in residential housing prices or transaction activity. Estimated effects remain small in magnitude and are generally statistically indistinguishable from zero, with similar patterns observed across different property types and after excluding nearby areas potentially affected by spillover effects. Overall, the results suggest that Malaysia's residential housing market exhibits a high degree of resilience to recurring annual flood exposure. These findings are consistent with the possibility that adaptation measures, community resilience, and continued government investment in flood mitigation reduce the extent to which recurring flood exposure is capitalized into residential housing market outcomes. By documenting the limited housing market response to annual flood exposure, this study contributes to the growing literature on climate risk and housing markets in developing countries.
By Izzat Bin Halim; Sogang University
Presented by: Izzat Bin Halim, Sogang University
Session 44: Financial IV - Corporate Finance July 30, 2026 8:30 to 10:00 Location: Indonesia Room (level 5)
Session Chair: Zhikai Wang, Zhejiang University
Session type: invited
1. Flow-Driven Demand and Price Multiplier: Evidence from Corporate Bond Market Abstract The sensitivity of asset prices to investor demand, the price multiplier, captures the fragility of financial markets and the transmission strength of quantity-based policies. This paper documents that price multipliers vary systematically across levels of market aggregation, market structure, and policy regime. Using the unique institutional setting of China’s segmented bond market—the world’s second largest—I provide the first systematic evidence of exceptionally high price multipliers, an order of magnitude larger than those observed in developed markets. The results reveal pronounced heterogeneity across trading venues and policy environments, indicating that price responses are strongly state-dependent. These findings also suggest that market design and policy conditions fundamentally influence demand elasticities and price adjustments, offering new empirical foundations for extending demand-based asset pricing to segmented and policy-driven financial systems.
By Jinzhe Xiang; Indiana University
Presented by: Jinzhe Xiang, Indiana University
2. The Impact of Climate Transition Risk on Corporate Debt Default: Evidence from Chinese Listed Firms Abstract As global warming intensifies, climate change has increasingly evolved into a systemic risk with far-reaching implications for economic stability and financial systems. In response, governments worldwide are implementing stringent emission reduction policies to facilitate low-carbon transitions. China, in particular, has advanced its “dual carbon” goals and positioned green finance as a central policy instrument. Within this context, climate transition risks, arising from regulatory changes, technological innovation, and shifting market expectations, are progressively transmitted to the micro level, shaping firms’ operational and financial conditions. Corporate debt default, as a critical firm-level outcome, not only threatens firm survival but may also propagate risks across supply chains and financial markets. Despite its significance, existing literature has predominantly focused on climate physical risks or macro-level financial stability, leaving limited empirical evidence on how transition risks affect corporate default risk and through which mechanisms. This study addresses this gap by systematically examining the impact of climate transition risk on corporate debt default and identifying its transmission channels and boundary conditions. Using a panel dataset of Chinese A-share listed firms from 2013 to 2023, we construct a firm-level measure of climate transition risk based on textual analysis of annual reports. Specifically, a seed dictionary comprising 34 climate-related terms is employed to capture firms’ exposure to transition-related uncertainties. Corporate default risk is proxied by distance to default, following the simplified structural model of Bharath and Shumway (2008). We adopt a two-way fixed effects model controlling for both firm-specific and time-specific heterogeneity. The empirical results indicate that climate transition risk significantly increases corporate default risk. Specifically, transition risk is negatively associated with distance to default, suggesting that greater exposure to transition-related uncertainties erodes firms’ financial buffers and heightens default likelihood. This finding is robust across multiple specifications, including instrumental variable estimation using industry-level average transition risk, exclusion of the COVID-19 period (2013–2019), and the inclusion of additional financial controls. To further elucidate the underlying mechanisms, we examine the mediating role of corporate value, proxied by Tobin’s Q. The results show that climate transition risk exerts a significant negative effect on firm value, reflecting diminished profitability expectations and asset valuations under transition pressures. When corporate value is incorporated into the regression, it is positively associated with distance to default, while the direct effect of transition risk is attenuated, indicating a partial mediation effect. These findings suggest that climate transition risk increases default risk both directly and indirectly through the erosion of firm value. We further explore heterogeneity across firm characteristics and external environments. The adverse effect of transition risk is significantly more pronounced for small and medium-sized enterprises (SMEs) than for large firms, highlighting SMEs’ constraints in resources, technological capacity, and risk resilience. In addition, firms operating in high-carbon industries, such as manufacturing, energy production, construction, and transportation, experience a stronger increase in default risk, reflecting their greater exposure to regulatory pressures and transition costs. Regional analysis reveals that the effect is significant for firms located in eastern China but not for those in non-eastern regions, likely due to stricter environmental regulations and higher industrial concentration in more developed regions. In addition, moderation analysis identifies important mitigating factors. First, stronger corporate risk management capability, measured by the Z-score, significantly attenuates the adverse effect of transition risk on default risk, indicating that financially robust firms are better able to absorb transition-related shocks. Second, higher institutional investor ownership weakens the negative impact, suggesting that institutional investors serve as an effective external governance mechanism by enhancing monitoring, improving information efficiency, and facilitating firms’ strategic adjustments toward low-carbon transformation. This study contributes to the literature in several respects. First, it provides firm-level empirical evidence on the financial consequences of climate transition risk, extending prior research beyond macro-level analyses. Second, it identifies corporate value as a key transmission channel linking transition risk to default risk, thereby offering novel insights into the micro-level mechanisms of climate-related financial risk. Third, it highlights the moderating roles of risk management and institutional ownership, enriching understanding of how firms can mitigate transition-induced vulnerabilities. The findings also carry important policy and managerial implications. Policymakers should design differentiated support mechanisms for SMEs and high-carbon industries, strengthen climate-related information disclosure frameworks, and promote region-specific transition policies. Firms, in turn, should enhance internal risk management systems, improve value creation capabilities, proactively disclose transition strategies, and accelerate green transformation efforts. Overall, this study advances understanding of how climate transition risks propagate through firms to the broader financial system, offering important implications for achieving sustainable and financially resilient economic transitions.
By Yingying Huang; Harbin Institute of Technology    Honglei Yue
Presented by: Yingying Huang, Harbin Institute of Technology
3. Debt Type Matters? Loan Heterogeneity and Debt Overhang Abstract This paper examines how the composition of corporate liabilities shapes the severity of debt overhang. Using firm-level financial statements and detailed loan records from banks in Thailand from 2014 to 2019, we find robust evidence that leverage is negatively associated with subsequent firm investment, consistent with a symptom of the debt overhang. In addition, we find that debt overhang is more severe among small firms, young firms, firms with weaker debt-servicing capacity, as measured by the interest coverage ratio, and firms that rely more heavily on long-term liabilities. Bank loans are also associated with a larger overhang than non-bank debt. Among firms with bank loans, those that borrow from multiple banks suffer more severe debt overhang than single-lender firms. In summary, these results highlight that the structure of corporate liabilities, not merely the level of leverage, is central to understanding investment distortions arising from debt overhang.
By Archawa Paweenawat; Chulalongkorn Business School    Krislert Samphantharak; University of California San Diego    Don Tawanpitak; Puey Ungphakorn Institute for Economic Research
Presented by: Archawa Paweenawat, Chulalongkorn Business School
4. Labor Rights Protection and Corporate Innovation: Evidence from Chinese A-share Listed Companies Abstract Employees are the core actors in generating innovation output, and labor rights protection is an important institutional foundation that affects labor allocation efficiency and firms’ long-term sustainable development. Using data on Chinese A-share listed companies from 2012 to 2023, this paper systematically examines the impact of labor rights protection on corporate innovation and its underlying mechanisms. The results show that stronger labor rights protection significantly promotes corporate innovation output, with a more pronounced effect on invention patents. This conclusion remains valid after a series of robustness tests. Specifically, a one-point increase in the labor rights protection score is associated with an increase of approximately 0.7% in total patent applications and 0.9% in invention patent applications. Mechanism tests indicate that labor rights protection helps build harmonious and stable labor relations between firms and employees, enhances employee loyalty, and effectively reduces employee turnover. At the same time, stronger labor rights protection strengthens employees’ identification with and satisfaction toward the firm, stimulates the innovation motivation of knowledge workers, and releases the intrinsic potential of human capital, thereby continuously improving firms’ core technological capabilities and brand competitiveness. In addition, sound labor rights protection strengthens corporate social responsibility reputation and brand image, enhances the recognition and trust of trading partners, promotes market expansion and supply-chain diversification, and generates more stable demand expectations. These effects reduce business uncertainty, improve the predictability of returns to innovation investment, and provide a stable external market environment for sustained innovation. Heterogeneity analysis shows that the innovation-promoting effect of labor rights protection is more significant among non-high-tech firms, firms in moderately competitive industries, and firms located in low-wage regions. From the perspective of labor rights protection, this paper provides a systematic explanation of the internal mechanisms that drive corporate innovation and offers useful implications for improving corporate employee social security systems and building internal governance arrangements that incentivize innovation.
By Jiarong Li; Zhejiang University    Zhikai Wang; Zhejiang University
Presented by: Jiarong Li, Zhejiang University
Session 45: Labor III July 30, 2026 8:30 to 10:00 Location: Philippines Room (level 5)
Session Chair: Nopphol Witvorapong, Chulalongkorn University
Session type: invited
1. Assessment of Unemployment Benefits and Their Interaction with Redistributive Policies in Singapore Abstract Singapore has traditionally relied on self-sufficiency and means-tested support, with no unemployment benefits. However, rising economic volatility led to the introduction of the SkillsFuture Jobseeker Support Scheme (JSS) in 2025 which serves as a targeted unemployment assistance scheme. Alternative proposals such as the Workers’ Party’s Redundancy Insurance (WPRI) reflect a contrasting approach of universal, contributory unemployment insurance, and have sparked debate over the optimal design of unemployment support. This study employs a static microsimulation model to evaluate the redistributive and fiscal effects of JSS, WPRI, and a combined JSS–WPRI scheme. The study adapts the Commitment to Equity (CEQ) framework which evaluates how fiscal interventions affect income distributions through sequential application of taxes and transfers. Policy effectiveness is evaluated using the Gini coefficient, Concentration Index (CI), and Kakwani Index (KI), capturing overall income inequality, targeting, and progressivity. Fiscal outcomes are assessed through total programme expenditure, government fiscal exposure, and insurance contributions, enabling comparison of redistributive performance relative to fiscal costs. Our study finds that all three schemes reduce inequality, with the combined scheme achieving the greatest impact but at the highest fiscal cost, while JSS is the most progressive and least costly, and WPRI offers broader but less targeted support. Overall, the findings highlight a key trade-off between redistribution and fiscal cost, as more comprehensive schemes deliver greater inequality reduction but at higher fiscal costs. This study contributes to a deeper understanding of unemployment benefit design in Singapore and offer insights to inform policymakers in calibrating schemes that balance redistribution, efficiency, and fiscal sustainability.
By Amru Jaafar; Nanyang Technological University    Dason Yeo; Nanyang Technological University    Glendon Heng; Nanyang Technological University
Presented by: Glendon Heng, Nanyang Technological University
2. Skewed Sex Ratios and the Reversal of the Educational Gender Gap in China Abstract This paper examines how demographic shocks—specifically, the rise in male-biased sex ratios at birth—affect the educational attainment of boys and girls and drive the reversal of the gender gap in schooling in China. Using a shift–share instrumental variable design that interacts historical sex ratios with the diffusion of ultrasound technology, we find that higher male-biased sex ratios substantially slow the educational progress of boys relative to girls, even though education levels for both sexes have risen substantially in recent decades. Thus, the reversal of the gender gap arises not because girls advance faster under skewed sex ratios, but because boys’ educational gains are constrained by demographic pressures. Evidence points to three key mechanisms: male-dominated classroom environments, shifts in parental attitudes toward sons’ human-capital investment, and intensified marriage-market competition in adulthood. The effects are robust across alternative instruments and measures and are most pronounced in low-income regions, southern provinces, and households with multiple children.
By Siyu AI; The University of Western Australia    Simon Chang; The University of Western Australia
Presented by: Siyu AI, The University of Western Australia
3. Women’s Fertility Decision-Making in The Presence of Co-Wives: Evidence from Low and Middle Income Countries Abstract Existing studies have investigated the relationship between polygyny and fertility in polygynous societies and provided mixed results. Studies in non-polygynous societies are sparse and do not seem to explicitly investigate fertility decisions, focusing instead on how resources from the ‘main’ marriage are re-distributed in the presence of extramarital affairs. This study analyzed the extent to which women’s awareness that their husbands had other wives affected their decision to have children and the perceived birthweight of their last-born child, capturing the quantity and the quality dimensions of fertility decision-making respectively. Using data of 66,525 partnered or married women aged 15-49 from the Multiple Indicator Cluster Surveys in eight low and middle income countries, where polygyny was not legally recognized, multivariate probit regressions were performed. Results showed that the presence of co-wives was associated with an increase in the probability that women would decide to have children and a decrease in the probability that their last-born child would be perceived as regular-sized. The study provides evidence of co-wife rivalry that imposes an adverse effect on children’s health. It suggests that female empowerment strategies be more widely implemented so that women can make better-informed fertility and partner selection decisions.
By Nopphol Witvorapong; Chulalongkorn University
Presented by: Nopphol Witvorapong, Chulalongkorn University
Session 46: Public II July 30, 2026 8:30 to 10:00 Location: Vietnam Room (level 5)
Session Chair: Wing Thye Woo, University of California, Davis
Session type: invited
1. Role of central bank autonomy in climate change: A global perspective Abstract We examine the effects of central bank independence on carbon emissions and renewable energy consumption across 120 countries for the post-crisis period between 2010-2020. Our study has some significant contributions to the literature. Our results show that countries with higher central bank independence tend to have lower carbon emissions and higher renewable energy consumption and it is consistent across models employed. The baseline results hold true when we further explore the mechanisms and alternative scenarios. We examine the moderating effect of inflation on our climate sustainability and observe that countries with CBI and high inflation tend to have lower renewable energy consumption and higher emissions. Then, we examine how the interventions in climate related financial policies by the Central banks along with independence affect our sustainability measures. Finally, we explore the fiscal implications of central bank independence by checking the moderating effect of fiscal rules and CBI on climate response and outcome variables. We further decompose our results into OECD and non-OECD countries to examine the consistency of the results between the developed and less-developed economies. We use Driscoll–Kraay (1998) standard errors with fixed effects to address cross-sectional dependence for our fixed effects model (Hoechle, 2007), which we examine in Table 3. Further we use the dynamic panel method proposed by Blundell & Bond (1998) and Arellano & Bond (1991), popularly called the System GMM and Difference GMM methods to tackle endogeneity issues. By using the process of first-order differencing, the time invariant omitted variables are removed from the model and then lagged values of the endogenous variables are used as instruments for the differenced variables. Moreover, the dynamic models also help us to understand the persistence effect by evaluating the effect of lagged dependent variable. We further carry out robustness checks using an alternative panel corrected standard error model that helps to correct biased standard errors standard errors due to heteroskedasticity and contemporaneous correlation across panels.
By HIMADRI CHAKRABARTY
Presented by: HIMADRI CHAKRABARTY,
2. Profit Shifting and Firm Dynamics: Explaining the Selection into Tax Havens Abstract I develop a firm-dynamics model where heterogeneous firms pay a sunk cost to adopt tax-haven status and choose shifting intensity subject to a convex cost. The sunk cost generates a two-threshold band of inaction in adoption, and the convex cost yields a closed-form shifting schedule increasing in firm size. Aggregate revenue losses depend on the size composition of haven users, not only their number. Calibrated to 2019 U.S. data, the model implies that raising the adoption barrier (the BEPS margin) triggers an offsetting composition effect and leaves aggregate shifted profits nearly unchanged, whereas compressing the statutory tax differential works through the intensive margin and generates substantial fiscal effects. In a Stackelberg tax-competition game between a large home and a small haven, uncoordinated rate setting produces a welfare loss of approximately 7%, whereas a Pillar Two floor at 21% eliminates strategic undercutting and raises welfare by approximately 10%.
By Masakazu Emoto; Hitotsubashi University
Presented by: Masakazu Emoto, Hitotsubashi University
3. Formal Exit or Substantive Transformation? Regulatory-List Exit and Market-Oriented Transformation of China’s Local Government Financing Vehicles Abstract Whether local government financing vehicles (LGFVs) that exit the regulatory list truly achieve market-oriented transformation is central to evaluating the effectiveness of LGFVs governance. Using a sample of LGFVs from 2015 to 2024, we distinguish between formal exit and substantive exit. It then estimates a difference-in-differences model to examine how exit from the regulatory list affects market-oriented transformation. We measure transformation along four dimensions: income structure, cash flow structure, business structure, and equity structure. The results show that exit from the regulatory list promotes LGFVs market-oriented transformation overall, but the effect of substantive exit is much stronger than formal exit. Formal exit mainly reflects a change in regulatory status and has a limited effect on transformation. By contrast, substantive exit significantly improves LGFVs’ income sources, cash flow sources, business activities, and equity structure. Further analysis shows that the transformation effect is stronger in regions with higher marketization, greater fiscal pressure, and among platforms with better credit quality. These findings suggest that LGFVs governance should not focus only on list exit. Instead, it should follow the principle of “substance over form” and promote a real weakening of government financing functions and a stronger capacity for market-oriented operation.
By Min Liu; Nanchang University    Jun Fang; Nanchang University    CHIEN-CHIANG LEE; City University of Macau
Presented by: CHIEN-CHIANG LEE, City University of Macau
4. Governance Depth in Cross-Border Co-Production: Evidence from Chinese Family Firms in the Global South Abstract Multinational firms increasingly coordinate cross-border production through governance arrangements that fall between arm’s-length contracts and full ownership, yet they face persistent uncertainty over when to deepen commitment, retain flexibility, or withdraw from hybrid collaboration. Focusing on Chinese family firms operating in the Global South from 2008 to 2024, we distinguish among low-commitment contractual arrangements, intermediate hybrid co-production, and high-commitment ownership-based governance. We theorize how firm-level attributes—autonomy and modernization—shape governance depth through distinct control- and capability-based mechanisms, and how these effects are conditioned by organizational complexity, intergenerational governance, host-country institutional connectivity (participation in the Patent Cooperation Treaty and the Belt and Road Initiative), and geopolitical environments. Using a firm–host country–year panel of 80,3621 observations covering 2,668 Chinese family firms across 40 Global South economies, we show that governance depth does not increase monotonically with firm capability or external pressure. Instead, intermediate governance occupies a fragile middle ground that is easily undermined by coordination costs, while ownership-based co-production emerges only when internal governance and external institutions jointly support deeper control. By advancing a depth-based conception of international governance, this study extends internalization theory beyond binary entry modes, clarifies when family firms coordinate without owning, escalate to ownership, or retreat to arm’s-length collaboration, and differentiates institutional enablement from geopolitical constraint in shaping international governance choices.
By Yang Chen; Xi’an Jiaotong-Liverpool University
Presented by: Yang Chen, Xi’an Jiaotong-Liverpool University
Session 47: Technology and Innovation II - Agricultural July 30, 2026 8:30 to 10:00 Location: Brunei Room (level 5)
Session Chair: Jong-Wha Lee, Korea University
Session type: invited
1. The Impact of Digital Economy on the Resilience of Agricultural Product Supply Chains and Its Differential Analysis Abstract Abstract Against the backdrop of deep integration between the digital economy and agricultural modernization, the resilience of agricultural product supply chains has emerged as a core issue in safeguarding national food security and sustainable agricultural devel.The digital economy, empowered by technology, drives the extension, complementation, and strengthening of industrial chains as a pathway to hedge against and disperse potential risks in the agricultural industry chain.This study utilizes provincial panel data from China between 2011 and 2023, employing a two-way fixed effects model to empirically examine the causal effects and mechanisms of the digital economy on the resilience of agricultural product supply chains. First, this study constructs a digital economic development index from three dimensions: digital infrastructure, digital industrialization, and industrial digitization. The core indicators include internet broadband penetration rate, employment share in digital industries, e-commerce sales, etc; The evaluation system for agricultural product supply chain resilience is constructed from three aspects: resistance capacity, recovery capacity, and reorganization capacity, covering 15 indicators including agricultural machinery productivity, rural road network accessibility, and financial support for agriculture.The measurement using the entropy method reveals significant disparities in the level of digital economic development, with Guangdong ranking first nationwide, followed by Zhejiang and Jiangsu;In terms of agricultural product supply chain resilience, Shandong has the strongest comprehensive index performance, while major agricultural provinces like Henan and Sichuan also rank high in resilience levels. The uneven development among regions is notably evident. Then, a two-way fixed effects model was employed to verify the impact of the digital economy on the resilience of agricultural product supply chains.The results indicate that the development of the digital economy has a significant positive impact on the resilience of agricultural product supply chains,further research revealed that the number of rural broadband connections and the proportion of e-commerce transactions in agricultural products form a dual mediation pathway—with rural broadband connections serving as the "fundamental carrier,"enhancing the resilience of agricultural product supply chains by reducing connection costs through breaking information barriers; The proportion of e-commerce transaction value of agricultural products serves as a "distribution hub," improving resilience by streamlining distribution tiers and strengthening production-marketing coordination. Finally, when examining the differential impact of digital technologies on the resilience of agricultural product supply chains, the research findings indicate that the enabling effect of the digital economy is more pronounced in major production areas of fresh agricultural products, agricultural supply chain entities dominated by large agricultural enterprises/leading cooperatives, and non-major grain-producing regions, the differences stem from the structural divergence in the adaptability of digital technologies and the supply chain's capacity to accommodate them across varying scenarios. The conclusions of this study remain valid after conducting robustness tests using various methods, including alternative measures of core explanatory variables, the instrumental variable approach, and controlling for high-dimensional fixed effects.In conclusion, this study reveals the intrinsic logic and scenario differences of how the digital economy empowers the resilience of agricultural product supply chains, providing theoretical and practical foundations for policymakers to precisely deploy rural digital infrastructure, cultivate e-commerce ecosystems, and differentially enhance resilience.
By Hua Chunlin; Southwest university of science and technology    zhengxiaofei zheng
Presented by: zhengxiaofei zheng,
2. How Does Cooperation with New Agricultural Business Entities Affect Agricultural Income? An Information Acquisition Perspective Abstract During China's agricultural modernization transformation, traditional smallholder farmers face structural challenges, including small production scales, weak market linkage capacities, and low technological levels. New-type Agricultural Business Entities (NABEs) serve as a crucial bridge connecting smallholder farmers with modern agriculture, playing a key role in promoting agricultural industrialization and increasing farmers' income. However, the specific impact mechanisms of different types of cooperative entities and cooperation models on farmers' income have not been fully verified. This study employs survey data from 4,501 farm households collected across 79 cities in 23 provinces in China between 2022 and 2025. Using Propensity Score Matching (PSM), we empirically examine the causal effects of cooperation with NABEs on farmers' agricultural income and identify potential mechanisms through a bootstrap-based mediation effect model. The results indicate that establishing cooperative relationships with NABEs can significantly improve the agricultural income of traditional smallholder farmers. Specifically: (1) Cooperation with either farmers' professional cooperatives or agricultural enterprises has a significant positive impact on farmers' agricultural income; (2) In terms of cooperation models, compared to technical support, profit-sharing has the most significant effect on improving farmers' income, followed by the contract farming; (3) Mechanism testing reveals that online media information acquisition and agricultural technical training are two important transmission pathways through which NABE cooperation affects farmers' income. Cooperative relationships broaden farmers' information acquisition channels, enhance their grasp of market information and agricultural technology, and simultaneously improve farmers' production skills and business management capabilities through systematic training. This study confirms the important role of NABEs in driving income growth for smallholder farmers, providing micro-level empirical evidence for deepening the supply-side structural reform in agriculture. At the policy level, it is recommended to: (1) strengthen the cultivation and support of NABEs and improve the interest linkage mechanism between smallholder farmers and new-type business entities; (2) prioritize the promotion of stable and efficient cooperation models such as profit-sharing and contract farming to ensure certainty of farmers' production returns; (3) strengthen rural information infrastructure construction to enhance farmers' ability to obtain market and technical information through online media; (4) establish a normalized agricultural skills training system to enhance smallholder farmers' human capital accumulation and market adaptability. Through multidimensional policy coordination, promote the organic integration of traditional smallholder farmers into modern agricultural development, achieving the strategic goal of effectively linking smallholder farmers with modern agricultural practices.
By sun jingyu; Southwest university of science and technology    Hua Chunlin; Southwest university of science and technology
Presented by: sun jingyu, Southwest university of science and technology
3. Research on the Mechanism of Digital Inclusive Finance on Farmers' Income Growth from the Dual Perspective of External Activation and Internal Transformation Abstract In the context of the deep integration of the digital economy and rural revitalization, digital inclusive finance (DIF) is viewed as a vital institutional supply to alleviate rural financial exclusion and promote income growth. However, despite the comprehensive physical coverage of digital infrastructure, a structural paradox of "broad coverage without actual benefits" has emerged. Existing literature often treats the income-increasing effect of DIF as an unconditional linear process, overlooking the complex friction between "institutional supply" and "effective usage". This paper breaks through traditional frameworks to propose a "two-step mechanism" hypothesis: the functions of DIF are not realized automatically but must cross two thresholds—the "external activation" of the regional environment and the "internal transformation" of farmers and industries. We investigate the conditions under which DIF transforms into actual income and identify the hidden obstacles in this empowerment path. This paper constructs a theoretical logic framework of "external activation—internal transformation". The first step is the external activation path. As an intangible supply relying on the Internet, the primary premise for digital inclusive finance to play its role is the support of the regional digital environment (such as Internet penetration rate) and policy support. If the infrastructure is weak or policy support is insufficient, the dividends of digital finance are blocked at the starting point. Only by crossing specific thresholds can digital finance truly embed itself in farmers' production and lives, completing the "activation" from supply to usage. The second step is the internal capability transformation path. External activation only provides the possibility of income growth; whether it can ultimately be transformed into real income also depends on farmers' micro-absorptive capacity (education level, credit activity) and industrial carrying capacity (advanced industrial structure). If farmers lack the financial literacy to convert digital resources into production factors, or if rural areas lack modern agricultural industrial scenarios to undertake modern financial resources, even if digital finance is successfully activated, its income-increasing effect will still be weakened during the internal transformation stage. This paper selects panel data from 31 provinces and municipalities in China from 2011 to 2024, using farmers' per capita disposable income as the dependent variable and the Peking University Digital Financial Inclusion Index as the core independent variable. In terms of empirical strategy, this paper first constructs a two-way fixed effects model to examine the baseline effect under the full sample; secondly, to accurately identify the "activated" and "blocked" states, this paper introduces a three-way interaction model and the Hansen Panel Threshold Model to systematically investigate the conditional constraints and synergistic regulatory roles of multi-dimensional factors in the income-increasing effect of digital finance. The results reveal four critical insights: (1)Rejection of Unconditional Effects: The "full-sample average effect" in the baseline regression is non-significant, refuting the assumption of "unconditional income growth". This confirms that digital empowerment is highly dependent on environmental and conditional constraints; simple coverage does not guarantee growth. (2)Validation of External Activation: Internet penetration and policy support are core to activating dividends. Internet penetration exhibits a significant non-linear threshold effect (the technological activation point), while policy support serves as a positive moderator that optimizes the institutional environment. (3)Structural Constraints in Internal Transformation: Interestingly, traditional years of education show a weak moderating effect, revealing a "new digital divide" where general human capital does not automatically translate into digital financial literacy. Furthermore, the solidification of traditional agricultural structures limits the productive transformation of credit resources. (4)Synergistic Multiplier Effects: A significant synergistic effect exists between external and internal factors. Three-way interaction results confirm that farmers’ education levels only yield income multipliers when rural Internet infrastructure reaches a specific standard. Similarly, strong fiscal support ensures that financial resources flow into modern agriculture, achieving productive income growth. This highlights the interactive logic between environmental and capability dividends. This study offers a new perspective for optimizing rural DIF policies. First, policy focus must shift from "breadth of coverage" to the synergy between infrastructure and supply, prioritizing the "external activation" of rural digital infrastructure. Second, the "internal transformation" must be addressed by shifting from "giving fish" to "digital empowerment". This includes targeted digital financial literacy training and deepening agricultural industrial integration to provide high-value application scenarios for credit resources, thereby clearing the "last mile" of income growth. JEL codes: Q14 Keywords: Digital inclusive finance; Farmers' income growth; Three-way interaction; Mechanism research
By Yang Sijie; Southwest university of science and technology    Hua Chunlin; Southwest university of science and technology
Presented by: Yang Sijie, Southwest university of science and technology
4. A Costly Shortcut: Crop Residue Burning, Crop-Management Windows and Winter Wheat Yield Losses in China Abstract Crop residue burning offers farmers a quick way to clear fields under tight crop-management windows, but this shortcut may carry production costs. This paper estimates the relationship between residue burning and winter wheat yields in China’s Huang-Huai-Hai Plain, a major winter wheat–summer maize rotation system. We combine VIIRS active fire detections with 30 m winter wheat yield data to construct a 1 km grid-level panel for 2016–2021. The empirical design exploits changes in burning exposure within grids over time and differences across grids within the same county-year, while controlling for grid fixed effects, county-by-year fixed effects and grid-level climate conditions. Crop residue burning is associated with significantly lower winter wheat yields, with losses concentrated after wheat harvest and during maize harvest/wheat sowing–emergence. Irrigation capacity mitigates these losses, but county-level machinery power does not. Mechanism-consistent evidence links burning to lower surface soil moisture, higher vapor pressure deficit and weaker crop growth during wheat establishment. The findings suggest that burning may involve both external environmental costs and internal production costs, and that burning-control policies should address farmers’ need for timely residue-management services.
By Tuo Zhang; Southeast university
Presented by: Tuo Zhang, Southeast university
Session 48: Plenary: The Challenge of Declining Fertility Rates July 30, 2026 10:30 to 11:40 Location: Ballroom 1 (level 3)
Session Chair: Hal Hill, AO, ANU
Session type: plenary
Discussants:      Yasuyuki Sawada, University of Tokyo      Jong-Wha Lee, Korea University      Charles Yuji Horioka, Kobe University
Session 49: Asian III July 30, 2026 12:40 to 13:50 Location: Cambodia Room (level 5)
Session Chair: Hwee Kwan Chow, Singapore Management University
Session type: invited
1. RECONSTRUCTING THE NATIONAL ACCOUNTS OF A BRITISH COLONY: NEW GDP ESTIMATES FOR SINGAPORE, 1870–1900 Abstract In this article, the authors continue the work of Sugimoto, who reconstructed the GDP aggregates of Singapore for the early to middle twentieth century, which have been incorporated into the Maddison Project database. The same methodology and primary sources from the British archives are used, with appropriate modifications as required, to extend the national income series backward to 1870 using the expenditure approach. An analysis of these new estimates produces the following findings: (i) living standards showed a gradual but steady improvement over the late nineteenth century; (ii) the movements of real and nominal GDP diverged for most of the period; (iii) private consumption, investment, exports and imports were strongly procyclical and co-moved together; and (iv) economic growth was attended by recurrent fluctuations due to the volatility of the tin price. The margin of error of the GDP estimates is moderately low.
By Ichiro Sugimoto; Soka University    Keen Meng Choy; Soka University
Presented by: Ichiro Sugimoto, Soka University
2. Projecting Inflation Tail Risks in a Small Open Economy: Some Evidence from Singapore Abstract This study empirically assesses the drivers of risks to the inflation outlook for a small open economy like Singapore. We apply the inflation-at-risk framework of López-Salido and Loria (2020) and incorporate projections from the Survey of Professional Forecasters (SPF) as point forecasts of inflation. Our findings show that macro-financial risk factors—shaped by Singapore’s openness, role as a financial hub, and exchange rate–centered monetary policy framework—enter nonlinearly into inflation risk models and exert differentiated effects. Foreign price pressures heighten upside risks, and exchange rate policy has proven effective at mitigating them. Tighter global financial conditions amplify inflation risks through cost-push channels, whereas demand weakness produces only muted downside effects. We also record sharp gains in log predictive scores for one-quarter ahead conditional distributions relative to unconditional ones during the post-pandemic inflation surge. One-year-ahead predictive distributions become markedly right‑skewed ahead of the surge, effectively signalling a heightened probability of extreme inflation outcomes. Overall, incorporating inflation risk measures improves both the in-sample fit and the forecast accuracy of predictive distributions of inflation one and four quarters ahead, offering insights for central banks navigating uncertain global conditions.
By Hwee Kwan Chow; Singapore Management University    Jordan Lee; Singapore
Presented by: Hwee Kwan Chow, Singapore Management University
Session 50: Energy I July 30, 2026 12:40 to 13:50 Location: Singapore Room (level 5)
Session Chair: Youngho Chang, Singapore University of Social Sciences
Session type: invited
1. Renewable Portfolio Standards under the Grid Curtailment Binding Target and Solar Photovoltaics Deployment: Evidence from China’s Prefecture-level Data Abstract Although the installed capacity in China’s solar photovoltaics (PV) has grown significantly over the last two decades, this rapid growth was accompanied by persistently high grid curtailment rates. To address this issue, the 2018 Clean Energy Utilization Plan (hereafter, the Plan) proposed two constraints to promote the healthy growth of the solar PV industry in China. First, the Plan set a 95% minimum utilization binding target for the installed solar PV capacity for each province, which means the grid curtailment rates should be no higher than 5%. Second, under this grid curtailment binding target framework, the Plan also introduced provincial renewable portfolio standards (RPSs) to promote further development in renewable energy, particularly in solar PV and wind. In this paper, we evaluate how the RPSs under the grid curtailment binding target (hereafter, the RPSs-UGCBT) affect the solar PV deployment for China’s prefectures. Given that there are great heterogeneities in solar resource endowments, grid absorption capacities for renewable energy, and technological innovation level across China’s prefectures, these prefectures may respond differently to the RPSs-UCGBT. Employing China’s prefecture-level data from 2014 to 2022, we specify a difference-in-differences model to investigate the causal effects of the RPSs-UGCBT on the PV compliance behaviors. Specifically, we first identify a continuous treatment variable to measure the intensity of the RPSs-UCGBT for each prefecture, and then investigate how the RPSs-UCGBT induced China’s prefectures to use the density and size of solar PV projects to reduce the compliance costs of this policy. In addition, we also address the potential induced green technical changes of the RPSs-UCGBT and further examine how the green technical changes can serve as a mechanism to moderate the relationship between the policy intensities and the solar PV deployment. We find that the RPSs-UCGBT have significant causal effects on the density and size of solar PV projects. Our baseline specification shows that the prefecture would, on average, install 3.10% more solar PV capacities per square kilometer within each solar PV station when facing 10% more tightened treatment intensities. However, we find a significant negative treatment effect on the proportion of large-sized projects (capacities ≥ 50 MW), with a magnitude of approximately 3% for every 10% increase in treatment intensity, implying that prefectures with higher treatment intensities tended to install relatively more projects with capacities between 20 and 50 MW. These results, both in magnitude and significance, are robust to various controls, measures, and estimators. Moreover, we find that the RPSs-UCGBT have crowd out green innovations, with green patent applications declining by 3.1% for prefectures facing 10% higher treatment intensities. Heterogeneity analysis further reveals that prefectures with greater green patent stocks would depend less on the increase in the density of PV capacity within each solar PV station, suggesting that existing green innovation abilities may serve as an alternative compliance pathway and reduce the necessity for increasing the density of solar PV stations. This paper contributes to three aspects of the existing literature. First, it fills the gap of existing studies by addressing the effects of the RPSs on the density and size of solar PV projects. Most of the previous studies on the effects of the RPS system mainly focus on capacity installation, investment, productivity, market expansion, and quota design. Second, this paper explores the relationship between the RPSs-UCGBT and green innovations in China, providing empirical evidence on the literature of environmental regulations and innovations. Third, this paper sheds light on the mechanisms of the RPSs-UCGBT by analyzing the moderating role of the green innovation stocks. Keywords: Renewable Portfolio Standards, Solar PV Deployment, Curtailment Constraint, Green Innovation JEL: Q28, Q48, C54
By Antong Zhu; Zhejiang University    Zibing Zhang
Presented by: Antong Zhu, Zhejiang University
2. Towards sustainable future: Exploring the Evolution and Improvement Pathways of Provincial Energy Justice in China under Multiple Scenarios Abstract Abstract: As energy lies at the core of the Sustainable Development Goals, issues of energy justice have become increasingly important in research on energy transition. This study utilizes the GCAM-China to simulate four typical climate scenarios, namely SSP1-1.9, SSP2-4.5, SSP3-6.0, and SSP4-3.7, to systematically assess the level of energy justice at the provincial scale in China. Furthermore, it explores the response patterns of interprovincial energy justice under uncertain scenarios and effective pathways for improvement. The findings are as follows: (1) Over time, the provincial energy justice in China shows a gradual upward trend across all climate scenarios, with significant increases in inter-scenario disparities. The stricter the climate control target, the higher the level of regional energy justice development. Distributive justice dominates the overall energy justice framework, while restorative and recognition justice have substantial room for improvement; procedural justice remains at a relatively low level, representing a key bottleneck in optimizing energy justice. (2) Under conditions of uncertainty, the scenario response patterns of provincial energy justice can be classified into four categories based on energy justice levels and scenario sensitivity. All categories exhibit a response trend of SSP3-6.0 < SSP2-4.5 < SSP4-3.7 < SSP1-1.9. Furthermore, the higher the overall energy justice level within a category, the more pronounced the differentiation between scenarios; the lower the overall energy justice level within a category, the smaller the scenario differences. Meanwhile, the response patterns of provincial energy justice exhibit distinct temporal evolution patterns, generally following a developmental path of gradual progression from low levels and low sensitivity to high levels and strong sensitivity. (3) The number of synergistic correlations among energy justice indicators has increased significantly. Carbon taxes, equity in urban-rural energy consumption, and energy system management efficiency serve as key nodes for enhancing cross-dimensional synergistic interactions, while the strength of cross-dimensional synergistic links related to income equity has gradually weakened. The research findings provide quantitative evidence and decision-making references for the differentiated improvement of provincial-level energy justice in China under different climate scenarios, as well as for cross-regional energy equity governance and the coordinated advancement of climate goals. Keywords: energy justice; evolution type; cross-dimensional synergy; GCAM-China JEL Classification: O13; Q01; Q56
By Guoqing Li; China University of Mining and Technology    Feng Dong; Yanshan University
Presented by: Guoqing Li, China University of Mining and Technology
3. Price Stability and Market Efficiency: Perspectives from Singapore’s Electricity Market Abstract Singapore began deregulating its electricity market in 1998, establishing the National Electricity Market of Singapore (NEMS) as a competitive wholesale trading platform. Despite relatively concentrated generation, the market has broadly sustained competitive outcomes. Hedge contracts, regulatory constraints, and the threat of entry can effectively restrain market power and promote more competitive outcomes in electricity markets (Wolak, 2000; Wolfram, 1999). The vesting contract regime, introduced by the Energy Market Authority (EMA) on 1 January 2004, has been central to this result. Under the regime, each generation company (genco) hedges a mandated volume of output at an administered price derived from the long-run marginal cost (LRMC) of generation. By fixing a portion of output at a regulated price, the mechanism weakens gencos’ incentive to withhold capacity or inflate bids in order to raise the Uniform Singapore Energy Price (USEP). While the NEMS has become more efficient over time (Feng and Zhou, 2023), vesting contracts play a key role in constraining market power and lowering electricity prices (Chang, 2007). This study examines the effect of vesting contracts on market efficiency in Singapore, with attention to both the level and volatility of the USEP. The vesting price reflects several cost components, including fuel costs, capital expenditure, and operating expenses, all benchmarked to the LRMC. Because liquefied natural gas (LNG) is the dominant fuel for power generation in Singapore, the USEP tracks global LNG prices closely, leaving it exposed to external price shocks. The stabilisation role of vesting contracts is therefore of interest. During the 2022 global energy price spike, both USEP and vesting prices rose sharply, and their co-movement suggests that the vesting mechanism helped tie wholesale prices to underlying cost fundamentals even under extreme conditions. We estimate a time-series regression in which the USEP is modelled as a function of the LRMC-based vesting price, vesting quantity, and other explanatory variables. To evaluate the effect of vesting contracts on both the price level and price volatility, we employ a Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model. The GARCH specification allows the conditional variance of electricity prices to depend on past shocks and past variance, thereby capturing volatility clustering. Vesting quantity enters both the mean and variance equations, so that its influence on the price level and on volatility can be assessed jointly. We estimate all models by maximum likelihood under the Student-t distribution, which accommodates the fat tails commonly observed in electricity price data. Gaussian estimates are reported as a robustness check. We also estimate an Error Correction Model (ECM) to capture the long-run equilibrium and short-run adjustment dynamics between vesting price components and the USEP. The baseline regression and the ECM confirm that higher vesting quantities are associated with lower wholesale electricity prices, consistent with the view that vesting contracts constrain the exercise of market power. A negative deterministic trend emerges in both the baseline and ECM specifications, pointing to a structural decline in prices after controlling for observable fundamentals. The GARCH(1,1) estimates extend these findings to price volatility. In the mean equation, the coefficient on log vesting quantity is negative and statistically significant at the 1% level across all specifications, with the preferred Student-t estimate implying a reduction of approximately S$13.4/MWh in the USEP per unit increase. In the variance equation, lagged vesting quantity enters negatively and significantly, providing direct evidence that vesting contracts reduce the conditional volatility of electricity prices. Including vesting quantity and other fundamentals in the variance equation lowers volatility persistence relative to the baseline specification, though under the preferred Student-t distribution it remains high, suggesting that vesting moderates but does not eliminate volatility persistence. Besides, LNG prices emerge as a key external driver of price dynamics in both mean and variance equations, consistent with Singapore’s heavy reliance on imported gas for power generation. This study contributes to the literature by providing evidence on the joint effect of vesting contracts on both the level and volatility of electricity prices using a GARCH framework suited to the institutional setting of the NEMS. These findings have clear policy implications. Recent geopolitical tensions underscore the need to manage price stability in energy markets dependent on imported fossil fuels. Our results indicate that vesting contracts effectively restrain market power and dampen price volatility in a concentrated, gas-reliant electricity market. At the same time, their role should be assessed in the context of Singapore’s broader energy transition. As the market evolves, vesting contracts may need to be complemented by deeper financial hedging markets, greater renewable energy penetration, and strengthened carbon pricing.
By Shihao Zhou; Singapore University of Social Sciences    Youngho Chang; Singapore University of Social Sciences
Presented by: Shihao Zhou, Singapore University of Social Sciences
Session 51: Environmental IV July 30, 2026 12:40 to 13:50 Location: Thailand Room (level 5)
Session Chair: Guangzhi Ye, Nanyang Technological University, Singap
Session type: invited
1. Does ESG Pay When It Matters Most? Airline Governance and Resilience under Geopolitical Risk Abstract This study investigates how Environmental, Social, and Governance (ESG) disclosure quality and board governance influence the financial resilience of global airlines facing geopolitical and climate-related risks. Drawing on institutional, stakeholder, and resource-based theories, we apply fixed-effects panel regressions and Granger causality tests to 31 airlines (2017–2022). Results show no immediate profitability gains from stronger ESG scores or greater board diversity and independence. However, ESG maturity interacts positively with geopolitical risk, mitigating downside effects during volatility, and sustained improvements in ESG and governance yield higher long-term returns. These findings challenge the view that ESG ensures immediate gains, positioning ESG governance as a resilience capability and a strategic investment in long-term adaptability and tourism system stability under systemic shocks.
By Suliman Alshahmy; Heriot-Watt University Dubai Campus    Mehmet Sahiner; University of Dundee
Presented by: Suliman Alshahmy, Heriot-Watt University Dubai Campus
2. On value transfer influence on results from an integrated assessment model Abstract This paper examines the influence of income elasticity of the marginal willingness to pay (MWTP) on outputs from cost-benefit integrated assessment models (IAMs), a parameter rarely addressed. A life cycle impact assessment (LCIA) model in our IAM replaces damage functions in standard IAMs. The standard damage functions with ad-hoc given income elasticity parameters directly generate output losses from increasing global temperatures. In contrast, the LCIA model consists of two distinct parts: (1) the physical impact of climate and non-climate change and (2) the monetary valuation of impacts in terms of the MWTP based on large-scale, cross-country, heterogeneous stated-preference surveys, which enables us to apply benefit transfer techniques to the MWTPs in our IAM. We demonstrate that changes in greenhouse gas emissions, carbon prices, and output caused by the elasticity are comparable with those caused by the discount rate and risk aversion factor, suggesting the viability and feasibility of considering benefit transfers in climate change economics.
By KOJI TOKIMATSU; Tokyo Institute of Technology
Presented by: KOJI TOKIMATSU, Tokyo Institute of Technology
3. Environmental Policy Effectiveness under Alternative Monetary Policy Regimes in Small Open Economies Abstract This paper studies the interaction between environmental policy and monetary policy in a small open economy using a two-sector Environmental Dynamic Stochastic General Equilibrium (E-DSGE) model. The economy features a brown sector and a green sector and incorporates two widely used environmental policy instruments: a carbon tax and a cap-and-trade system. We embed this framework in a small open economy with alternative monetary policy and exchange rate regimes to examine how macroeconomic policy design affects the transmission and effectiveness of environmental regulation. We first characterize steady-state outcomes under varying degrees of carbon tax rates and cap-and-trade stringency, allowing for static comparisons across environmental policy instruments. We then study the dynamic responses of macroeconomic variables to productivity and monetary policy shocks under each environmental policy regime across four small open economy configurations. We conduct both static and dynamic welfare analyses to compare carbon taxation and cap-and-trade in open economies.
By Wenbo He; Nanyang Technological University    Guangzhi Ye; Nanyang Technological University, Singap
Presented by: Guangzhi Ye, Nanyang Technological University, Singap
Session 52: Industrial Organization II July 30, 2026 12:40 to 13:50 Location: Malaysia Room (level 5)
Session Chair: Jamus Lim, ESSEC Business School
Session type: invited
1. Entrepreneurial non-financial Capital, Sustainable business model Innovation, and Firm Value: Evidence from China's Manufacturing Sector Abstract Abstract: Against the backdrop of the global transition toward a green and low-carbon economy and China’s pursuit of high-quality development, the driving mechanism through which heterogeneous human capital factors influence micro-level enterprise value is undergoing profound restructuring. Departing from the traditional analytical paradigm centered on financial indicators, this study conceptualizes entrepreneurial traits as a form of entrepreneurial non-financial capital. Using balanced panel data from 1,179 manufacturing firms listed on the Shanghai and Shenzhen A-share markets over the period 2013–2022, and employing a two-way fixed-effects model, this paper systematically examines the impact of entrepreneurial non-financial capital on enterprise value. To ensure the rigor of causal identification, this study further employs the instrumental variable approach and the Heckman two-stage model to effectively mitigate potential endogeneity issues. The empirical results indicate that entrepreneurial non-financial capital significantly enhances enterprise value. Moreover, this driving effect exhibits stronger marginal contributions in firms located in the central and eastern regions, labor-intensive enterprises, and non-high-tech firms. Mechanism analysis further reveals that sustainable business model innovation plays a significant mediating role in this relationship, highlighting the micro-level logic through which entrepreneurial capital generates value by optimizing resource allocation and internalizing environmental externalities. Additional analysis shows that government subsidies, as an external institutional incentive, positively moderate this process by alleviating firms’ financing constraints. These findings provide empirical evidence for understanding the premium effects of intangible production factors in emerging economies and offer policy implications for improving the allocation efficiency of government subsidies and fostering high-level entrepreneurial talent. Keywords: Entrepreneurial non-financial capital; Enterprise value; Sustainable business model innovation; Government subsidies. JEL codes: C23; O31; H23; M14
By Yanhui Liu; Chongqing University    Pengcheng Xiang; Chongqing University
Presented by: Yanhui Liu, Chongqing University
2. National Logistics Hubs and the Geography of Supplier Networks:From a Market Integration Perspective Abstract We exploit China's National Logistics Hub (NLH) construction program as a quasi-natural experiment to identify how logistics infrastructure shapes the geographic scope of firm-level supplier networks. Using a multi-period difference-in-differences framework applied to 3,001 A-share firm-year observations from CSMAR supply chain disclosures spanning 2012--2024, we find that NLH designation expands firms' weighted-average supplier distance by approximately 117.7 km. The effect survives a battery of robustness checks and endogeneity corrections. Mechanism analysis reveals three complementary channels: (1) supplier substitution, in which firms replace nearby high-cost suppliers with remote low-cost ones (fixed matching-cost channel); (2) share concentration, in which purchasing share concentrates toward remote efficient suppliers (variable transport-cost channel); and (3) vertical disintegration, in which firms increase outsourcing of previously in-house inputs (make-or-buy boundary channel). We additionally document significant policy accumulation effects and spatial spillover effects of the NLH program. Heterogeneity analysis shows private firms, non-high-tech firms, and firms with higher intermediate input dependence or stronger supply chain risk perception exhibit larger treatment effects. At the city level, NLH construction raises both the breadth and intensity of cross-provincial procurement links. Hub complementarity estimates reveal differentiated coordination effects: Core-type and Regional-type hub pairs exhibit the strongest bilateral trade linkages, yet Regional hubs exert weaker trade-driving effects than their Core counterparts. JEL NO.H54, L23, D22
By Tian Luo; Renmin University of China
Presented by: Tian Luo, Renmin University of China
3. Inattention to market shrinkage: The case of the photo film market Abstract In the photo film market of the 2000s, Kodak's failure to sufficiently reduce production in response to market shrinkage has become a canonical example of how firms fail to adjust to market shrinkage. This seemingly optimistic response contrasts sharply with Fujifilm's response, which ultimately led it to exit the market successfully. To account for these contrasting cases, we incorporate the sparsity-based model of Gabaix (2014, 2019) into a textbook Cournot model in which firms are inattentive to changes in market size. We show that such inattention leads firms to respond optimistically to market shrinkage relative to the full-attention benchmark. We also show that a firm may respond pessimistically when its competitor is substantially inattentive. These results help explain Kodak's slow response and Fujifilm's relatively rapid adjustment to market shrinkage. Finally, we develop a model with endogenous attention choice, in which heterogeneity in forecast horizons and/or production cost structures generates heterogeneity in attention, a key driver of our results.
By Masataka Eguchi; Nagoya City University    Takayuki Tsuruga; The University of Osaka    Mai Yamada; Nihon University
Presented by: Masataka Eguchi, Nagoya City University
Session 53: International II - Growth July 30, 2026 12:40 to 13:50 Location: Indonesia Room (level 5)
Session Chair: Partha Sen, Delhi School of Economics
Session type: invited
1. Convergence under the Microscope Abstract This paper tests for convergence in establishment-size distributions across U.S. states. We document four facts about the nature and sources of this convergence. First, establishment-size distributions differed significantly across states in 1980 but have converged through 2019. This trend underlies a "duo-convergence": convergence in establishment-size distributions coincides with convergence in GDP per capita across states. Second, convergence has been highly uneven: the left tail drives the trend, whereas the right tail exhibits little systematic catch-up. Third, entry and exit rates show no convergence, but entrant sizes do. Fourth, initially poorer states experienced higher establishment employment growth. We highlight the implications of these micro-level facts for understanding cross-state differences in growth and examine what our evidence implies for policies aimed at achieving macro-level convergence.
By Yoshiki Ando; Singapore Management University    Joseph Hoon; National University of Singapore    Donghai Zhang; National University of Singapore
Presented by: Yoshiki Ando, Singapore Management University
2. Multinational Production, Comparative Advantage and Global Long-run Growth Abstract This paper examines how multinational production (MP) influences global long-run growth in a world where countries differ in innovation capacities and labor endowments. We develop an open-economy model of endogenous growth in which MP enables products invented in one country to be manufactured in another. MP breaks the link that causes manufacturing and research employment to move together in canonical endogenous growth models—a link that renders trade alone devoid of labor allocation effect and hence growth-neutral in the absence of knowledge spillovers effects. With both trade and MP, countries with a comparative advantage in innovation experience an increase in the global production of their domestically invented varieties relative to their domestic production, which raises the ratio of research to manufacturing employment; the opposite pattern arises in countries with a comparative disadvantage. This labor reallocation enhances the global efficiency of knowledge accumulation and increases the global long-run growth rate even when MP does not stimulate knowledge spillovers. We further show how the cross-country distribution of comparative advantage in innovation shapes the cross-country distributions of wages and intangible wealth, MP flows and internal income distribution. A numerical exercise suggests that eliminating MP would reduce the annual growth rate of global manufacturing output by approximately 0.15 percentage points.
By E. Young Song; Sogang University
Presented by: E. Young Song, Sogang University
3. Microfoundations of agglomeration economies in China's manufacturing industries Abstract This paper explores the microfoundations of agglomeration economies within China's manufacturing sectors by analyzing the industry-specific determinants of spatial clustering. Building on classical agglomeration theories, the study outlines key mechanisms such as knowledge spillovers, labor market pooling, and input sharing, which are examined through observable industry-specific characteristics, including innovation capacity, labor scale, and the structure of intermediate inputs. Additionally, variables related to the financing environment are incorporated, allowing for the integration of financial factors into a cohesive analytical framework. The research utilizes the Ellison–Glaeser (EG) index and a density-based index (DBI) to measure industrial agglomeration along two complementary dimensions: overall spatial concentration and localized clustering. The regression analysis investigates the relationship between industry characteristics and spatial agglomeration, thereby assessing the relative significance of different mechanisms in shaping agglomeration. The findings are expected to demonstrate that, in the context of China's manufacturing transformation, industrial agglomeration is linked not only to knowledge spillovers, labor market conditions, and economies of scale but also to financing conditions. By combining traditional agglomeration mechanisms with financial factors, this study offers new industry-specific empirical evidence on the operation of New Economic Geography theories in developing economies.
By QIANFEI SHU; Kansai Gaidai University    shengping Yang; Colorado State University-Pueblo
Presented by: QIANFEI SHU, Kansai Gaidai University
Session 54: Pandemic I July 30, 2026 12:40 to 13:50 Location: Philippines Room (level 5)
Session Chair: Tetsushi Sonobe, National Graduate Institute for Policy Studies (GRIPS)
Session type:
1. Optimal Lockdown Policy with Virus Mutation Abstract We examine the implications of virus mutation for optimal lockdown policy in an epi-macro model. We consider three ways of modelling mutation---one deterministic setup and two stochastic setups featuring a two-state and three-state Markov process. We find that the effects of mutation on optimal lockdown policy are asymmetric. In particular, a future reduction in the transmission rate increases lockdown intensity by more than a future rise in the transmission rate lowers it. As a corollary to this asymmetry, an increase in uncertainty about future mutation is non-neutral and reduces lockdown intensity under the optimal policy.
By Quentin Batista; MIT    Masakazu Emoto; Hitotsubashi University    Naoki Maezono; University of Tokyo    Taisuke Nakata; University of Tokyo
Presented by: Taisuke Nakata, University of Tokyo
2. Epidemic Risk and the Breakdown of Analyst Information Channels: Evidence from China’s Zero-COVID Policy Abstract This paper examines how regional epidemic risk during China’s COVID-19 Zero-COVID period affected financial analysts’ earnings forecast accuracy and related behaviors. Using analyst- and firm-level forecasts for A-share-listed firms from 2020–2021, we show that higher local epidemic risk significantly reduces forecast accuracy at both annual and quarterly horizons. Two mechanisms drive this decline. First, strict lockdowns and travel restrictions impede analysts’ ability to conduct on-site due diligence, with the adverse effects more pronounced for distant and out-of-province analysts. Second, heightened uncertainty and operational disruptions amplify information asymmetry, especially for non-SOEs, small firms, firms with greater earnings management, and firms audited by non-Big 4 auditors. Epidemic risk also reshapes analyst practices: it reduces coverage, increases forecast dispersion, raises the likelihood of forecast revisions, and encourages team collaboration as analysts attempt to mitigate informational frictions. Overall, the findings provide large-scale evidence that epidemic-induced disruptions fundamentally weakened analysts’ information sets and forecasting precision. The results highlight the vulnerability of capital-market information production to external shocks and underscore the importance of robust information channels when face-to-face information gathering becomes constrained.
By Sandy Suardi; University of Wollongong
Presented by: Sandy Suardi, University of Wollongong
Session 55: Political I July 30, 2026 12:40 to 13:50 Location: Brunei Room (level 5)
Session Chair: Bruno Dallago, University of Trento
Session type:
1. The Role of Political and Geopolitical Risks in Global IPOs Abstract The American Depositary Receipt (ADR) market experienced three booms in the mid-1980s, mid-1990s and post-2005, driven by issuers from advanced economies (AEs), emerging economies (EEs) and Mainland China, respectively. Using cross-sectional data in 1997, Doidge, Karolyi, and Stulz (2004) demonstrate a cross-listing premium for ADRs, arising from a “bonding" effect. From a longer and more recent panel of ADRs and their domestic peers, we find the ADR premium enjoyed by firms from EEs is significantly lower than that of AEs and may even become negative in some years. We extend the model of bonding theory to incorporate the effect of state expropriation as a form of political risk and geopolitical risk on controlling shareholder's cross-listing decision and firm's valuation. Testing the model using an endogenous treatment effect framework, we find country-specific persistent risk of state expropriation leads to a cross-listing discount. We also document how geopolitical risk further shapes cross-listing outcomes: US geopolitical risk reduces the benefits of listing in the US, whereas home-country geopolitical risk generates a flight-to-quality premium for ADRs.
By An Dong; Nanyang Technological University    Qu Feng; Nanyang Technological University, Singapore    Shang J Wei; Columbia University    Guiying Laura Wu; Nanyang Technological University
Presented by: An Dong, Nanyang Technological University
2. War and Human Capital Accumulation: Evidence from the Second Sino - Japanese War Abstract War losses are often geographically concentrated, but their long-run consequences depend on how states respond after conflict. We study this mechanism in the Sino-Japanese War by combining a new county-level measure of wartime loss, built from digitized individual martyr records in the national registry, with pooled microdata from the 1982, 1990, and 2000 Chinese population censuses. Our design is a cohort difference-in-differences that compares pre- and post-war birth cohorts across counties with different wartime-loss intensity. Post-war cohorts from higher-loss counties attain 0.09 to 0.16 additional years of schooling relative to comparable cohorts from lower-loss counties. The result is stable across treatment definitions, cutoff choices, historical county controls, and functional-form checks. The gains are concentrated at basic schooling margins and are larger in counties with weaker pre-war educational capacity. Mechanism evidence is consistent with a supply-side response through higher local education spending, alongside persistence in education-oriented values across generations.
By Jinyuan Liu; Renmin University of China    Yizheng Wang; Renmin University of China
Presented by: Jinyuan Liu, Renmin University of China
3. The WW2 Axis Occupation Legacy and Right-Wing Voting: Evidence from Slovenia Abstract Can past experiences with the WW2 Axis violence affect populist and right-wing voting today? In this paper, we offer a preliminary examination of the little-noticed variation in the Axis occupation regimes during WW2. Importantly for our study, the current Slovenian political parties are still associated with the opposing sides from the WW2. The Social Democrats, the major left-wing party, are the direct descendants of the Yugoslav Communists who led the armed resistance to the Axis occupation during the WW2. At the same time, the major right-wing populist party, the Slovenian Democratic Party, is often accused of glorifying the WW2 collaborators. Using geographical regression discontinuity design around the borders of former occupation zones, we show that residents of the areas exposed to a harsher regime under the Italian occupation are more likely to vote for left-wing parties and less likely to vote for right-wing parties. The potential for history-driven political mobilization is, however, limited due to lower turnout in the treated areas.
By Denis Ivanov; Shenzhen MSU-BIT University    Danil Medvedev; Independent Researcher    Rok Spruk; University of Ljubljana
Presented by: Denis Ivanov, Shenzhen MSU-BIT University
Session 56: AI and Digital Markets II July 30, 2026 12:40 to 13:50 Location: Vietnam Room (level 5)
Session Chair: Taojun Xie, Nanyang Technological University
Session type: invited
1. Coordination Failures in Digital Payment Adoption: Evidence from a Field Experiment in Pakistan Abstract Digital payment systems are widely recognized as a cornerstone of financial inclusion, yet adoption in developing economies such as Pakistan remains persistently low despite significant investments in infrastructure, including fast payment systems like Raast. This paper investigates the underlying barriers to digital payment adoption through a combination of descriptive analysis and a large-scale randomized controlled trial (RCT). Using data from 1,191 merchants and 1,189 households across 281 markets in Punjab, we document a striking gap between stated preferences and actual usage: while over 75% of merchants and 80% of households report valuing digital payments, cash continues to dominate everyday transactions. We identify a key mechanism driving this gap: a two-sided coordination failure rooted in systematic misperceptions. Merchants significantly underestimate customers’ willingness to pay digitally, while households similarly underestimate merchants’ readiness to accept digital payments. To test whether correcting these belief gaps can increase adoption, we implement three interventions: two-sided information provision, coordinated information (common knowledge), and financial incentives. The results show modest average effects. Information treatments increase passive adoption among merchants but reduce active promotion, while coordinated information yields negligible gains. Financial incentives also have limited impact, and no significant effects are observed on the household side. Heterogeneity analysis reveals that prior negative experiences—reported by a majority of merchants—substantially dampen treatment effects, and responses vary across sectors, with stronger impacts in high-value transaction environments such as electronics. Overall, the findings highlight that correcting informational frictions alone is insufficient to drive widespread adoption. Structural constraints—particularly trust, reliability, and dispute resolution—remain binding. The paper underscores the importance of a phased policy approach that prioritizes system reliability and trust-building before scaling informational or incentive-based interventions to unlock the full potential of digital payments in Pakistan.
By Kashif Malik; Lahore University of Management Sciences
Presented by: Kashif Malik, Lahore University of Management Sciences
2. Can Digital Technology Bridge the Enforcement Gap? The Impact of Smart Courts on Labor Protection Abstract This paper examines how digital technologies affect labor market outcomes through legal enforcement. Exploiting China’s Smart Courts reform as a quasi-natural experiment, we show that judicial digitalization significantly increases firms’ compliance with social insurance obligations, indicating stronger labor protection. Mechanism analysis reveals that these effects operate through improved judicial accessibility and efficiency. The impacts are more pronounced among firms and regions with weaker baseline labor protection, suggesting a compensatory role of digitalization. We further find that judicial digitalization complements market-based supervision, with stronger effects in firms subject to greater media attention and institutional investor monitoring. Finally, enhanced labor protection translates into higher firm productivity. Our findings highlight legal enforcement as a key institutional channel through which digital technologies shape labor market outcomes, complementing the existing production-based view.
By Shihe Liang; Xiamen University    bo ning; Xiamen University    Yue Pan; Xiamen University
Presented by: Shihe Liang, Xiamen University
3. Demographic Structure and Automation Adoption: Evidence from Local Labor Markets in Thailand Abstract For many economies, transition to automation has become a race against rapid population aging. This paper examines how spatial dynamics of population aging shape automation in Thailand. Using historical data at subdistrict (tambon) level, we analyze mean aging and aging trends influence automation adoption, automation intensity per worker, and share capital allocated to automation. Our empirical strategy combines double-selection LASSO approach to address high-dimensional confounding with spatial auto-regressive specification to account for geographic spillovers. We find demographic trends are more systematically related to automation out comes than static levels once spatial dependence is accounted for. These trends display nonlinear U-shaped relationship with automation intensity, with negative relationships at low levels of aging trends and positive relationships at higher levels. Patterns are het erogeneous across labor composition geography. Female-intensive firms show stronger increases in automation intensity and capital deepening, consistent with labor–capital substitution in routine-intensive production. Spatial heterogeneity is also pronounced: firms outside Bangkok and Eastern Economic Corridor respond more strongly to de mographic trends, whereas firms in Bangkok respond more strongly to levels of aging. Complementary panel evidence suggests aging operates through wages, skill com position, productivity, and capital intensity. Findings imply policy responses should be place-based, gender-sensitive, and targeted toward local labor markets demographic transition.
By Peerat Metta; National Statistical Office of Thailand    min Hein; Thammasat University
Presented by: Peerat Metta, National Statistical Office of Thailand
Session 57: AI and Digital Markets III July 30, 2026 14:00 to 15:30 Location: Singapore Room (level 5)
Session Chair: Erik Snowberg, The University of Utah
Session type: invited
1. AI as an Institutional Mediator: Navigating Institutional Pluralism in Sustainability-Driven Intrapreneurship Abstract Sustainability-driven intrapreneurs operate within complex organizational environments shaped by institutional pluralism, where economic, environmental, and social demands frequently conflict. These competing pressures require organizations to balance profitability with sustainability while maintaining legitimacy among diverse stakeholders. Although prior research highlights adaptive strategies such as bricolage and effectuation, the role of artificial intelligence (AI) in shaping intrapreneurial decision-making and innovation remains underexplored. This study develops a conceptual framework positioning AI as both a strategic enabler and an institutional mediator embedded within organizational decision-making and innovation processes, especially when it comes to navigating the dilemma of institutional pluralism. Drawing on institutional theory, stakeholder theory, dynamic capabilities, and actor-network theory, the paper argues that AI extends beyond a technical tool to support sense-making, multi-stakeholder interpretation, and opportunity recognition. The empirical component of this study draws on two sources of evidence (1) a CAWI survey of 22 MBA students and professionals at Nagoya University of Commerce and Business representing diverse international and industry backgrounds (2) a case study of ADNOC, a UAE-based energy company, based on semi-structured interviews and documentary analysis of company reports and website data. The research examines how AI functions within organizational contexts as an institutional mediator that empowers intrapreneurs to navigate institutional pluralism, enhance decision-making processes, and foster innovation. The findings indicate strong support for the role of AI as a mediating mechanism in enhancing decisions quality for addressing the profitability-environmental tension. Specifically, 68% of NUCB survey respondents agreed that AI can facilitate or resolve conflicts between economic and environmental objectives. Furthermore, the ADNOC case analysis revealed that AI implementation contributed to enhanced profitability, generated positive social outcomes, and reduced the company's carbon footprint. By integrating conceptual and empirical insights, this study contributes to management and entrepreneurship literature in several ways. First, it extends institutional theory by incorporating technological agency, positioning AI as an active participant in shaping organizational responses to institutional pressures. Second, it advances understanding of sustainability-driven intrapreneurship by highlighting how AI influences decision-making and innovation processes. Third, it offers a practical framework for organizations seeking to leverage AI not merely for efficiency, but as a strategic enabler of responsible and innovative growth. Finally, the study provides a foundation for future empirical research examining the conditions under which AI supports substantive versus symbolic sustainability outcomes, decision-making and sense-making within organizations in the process of building legitimacy.
By Mohamed Hegazy; Nagoya University of Commerce and Business    Hoe Chin Goi; NUCB Business School
Presented by: Mohamed Hegazy, Nagoya University of Commerce and Business
2. Generative AI Assistance and Conformity under System 1 Thinking Abstract This study examines whether assistance from generative AI systems affects individuals’ tendency to revise their judgments under System 1 thinking. We conduct a counting experiment in which participants are asked to report the number of objects presented in visual displays. Some displays contain objects arranged in a consistent and regular manner, whereas others contain irregular and uneven arrangements that make quick judgment more difficult. After giving an initial answer, participants are exposed either to assistance from generative AI systems or to human advice, and we then observe whether they revise their responses. The main finding is that assistance from generative AI systems makes participants more likely to change their answers when the objects are irregularly arranged. By contrast, this pattern is not observed when advice is provided by humans.
By Yasuhiro Nakamoto; Kansai University
Presented by: Yasuhiro Nakamoto, Kansai University
3. Simulating Analyst Forecast Behavior using LLMs Abstract Recent research finds that large language models (LLMs) can match or outperform professional forecasters on macroeconomic variables and predict the direction of firm earnings better than human analysts. These results raise a natural question: can LLMs also match analysts in the more demanding task of forecasting earnings per share (EPS) Existing evidence largely focuses on directional prediction, survey of macroeconomic forecasting exercises, but not on numerical EPS forecasting at the individual observation level. We examine this question using 121,369 paired analyst–LLM forecasts based on individual analyst EPS forecasts for 607 Korean listed firms over 2018–2025. For each analyst forecast, we generate a corresponding LLM forecast using only information that is publicly available as of the forecast date, including financial statements, macroeconomic conditions, historical EPS, the analyst’s own prior forecasts, and prevailing market consensus. External search is disabled to isolate the model’s intrinsic forecasting performance rather than its ability to retrieve additional information. Our objective is to assess whether commercially available, off-the-shelf LLMs can generate analyst-level forecasts without fine-tuning or parameter optimization. Accordingly, all API parameters are left at their default settings. We use GPT-5.4-nano as the primary model in the analyst–LLM comparison and GPT-4.1-nano as a benchmark in the model-advancement comparison. This design places analysts and the LLM in a common public-information environment and allows a direct comparison of their forecasts at the analyst–firm–date level. We assess relative forecast accuracy using matched analyst–LLM forecast pairs. We first compare forecast errors across forecast horizons, and test analyst superiority using a nonparametric paired rank test. We then examine heterogeneity in analyst superiority by regressing it on lagged firm characteristics, controlling for analyst, firm, and time fixed effects as well as forecast horizon. We find that human analysts outperform LLMs by around 20% overall, with median forecast errors of 1.9% of stock price for analysts and 2.3% for the LLM. Comparing the LLM with two natural benchmark forecasts included in the prompt, we find that it improves on the prevailing consensus but still falls short of analysts’ prior forecasts. This comparison is informative because both prior forecasts and consensus are natural anchors in an EPS setting, and both are explicitly available to the model in our prompt design. The analyst advantage over LLMs is highly heterogeneous across firms. It is larger for loss-making firms, firms with high analyst disagreement, and financially fragile firms with high leverage, but smaller for large, profitable, low-leverage firms where public information is richer and uncertainty is lower. This pattern suggests that LLMs are less effective in settings where public signals are noisier and the scope for analyst judgment is greater. The heterogeneity results are broadly similar across forecast horizons and remain especially strong for longer-horizon forecasts. We also compare two model generations under identical prompts. The newer model closes 68.1% of the overall gap relative to human analysts, indicating substantial improvement in model performance over a short period. A natural concern in this setting is that LLM forecasts may reflect retrieval of historical information or memorization of realized EPS rather than genuine forecasting. We address the first concern by disabling external search. To assess the second, we compare analyst superiority before and after each model’s training cutoff. If the model were simply recalling memorized outcomes, analyst superiority should decline sharply in observations more likely to fall within the training data. Instead, analyst superiority remains positive on both sides of the cutoff, and the differences across subsamples are small. These patterns provide little support for a large memorization-based explanation. Overall, our evidence shows that current commercial LLMs still underperform human analysts on average, even when given structured public information, prior analyst forecasts, and consensus benchmarks. However, two findings qualify this average underperformance: model performance improves substantially across generations, and LLMs perform relatively better for firms with richer public information and lower uncertainty. Given their lower cost, these results suggest greater potential for LLM use in such settings.
By Hyuk An; KDI School of Public Policy and Management    Seohyun Lee; KDI School of Public Policy and Management
Presented by: Hyuk An, KDI School of Public Policy and Management
4. Bytes Beyond Boundaries: Effects of Digitization on Innovation Abstract This paper examines how digital technology adoption affects firm innovation using comprehensive data on Chinese listed firms. We measure innovation with over three million patent records and capture digital adoption through textual analysis of annual reports from 2011 to 2022. Digital adoption significantly increases both the quantity and quality of innovation output. To address endogeneity, we employ a two-stage least squares strategy using annual report length and CEO IT background as instruments. We identify multiple mechanisms underlying this relationship. Digital adoption promotes R&D collaboration across organizational boundaries, as reflected in increased joint patenting, and expands firms’ access to external knowledge spillovers by enlarging effective knowledge pools in technology space. In addition, digital adoption improves R&D efficiency, enabling firms to generate more patent output per unit of R&D input. Finally, technology-specific evidence shows that communication, information collection, and analytics tools affect innovation through distinct channels. A difference-in-differences analysis exploiting the COVID-19 pandemic further corroborates these findings.
By Mengyuan CAI; Nanyang Technological University
Presented by: Mengyuan CAI, Nanyang Technological University
Session 58: Asian IV July 30, 2026 14:00 to 15:30 Location: Cambodia Room (level 5)
Session Chair: KOJI TOKIMATSU, Tokyo Institute of Technology
Session type: invited
1. Convergence in Energy and Carbon Intensity: A Decomposition Analysis of India and ASEAN Economies Abstract This paper examines the structural drivers of carbon emissions across India and ASEAN economies, with a particular focus on Singapore as a benchmark for energy efficiency and transition performance. While existing studies have analyzed the energy–environment nexus using either econometric or decomposition approaches, limited attention has been given to the convergence of underlying structural drivers of emissions, particularly in a comparative framework spanning South and Southeast Asia. To address this gap, the study integrates the decomposition analysis and convergence testing in a unified empirical setting. Using a balanced panel dataset of 11 countries over the period 2013–2024, the paper decomposes carbon emissions into key components, namely, economic scale, energy intensity, and carbon intensity, and subsequently examines whether the structural factors exhibit convergence across countries. The analysis employs a β-convergence models for energy and carbon intensity alongside LMDI (Log Mean Divisia Index) decomposition analysis. The results reveal distinct patterns of structural transformation. The findings underscore that aggregate convergence in emissions, may mask significant divergence in underlying structural drivers. By jointly analyzing decomposition and convergence, this study provides new insights into the dynamics of energy transition in emerging Asia. The paper contributes to the literature in three ways: first, by offering a comparative analysis of India and ASEAN economies; and second, by highlighting the importance of structural or efficiency convergence in energy and carbon intensity for achieving sustainable and low-carbon growth. The results carry important policy implications for designing targeted and region-specific energy transition strategies.
By Poulomi Bhattacharya; Indian Institute of Technology, Kanpur, India    Mousami Prasad; Indian Institute of Technology, Kanpur
Presented by: Poulomi Bhattacharya, Indian Institute of Technology, Kanpur, India
2. Firm-Level Asset Stranding Risk Perception: Text-Based Evidence from China’s Low-Carbon Transition Abstract As the low-carbon transition accelerates, stranded asset risk has become a key source of uncertainty in firms’ long-term decisions. Existing research emphasizes objective exposure and financial consequences but largely overlooks heterogeneity in managerial perceptions, even though firms’ responses depend on how such risks are perceived. This paper incorporates managerial risk perception into the analytical framework of stranded asset risk. Using 67,944 MD&A sections from Chinese listed firms’ annual reports, we apply deep learning algorithms to construct a Stranded Asset Risk Perception Index that integrates policy, technological, and market transition drivers while capturing managerial sentiment. We document substantial heterogeneity across time, regions, industries, and firms. Over time, perceived risk shifts from market-driven volatility to joint influence of policy and technological constraints. Spatially, risk perception exhibits a west–east gradient and is strongly associated with regional resource dependence, especially in areas under stricter environmental regulation and fiscal pressure. Across industries, high-carbon and financial sectors report higher perceived risk than low-carbon sectors, though within-industry dispersion remains notable. Firm-level evidence shows that state ownership, firm size, asset rigidity, and financial pressure significantly amplify managerial risk perception, whereas stronger market expectations and profitability partially mitigate it. Corporate governance plays a limited moderating role. By shifting focus from objective exposure to managerial cognition, this study provides novel insights into the microeconomic transmission of transition risk and its interaction with firm financial and governance structures, with implications for capital allocation, risk management, and strategic adaptation in the low-carbon transition.
By Ruoyang Pu; Beijing Institute of Technology
Presented by: Ruoyang Pu, Beijing Institute of Technology
3. Who Causes the Waste? Spatially Selective Tourism–Waste Generation in a Tourism-Led Growth City Abstract Tourism-led growth cities across developing Asia (Nguyen et al., 2025) share a repeated policy puzzle: whether the city's waste volumes rise directly with tourism expansion (Arbulú et al., 2015; Manomaivibool, 2015) or from the urban expansion that economic growth itself generates (Zhang et al., 2024; Pariatamby & Babel, 2023; Siddiqua et al., 2023) — yet the finding remains ambiguous. Two features in tourism-led growth city simultaneously press the stress on municipal waste systems in these destinations — visitors themselves, and the large, unregistered workforce (service staff, informal-sector labour, undocumented migrants) that tourism demand attracts but official registered statistics do not capture. Standard empirical studies, Standard empirical studies, which model provincial waste as a function of aggregate GDP or tourist arrivals, are incomplete. The consequence is a poorly identified elasticity that underlies most waste-infrastructure planning in tourism destination. This paper asks whether the observed tourism–waste linkage reflects the physical presence of visitors or the expansion residency side of the city. The study uses Phuket, Thailand, as a natural laboratory for tourism issues. Getis–Ord Gi* hotspot analysis on 2,796 accommodation and 183 attraction points-of-interest was used to classify the province into seven tourism-led-growth sub-district areas, nine residential sub-districts. Two disaggregated datasets were then constructed: an annual panel (1998–2025, N = 26) relating real tourism-sector value added (CVMs) to waste generation at each spatial layer, and a monthly panel (October 2015–December 2023, N = 99) relating tourist arrivals to the same spatial layers. The econometric pipeline applies Augmented Dickey–Fuller unit root tests, Johansen cointegration, vector error correction models, Dynamic OLS for long-run elasticities (Stock & Watson, 1993), and Toda–Yamamoto causality testing (1995). All series are I(1). Johansen tests find no cointegrating relationship between waste generation amount (ton) and waste at any spatial level, suggesting that aggregate economic expansion does not cause a stable long-run equilibrium with waste generation. However, pairwise Granger causality reveals strongly significant short-run transmission, a one side direction from economic expansion to total provincial waste (F = 14.29, p = 0.001) and to waste from 7 tourism sub-districts (F = 8.73, p = 0.008). The bidirectional pattern for residential waste is consistent with its role as a proxy for local population growth and urbanization (Khan et al., 2024; Siddiqua et al., 2023), while the unidirectional tourism–waste relationship is consistent with visitor flows being exogenously determined by origin-market factors rather than destination conditions (Saladié et al., 2020). In the direct measure of tourism pressure — waste and tourist arrivals —. Johansen testing identifies cointegration at the one percent level between arrivals and both total provincial waste (trace = 21.58) and tourism-area waste (trace = 26.17), but not between arrivals and residential waste (trace = 13.33). The spatial contrast answers the motivating question should the waste from residential areas co-move with tourist arrivals as worker households expand during peak seasons. It does not: residential waste is uncorrelated with arrivals at every frequency tested. The long-run equilibrium exists only sub districts where tourists physically concentrate, and the effect materialises contemporaneously — consistent with visitor-generated waste collected within the same reporting period, rather than a delayed demographic effect mediated by workforce housing. The paper therefore attributes the tourism–waste interaction primarily to visitors themselves. The paper contributes a methodological template — spatial disaggregation via hotspot analysis combined with two-frequency time-series econometrics — that addresses a known limitation of both macro panel studies (Arbulú et al., 2015; Greco et al., 2021) and micro island surveys (Mateu-Sbert et al., 2013; Saladié et al., 2020). Substantively, the findings from this present study imply that waste infrastructure planning in tourism-led growth cities should be spatially targeted to tourism districts, calibrated to arrival forecasts rather than population or regional or provincial economic growth projections, The findings generalise to other destination cities where tourism demand and unregistered labour presence are spatially and temporally entangled.
By Chayanon Phucharoen; Prince of Songkla University    Nichapat Sangkaew; Prince of Songkla University
Presented by: Chayanon Phucharoen, Prince of Songkla University
Session 59: Econometrics III July 30, 2026 14:00 to 15:30 Location: Thailand Room (level 5)
Session Chair: K.S. Jomo, Khazanah Research Institute
Session type: invited
1. News Shocks and Sudden Stops Abstract I examine the role of news shocks in causing Sudden Stops in emerging market economies. In a small open production economy with capital accumulation, a collateral constraint on borrowing creates a pecuniary externality that leads to overinvestment in good times and a Sudden Stop in some states. I introduce news shocks as signals about future TFP into this framework. I calibrate the model to data from Mexico, using text-based analysis of media articles and time-series analysis to identify news shocks. I show that news shocks increase the unconditional Sudden Stop probability from 4.5% to 5.3%. Without the corrective policy, news shocks can decrease welfare even though they provide additional, useful information. Incorrect positive news, where tomorrow's high productivity is unrealized, increases future binding constraint likelihood. News shocks require more active policy intervention to correct the externality, with a larger tax on borrowing in good times and greater subsidy during crises.
By Jin Lau; Marist University
Presented by: Jin Lau, Marist University
2. Climate Variability, Health Outcomes, and Health Care Utilization: Evidence from Indonesia Abstract Climate variability poses growing challenges to population health and health systems, particularly in developing countries where adaptive capacity remains limited. Deviations in local temperatures from their long-term climatic norms may adversely affect health and increase the demand for health care services, generating additional burdens for households and health systems. This study examines the effects of climate variability on health outcomes and health care utilization in Indonesia using nationally representative microdata from the National Socioeconomic Survey (SUSENAS) covering approximately 7.9 million individuals across 514 districts during 2018–2024. Climate variability is measured using temperature anomalies, defined as deviations of actual temperature from long-term monthly climatological averages. To account for differences in survey recall periods, one-month temperature anomalies are used for health complaints and outpatient care, while twelve-month exposure is used for inpatient hospitalization. The empirical analysis employs linear probability models with district and month-year fixed effects to exploit within-district variation over time while controlling for time-invariant regional characteristics and common shocks. Logit models with average marginal effects are estimated as robustness checks. The analysis further controls for individual characteristics, household conditions, and local climatic factors, including precipitation, relative humidity, and solar radiation. The results show that higher temperature anomalies significantly increase the probability of experiencing health complaints and utilizing outpatient care. In the preferred specification, a one-degree increase in temperature anomaly is associated with a 2.1 percentage-point increase in health complaints and a 1.1 percentage-point increase in outpatient care utilization. Positive effects are also observed for inpatient hospitalization, although the estimated magnitude is relatively small. Results from logit models yield qualitatively similar patterns, particularly for health complaints. These findings suggest that climate variability generates measurable pressures on population health and health care demand in Indonesia. The results highlight the importance of integrating climate-related risks into health system planning and adaptation policies to mitigate the economic consequences of increasing climate variability.
By Avina Kamilia; Universitas Gadjah Mada    Heni Wahyuni; Universitas Gadjah Mada
Presented by: Avina Kamilia, Universitas Gadjah Mada
3. Sovereign Credit Risk Comovement and Predictability During the U.S. Subprime Crisis: Evidence from Deep Learning Abstract This study examines the cross-country comovement and predictive relationships of U.S. sovereign credit risk and global sovereign credit default swap (CDS) spreads during the 2008 U.S. subprime mortgage crisis. To capture nonlinear and dynamic patterns, we employ deep learning models, including multilayer perceptron (MLP) and convolutional neural networks (CNN), to predict sovereign CDS movements for 61 countries. The results show that most countries exhibit positive comovement with U.S. sovereign risk. Under the MLP model, 77.05% of countries display positive correlations, while the CNN model slightly increases this proportion to 78.69%, indicating widespread global co-movement patterns. Stronger correlations are observed in financially integrated economies, whereas moderate and weak correlations reflect differences in financial openness and macroeconomic conditions. In contrast, several peripheral Eurozone countries exhibit negative correlations, suggesting a shift from global to domestic risk drivers, particularly in the context of the European sovereign debt crisis. Model comparisons further show that CNN outperforms MLP in most cases, highlighting the importance of nonlinearities and local temporal dynamics. Overall, deep learning models outperform traditional time-series approaches, demonstrating superior ability to capture complex and heterogeneous cross-market linkages. These findings suggest that global sovereign risk co-movements are nonlinear, heterogeneous, and time-varying, and that deep learning provides an effective framework for modeling systemic risk dynamics.
By Yi-Long Hsiao; National Dong Hwa University    Chien-Jung Ting; Southern Taiwan University of Science and Technology
Presented by: Chien-Jung Ting, Southern Taiwan University of Science and Technology
4. Robust Variance Estimation in Linear Regression: A Projection-Geometry Perspective Abstract Inference in linear regression relies on OLS residuals as proxies for unobserved errors in variance estimation. This proxy breaks down when the projection matrix exhibits non-negligible off-diagonal mass, so that residuals remain a mixture of errors even asymptotically. Such projection spillovers arise in empirically relevant settings including high-dimensional controls and multi-way fixed effects, where classical heteroskedasticity-robust (HC) and cluster-robust variance estimators (CRVE) discard first-order variance information and understate sampling uncertainty. We show that the variance of the OLS estimator admits an exact finite-sample representation as a Riesz functional of latent covariance blocks, with observable residual moments linked to this target through a linear operator determined by projection geometry. Variance estimation therefore reduces to a linear inverse problem. Within this framework, we propose the full Riesz estimator using both within- and cross-moments together with the full projection matrix, and the partial Riesz estimator restricting to within-moments while retaining full projection geometry. Classical HC and CRVE rely only on local projection information and can be viewed as approximations to the partial Riesz solution, with accuracy governed by projection spillovers. We provide an iterative algorithm that avoids matrix inversion and scales to large datasets. The resulting variance estimator is consistent and the corresponding t-statistics are asymptotically valid. Simulations show that classical estimators severely undercover under projection spillovers, while the proposed estimator restores nominal coverage.
By Yanping Chen; Indiana University Bloomington
Presented by: Yanping Chen, Indiana University Bloomington
Session 60: Environmental V July 30, 2026 14:00 to 15:30 Location: Malaysia Room (level 5)
Session Chair: Guangzhi Ye, Nanyang Technological University, Singap
Session type: invited
1. Carbon Pricing Intensivising Energy Transition in Electricity Market Abstract Carbon pricing has become a central policy instrument for reducing greenhouse gas (GHG) emissions and promoting low-carbon investment. Emissions trading systems (ETSs), such as the European Union Emissions Trading System (EU ETS), are often valued for their cost-effectiveness and flexibility, as they allow the carbon price to be determined by the market. However, concerns remain over price volatility and the possibility that prices may be too low to provide stable long-term incentives for decarbonization. In response, some jurisdictions, including the United Kingdom, Germany, and Canada, have adopted hybrid carbon pricing approaches that combine emissions trading with carbon taxes or price floors. The power sector is a particularly important setting for evaluating the effectiveness of such policies. As one of the largest sources of emissions, it has been a primary target of carbon pricing and is also central to broader energy transition strategies. Policy-induced changes in the power sector can generate not only direct emissions reductions but also structural shifts in the energy mix, including the phase-out of coal and expansion of renewable electricity. Studying these effects can therefore provide broader insights into how carbon pricing supports decarbonization in practice. This study examines the United Kingdom’s experience with hybrid carbon pricing in the power sector. The UK provides a useful case because it combined participation in the EU ETS with an additional domestic carbon tax instrument, the Carbon Price Floor (CPF), introduced in 2013. Within the CPF framework, the Carbon Price Support (CPS) raised the effective carbon price faced by fossil fuel power generation. The policy was introduced partly to address the weakness of EU ETS prices at the time and to strengthen incentives for cleaner electricity generation. Since then, the UK power sector has undergone a substantial transition, including a sharp decline in coal use and a rapid increase in low-carbon generation. Against this background, this paper evaluates whether the UK’s hybrid carbon pricing framework contributed to emissions reductions and power sector transition. Focusing on the CPS as the key policy intervention, we assess its impact on overall emissions, power sector emissions, and changes in the electricity system. By doing so, the study contributes empirical evidence on whether combining an ETS with a carbon tax can enhance policy effectiveness. The findings are relevant not only for understanding the UK case, but also for informing policymakers in other jurisdictions that are considering stronger or more stable carbon pricing frameworks.
By HONGYAN LI; National University of Singapore
Presented by: HONGYAN LI, National University of Singapore
2. Behavioral Forces in Green Finance_ Mapping Sentiment and Contagion in Chinese Green Bonds Abstract This study identifies and analyses the impact of individual and institutional investors’ sentiment as well as their contagion on the green bond market performance in China, covering the period from July 1, 2016, to December 31, 2025. We conduct our research by applying GARCH-mixed data sampling (MIDAS), Quantile-on-Quantile (QQ), and time-varying parameter vector autoregression (TVP-VAR) regression techniques. Our empirical results reveal the significant role of both individual and institutional investors’ sentiment together with their spillovers in enhancing the performance of the Chinese green bond market. Our research findings contribute to the growing body of literature on sustainable and behavioural finance. It also offers valuable policy implications and investment strategies to green bond regulators and investors across countries.
By Thuy Duong Le; Murdoch Univesity    Ariful Hoque; Murdoch Univesity    Thi Le; Murdoch Univesity
Presented by: Thuy Duong Le, Murdoch Univesity
3. Does Environmental Information Provision Deliver? Experimental Evidence from Chinese Schools Abstract Public provision of environmental information is becoming prevalent worldwide to promote public awareness of environmental risks to protect health, but there is a lack of causal evidence on its effectiveness. This study examines how the provision of air quality information affects the behaviors, health, and academic performance of students in Chinese secondary schools, who are at a critical stage of human capital cumulation with significant mental challenges and susceptibility to air pollution. We conduct a large-scale experiment which randomly selects over 16,000 students into multiple interventions, including information on ambient air pollution, advisories on defensive measures, and their respective effects. Students do not respond to information on pollution or its mortality impacts. In sharp contrast, information on the adverse impact of air pollution on test scores with behavioral advisories triggers a 2pp increase in air purifier adoption at home within one month. Importantly, the advisories on defensive measures offer a critical choice set, without which students will only close the window, which is much less effective than an air purifier. Furthermore, air purifier adoption improves the mental health of students and math scores. The findings provide novel measurements on the willingness to pay for clean air for the understudied adolescents and their parents, offer useful insights into information provision, risk perceptions and behaviors, and highlight the importance of tailored behavioral advisories in ensuring the effectiveness of information programs on air quality and beyond.
By Tong Liu; National University of Singapore
Presented by: Tong Liu, National University of Singapore
4. Diagnostic Expectations and Carbon Taxation: Amplification, Allocation, and Welfare in a Two-Sector DSGE Model Abstract This paper studies how diagnostic expectations change the transmission of carbon taxation in a two-sector New Keynesian environmental DSGE model. Relative to the rational-expectations benchmark, diagnostic expectations generate stronger short-run overreaction and more persistent adjustment following productivity and monetary policy shocks. Quantitatively, we identify two distinct transmission mechanisms. Distorted consumption expectations primarily amplify aggregate and sectoral fluctuations, while distorted pricing expectations primarily reshape brown-green allocation by strengthening relative-price adjustment and expenditure switching toward the green sector. These effects become larger as the carbon tax rises. We further show that diagnostic expectations increase transition welfare losses at all tax rates considered. A welfare decomposition reveals that the additional welfare cost is driven mainly by the consumption channel, even though the pricing channel is central for sectoral reallocation. The results imply that expectation distortions affect environmental policy through separate amplification and allocation margins, and that ignoring these margins understates the transition costs of carbon taxation. JEL Classification: E32, E50, E70, Q58 Keywords: Green Transitions, Behavioral Expectations, Environmental Policy, Monetary Policy, Macroeconomic Dynamics
By Wenbo He; Nanyang Technological University    Guangzhi Ye; Nanyang Technological University
Presented by: Wenbo He, Nanyang Technological University
Session 61: Empirical II July 30, 2026 14:00 to 15:30 Location: Indonesia Room (level 5)
Session Chair: James Forder, Balliol College Oxford
Session type: invited
1. Cannibalizing the Carnival: How Tiered Commissions Crowd Out Platform-Wide Promotions Abstract Digital platforms generally manage sellers through interconnected rules instead of separate tools. However, research has mainly treated commission structures and platform promotions as distinct areas. This separation hides a key governance issue: a platform can set a new fee structure for all sellers, but often cannot force sellers to join voluntary promotional programs. Consequently, a change in a mandatory policy can influence the benefits of choosing a voluntary program. We explore this policy interaction in Steam’s late-2018 shift from a flat 30% commission to a tiered revenue-sharing system and how it impacted developers’ participation in Steam’s major seasonal sales. Steam is a good case because the commission change was platform-wide and driven by outside pressure, while participation in seasonal sales was voluntary. The reform reduced the commission rate only after a game reached certain revenue milestones, benefiting high-revenue titles by increasing their margins while smaller games continued to pay the standard 30%. This creates conflicting incentives within a shared promotional event: large titles can scale more easily, while smaller titles may see less appeal in deep discounts once market conditions shift. We assemble a panel of 14,487 game-season observations spanning 2016 to 2021 and combine descriptive evidence with fixed-effects difference-in-differences models. The descriptive series shows a clear drop in sales participation following the reform. In our preferred specifications, the reform reduces the likelihood of a game participating in a major seasonal sale by about 5.3 to 5.5 percentage points, compared to a mean participation rate of 62.8%. The impact is highly uneven, mainly affecting younger titles, indie games, and games with revenue below $10 million. Valve’s own titles show no similar decline, and high-revenue titles experience no significant reduction in participation. Overall, these patterns suggest that the negative effect is primarily driven by the withdrawal of the long tail rather than an overall collapse in platform-wide promotions. The evidence aligns with a cross-policy externality. Once tiered commissions increased the effective margin advantage of top sellers, major sales became less appealing to smaller developers. Some likely faced a threshold effect, where high-revenue games could discount more heavily without sacrificing margins to the same extent. Others probably experienced competitive traffic siphoning: as leading titles ramped up their promotional efforts, smaller games lost the marginal, price-sensitive consumers who make discounting profitable. In this context, nonparticipation becomes a rational choice rather than a sign of seller passivity. The paper contributes to research on platform governance, digital promotions, and marketplace design. Conceptually, it demonstrates that seller behavior on a voluntary level cannot be understood without considering the platform’s mandatory policy package. Empirically, it offers quasi-experimental evidence that fee reforms can discourage participation in a separate promotional institution. Managerially, it indicates that platforms aiming to keep blockbuster titles through targeted fee cuts might unintentionally reduce long-tail participation and marketplace diversity unless they explicitly create compensating mechanisms for smaller sellers.
By Pu Zhao; Boston University    Xintong Han; Laval University    Junnan HE; Sciences Po
Presented by: Xintong Han, Laval University
2. Information Constraints and Cross-Sectional Interest Elasticity of Household Cash Holdings Abstract This paper examines how information constraints shape the cross-sectional relationship between deposit interest rates and household cash holdings in Japan. Mulligan and Sala-i-Martin (2000) interpret cross-sectional interest elasticity as reflecting the extensive-margin adoption of interest-bearing financial technologies. This mechanism is less central in Japan, where basic interest-bearing deposit accounts are already widely adopted. Using household survey data that report cash holdings, total financial assets, perceived deposit rates, and subjective assessments of cash ratios, we examine whether cross-sectional interest elasticity reflects information constraints and portfolio awareness rather than financial technology adoption alone. We classify households according to whether their subjective cash-ratio assessments are consistent with the ranges implied by their reported asset holdings. This classification yields three groups: correct respondents, incorrect respondents, and indeterminable respondents. Among the indeterminable group, a subset has observed cash holdings and total financial assets but missing subjective ratios; these households enter the regression sample as unknown respondents. The results show that cross-sectional interest elasticity differs sharply across these information groups. Among correct respondents, whose subjective and objective cash ratios are consistent, the estimated coefficient is small in magnitude and statistically insignificant in the baseline OLS specification, consistent with the prediction that money demand is weakly interest-sensitive in a low-interest-rate environment. In contrast, incorrect respondents, who misperceive their portfolio composition, exhibit a negative relationship between deposit interest rates and cash ratios. Unknown respondents also display near-zero elasticity, consistent with limited information about their own portfolio allocation. These findings suggest that cross-sectional interest elasticity in Japan reflects heterogeneity in financial information and portfolio awareness rather than a uniform behavioral response to interest-rate differences. More broadly, the results show that information constraints can shape household portfolio adjustment even after basic interest-bearing financial technologies have been adopted. The transmission of monetary policy through household portfolio reallocation may therefore depend not only on interest rates themselves, but also on households’ awareness of those rates and of their own asset allocation.
By Hiroshi Fujiki; Chuo University
Presented by: Hiroshi Fujiki, Chuo University
3. What is the difference between a “vertical” and an “expectations augmented” Phillips curve? Abstract In the consensus economics of the 1980s and after, the “vertical” and “expectations augmented” Phillips curves are very much the same thing. It is shown that the expressions emerged in quite different contexts. The language of the “vertical Phillips curve” originates in the American literature of the early 1970s, reflecting econometric investigation of the change in the inflation-unemployment relationship of the preceding decades. The “expectations augmented Phillips curve” was a term coined by British monetarists in 1973 in making their argument against cost-push explanations of inflation. It was didactic, and argumentative, rather than econometric, and was designed to counter the view of the British Keynesians that no “Phillips curve” of any kind existed. When consensus emerged, the two terms came to be used interchangeably.
By James Forder; Balliol College Oxford
Presented by: James Forder, Balliol College Oxford
Session 62: Energy II July 30, 2026 14:00 to 15:30 Location: Philippines Room (level 5)
Session Chair: Yasuyuki Sawada, University of Tokyo
Session type: invited
1. Shadows in the Sunlight: Do Solar Power’s Benefits Shine Equally on Everyone? Abstract This study investigates the structural inequities embedded within the allocation of non-refundable energy tax credits in the U.S. residential solar market. By analyzing tax credit data from the Internal Revenue Service (IRS) alongside individual-level data from the Annual Social and Economic Supplements (ASEC), we reveal a significant 74\% discrepancy in tax credit utilization between low- and higher-income households. Additionally, we find that 28\% of homeowner households are ineligible for full solar tax credits due to tax liability constraints. Using a structural model of household solar panel adoption that incorporates tax benefits, this research quantifies the adverse impacts of current tax policies. Through counterfactual scenarios, we demonstrate that making tax credits refundable could increase adoption rates by 23.8\% overall, effectively doubling the number of solar panel systems among the most economically vulnerable populations. Furthermore, our evidence shows that refundability could lead to a significant 8\% reduction in emissions, including CO2, SO2, NOx, and PM2.5. These findings underscore the need for policymakers to restructure energy tax credits to bridge the socioeconomic divide, thereby accelerating the transition towards a more sustainable and equitable energy system.
By Huiqi Zhuang; Nankai University
Presented by: Huiqi Zhuang, Nankai University
2. The impact of digital transformation on energy common prosperity in China Abstract With the accelerating pace of worldwide digitalization, how digital transformation affects the process of energy common prosperity (ECP) deserves special attention. We first constructed a comprehensive indicator system for the assessment of ECP in China and further examined the potential impacts of digital transformation on ECP for the first time in this study. The influencing mechanisms of digital transformation on ECP and the regional heterogeneity of this impact are also have been discussed. The main findings are as follows: (1) The comprehensive index of ECP shows significantly increasing trend over 2013-2022. From regional insights, the eastern coastal region exhibited the highest index of ECP than the central and western inland regions of China. (2) Digital transformation can advance ECP significantly, to be specific, a 1% increase in the level of digital transformation will lead to an advancement in ECP by 0.024%. (3) Digital transformation indirectly promotes ECP through mechanisms such as improving energy infrastructure, creating income growth effect, enhancing energy efficiency and energy management capacity. (4) There exists significant heterogeneity in the impact of digital transformation on ECP. Specifically, in regions with higher levels of digital transformation and ECP, the digital transformation has a considerably greater influence on the promotion of ECP. Finally, we highlight some policy implications based on the key findings of this study.
By Maliyamu Abudureheman; Xinjiang University    Cong Dong; University of International Business and Economics
Presented by: Cong Dong, University of International Business and Economics
3. Determinants of Renewable Energy Transition: The Role of Economic Development, Financial Systems, Institutional Quality, and Energy Security Abstract The transition toward renewable energy has become a central component of global efforts to reduce greenhouse gas emissions, strengthen energy security, and promote sustainable development. Despite rapid progress in renewable energy deployment, the pace and scale of adoption differ substantially across countries. Understanding the structural determinants of renewable energy transition is therefore essential for designing effective energy and climate policies. This study investigates the economic, financial, institutional, and energy-related factors that influence renewable energy transition using an unbalanced panel of 24 countries over the period 2005–2021. The analysis examines the effects of economic development, financial development, government effectiveness, energy import dependence, and carbon intensity on renewable energy consumption. The empirical framework also controls for fossil fuel consumption, trade openness, and inflation in order to account for broader macroeconomic and energy system conditions. The study employs a multi-stage econometric strategy. Baseline estimates are obtained using fixed effects and random effects models to control for unobserved country heterogeneity. Robust inference is then ensured through heteroskedasticity-robust and Driscoll–Kraay estimators. To address potential endogeneity and dynamic persistence in renewable energy adoption, the analysis further applies dynamic panel estimation using Difference GMM and System GMM. In addition, the robustness of the findings is examined using renewable electricity generation as an alternative dependent variable. The empirical results show that carbon intensity of GDP consistently exerts a strong negative effect on renewable energy transition, while energy import dependence generally promotes renewable energy adoption, reflecting the importance of energy security considerations. Financial development supports renewable energy expansion in the baseline models, although its effect weakens in some dynamic specifications. Institutional quality also matters, particularly in robust estimations using alternative measures of renewable energy transition. Overall, the findings suggest that renewable energy transition is shaped by a combination of environmental pressure, energy security concerns, financial capacity, and institutional conditions. This study contributes to the literature by integrating economic, financial, institutional, and energy-related determinants within a unified panel framework and by employing multiple econometric approaches to ensure robust inference. The results offer important policy insights for governments seeking to accelerate renewable energy deployment and support long-term low-carbon development.
By MOHD AFJAL; Al Qasimia University
Presented by: MOHD AFJAL, Al Qasimia University
4. Threshold Incentives and Solar PV Capacity Choice in South Korea Abstract Introduction Korea has used several policies to support renewable energy, including K-FITS, which supports small solar projects through a fixed-price contract. The policy is intended to reduce revenue uncertainty and ease entry for small producers that may face higher financing costs, greater market risk, and higher transaction costs. At the same time, its clear size threshold may create distortions by encouraging developers to keep projects just below the cutoff rather than choose the most efficient size. This concern is important in Korea because recent evidence suggests that smaller solar projects tend to have higher unit installation costs than larger ones (Korea Energy Economics Institute, 2025). Thus, the key policy question is not only whether K-FITS increased solar capacity, but also whether it did so in a cost-effective way. This paper asks a simple question: did the 100 kW threshold in K-FITS increase solar deployment in a cost-effective way? Even if the policy increased capacity in the targeted segment, that does not automatically mean it was an efficient way to reduce carbon emissions. A policy can raise installed capacity but still be costly if it supports projects that are too small, if it causes firms to change project size only to qualify for support, or if the same emissions reductions could have been achieved more cheaply through other instruments or larger projects. This question matters in Korea, where renewable expansion must take place under fiscal, spatial, and political limits. Existing Korean studies provide important background on the broader policy environment, including the interaction between the RPS, auctions, and feed-in tariffs (Kwon, 2018, 2020), the design and sustainability of the RPS (Lee and Seo, 2019), alternative renewable policy tools in Korea’s electricity market (Kim, 2019), and the feasibility or social acceptance of distributed solar investment (Lee, Huh and Yoo, 2018; Koo, 2017; Chung, 2020). Recent Korean research also shows that small-solar projects under the Korean FIT tend to have higher unit installation costs (Korea Energy Economics Institute, 2025). However, there is still limited ex post evidence on whether the 100 kW K-FITS threshold generated enough additional solar capacity to justify its cost, and whether the response came from genuine new entry, strategic downsizing, or a combination of both. Method & Results This study uses a Difference-in-Differences approach with a district-year-group panel to examine how K-FIT changed installation outcomes for solar systems below 100 kW, compared with a nearby comparison group. The linear results show that, after the policy, the below-100 kW group had a larger increase than the comparison group. In the baseline estimates, the number of installations increased by about 4.8 more units, and installed capacity increased by about 167 kW more. In the models with additional interaction controls, the results are very similar: the estimated increase is about 4.84 more installations and about 169 kW more capacity. The results also suggest that the increase was stronger in places with a higher share of farmland. At the same time, the full set of results suggests a careful interpretation. In the Poisson model, the estimated policy effect is negative, and the logit model also suggests that the probability of having any installation became lower in the below-100 kW group relative to the comparison group after the policy. However, when the sample is limited to observations where installation had already taken place, the number of installations again shows a positive increase of about 5.56 units. Taken together, these findings suggest that K-FIT may not have led to broad new entry across many new places. The results suggest more concentrated growth in already active small-project locations, rather than broad nationwide expansion. We estimate the climate benefit in three steps. First, we use the DID estimate for additional installed capacity in the treated group. Second, we convert this added capacity into annual electricity generation using the PV output measure in the data. Third, we convert the added generation into avoided CO2 emissions using Korea’s official generation-side electricity emission factor, and then value those avoided emissions using benchmark Social Cost of Carbon (SCC) values. Korea’s EG-TIPS reports a 2023 generation-side emission factor of 0.3822 tCO2/MWh and a 2021–2023 average of 0.3964 tCO2/MWh. As benchmark SCC values, we use the U.S. EPA’s 2023 SC-GHG estimates, which report $120, $190, and $340 per ton of CO2 under different discount-rate assumptions. Because these SCC values are currently being reviewed in U.S. policy discussions, we treat them as benchmark sensitivity values rather than as one fixed number.
By DaBean Bae; Sogang university    Jaecheol Lee; Sogang University
Presented by: DaBean Bae, Sogang university
Session 63: International III - Trade July 30, 2026 14:00 to 15:30 Location: Brunei Room (level 5)
Session Chair: Daniel Houser, George Mason University
Session type:
1. Foreign Investment Repatriation from India: Trends, Drivers, and Policy Implications Abstract The global landscape of foreign direct investment has undergone a quiet but consequential shift over the past two decades. Emerging market economies, long cast as passive recipients of capital from advanced economies, have increasingly become sources of outward investment in their own right. India is no exception — outward FDI flows have grown markedly since the mid-2000s, complicating the conventional narrative of unidirectional capital dependence. Yet alongside this structural transformation, a parallel and underexamined phenomenon persists: the recurring repatriation of inward foreign investment, where capital previously committed to the domestic economy is withdrawn by foreign investors. Together, these twin dynamics raise pointed questions about the durability of India's integration into global capital markets and the adequacy of existing policy frameworks designed primarily to attract, rather than retain, foreign capital. This paper investigates the macroeconomic and institutional determinants of foreign investment repatriation from India over the period 2011Q1–2025Q2. The choice of timeframe is deliberate — it captures the post-liberalisation consolidation phase, successive regulatory overhauls under the Foreign Exchange Management Act, the disruptive introduction of the Goods and Services Tax, and the extraordinary capital flow volatility induced by the COVID-19 pandemic and its aftermath. Given the absence of granular bilateral investment flow data, the empirical analysis draws on quarterly aggregate time series sourced from the Reserve Bank of India Handbook of Statistics, the IMF Balance of Payments Statistics, and OECD investment databases. Given the absence of granular bilateral investment flow data at higher frequencies, the analysis is grounded in quarterly aggregate time series data sourced from the Reserve Bank of India, the IMF Balance of Payments Statistics, and the OECD. We employ an autoregressive distributed lag (ARDL) bounds testing approach to examine both short-run dynamics and long-run equilibrium relationships between repatriation flows and a set of macroeconomic and institutional covariates. These include real exchange rate movements, domestic interest rate differentials, sovereign risk ratings, equity market returns, and a measure of global risk sentiment proxied by the VIX. These results are robust across alternative lag specifications and hold after controlling for global liquidity conditions proxied by the US Federal Funds rate. The findings carry substantive implications for capital account management in India and, more broadly, for emerging economies navigating the dual pressures of rising outward investment ambitions and continued vulnerability to inward capital reversals. The paper contributes to a growing literature on investment cycle asymmetries in developing economies and offers evidence-based guidance for institutional reforms aimed at improving foreign investor retention without compromising capital account openness.
By AMAL KRISHNAN; CHRIST UNIVERSITY, BENGALURU    Muhammed Rafi OPC; Indian Institute of Foreign Trade (IIFT)
Presented by: AMAL KRISHNAN, CHRIST UNIVERSITY, BENGALURU
2. Red Tape Protection vs. Tariff War Abstract This paper investigates the problem of red tape barriers (RTBs), which are considered one of the most important political issues in international trade, alongside FTAs. To address this, we propose a two-country, n+m-firm Cournot model that includes both FTA negotiations and RTB decisions. We show that i) such wasteful RTBs can occur even if governments are politically unbiased, but ii) they appear only if the competition level among domestic firms exceeds that among foreign firms. Furthermore, iii) to avoid RTB problems, the negotiated tariff rate will be higher than when the RTB problems are absent. Finally, finding ii) is related to ``the excess entry theorem" and contradicts the policy implication suggested by Lahiri and Ono (1988).
By Kentaro Inomata; Tokoha University
Presented by: Kentaro Inomata, Tokoha University
3. Who Bears the Cost of Trade and Geopolitical Uncertainty? Evidence on Spillovers and Transmission Channels Abstract Both trade policy uncertainty and geopolitical risk has intensified in recent years, particularly since the escalation of US-China trade tensions in 2018. This paper therefore examines the global macroeconomic and financial consequences of these two key uncertainty shocks, alongside the conventional global financial risk shock that has been central to the discussions of spillovers in international macroeconomics literature. Using a global vector autoregression framework covering 42 advanced and emerging economies plus the United States over 2000–2020, we find that trade policy and geopolitical risk shocks exert larger negative effects on output than conventional financial risk shocks, while the latter weigh more heavily on equity markets. We show that capital controls and macroprudential policies, while effective against financial risk shocks, provide little insulation against trade policy uncertainty and geopolitical risk shocks; only flexible exchange rates appear to cushion their impact. Our findings suggest a new policy dilemma: capital controls safeguard autonomy in the face of financial shocks but lose effectiveness when shocks stem from trade or geopolitics, where exchange rate depreciation becomes the key buffer. Finally, we demonstrate that geopolitical alignment and export diversification critically shape transmission: on average, output losses are greater in the US and neutral blocs, and share prices fall more in the US bloc under global financial risk shocks. These results highlight the need for new policy instruments to address rising trade and geopolitical uncertainties in the global economy.
By Jingru Luo; Nanyang Technological University    Jingting Liu; National University of Singapore
Presented by: Jingru Luo, Nanyang Technological University
4. Sequentialism vs. Simultaneity to Free Trade Abstract This paper constructs a three-country intra-industry trade model with asymmetric cost firms, in order to analyze the welfare effects under sequential or simultaneous customs unions (CUs) forming on the basis of the most-favored-nation (MFN) clause. On a non-discriminatory basis, sequential or simultaneous trade liberalization and their impact on pursuing global free trade are analyzed herein. A cost-efficient (cost-inefficient) CU imposes a low (high) common external tariff on a non-member country, where the degrees of trade liberalization are also endogenously decided. Sequentialism may yield global free trade if the difference in cost efficiency is sufficiently low. By contrast, global free trade is a unique coalition-proof Nash equilibrium (CPNE) under simultaneity.
By TE-CHENG LU
Presented by: TE-CHENG LU,
Session 64: Labor IV July 30, 2026 14:00 to 15:30 Location: Vietnam Room (level 5)
Session Chair: Jong-Wha Lee, Korea University
Session type: invited
1. Beyond the Keju: Confucian Academies and Long-Run Human Capital Accumulation in China Abstract This study examines the role of academies in contemporary human capital accumulation and their interaction with the keju system. It finds that the academy consistently impacts modern human capital accumulation in a manner comparable to the keju system. Notably, the two institutions exhibit partial substitution rather than simple complementarity: while the keju primarily fosters elite-oriented human capital through examination incentives, academies promote broader general human capital formation. Mechanism tests indicate that the role of the academy operates through three pathways: reinforcing the value of education, securing educational investment, and enriching the local supply of educational resources. Our study complements the current studies on Confucianism and human capital formation and highlights the importance of distinguishing between different institutional carriers of Confucian education when assessing its long-run economic and social consequences.
By Hongjun Zhao; Shanghai Normal University
Presented by: Hongjun Zhao, Shanghai Normal University
2. Endogenous vacancy-posting costs, worker effort, and labor market dynamics Abstract This study investigates the relationship between technology shock and labor input, which has received considerable attention in the macroeconomic literature since Galí (1999). Existing studies document both positive and negative relationships between technology shocks and labor input. To examine this issue, this study adopts a search and matching framework that incorporates an endogenous vacancy-posting costs. Additionally, this study examines how worker effort affects labor market fluctuations in response to the shock in the framework in which workers and firms bargain over wages. In the standard flexible‑price model, a positive technology shock raises labor demand, which in turn increases employment. In contrast, Francis and Ramey (2005) demonstrate a negative response of labor input to a positive technology shock using two dynamic general equilibrium models: one includes habit formation in consumption and investment adjustment costs, whereas the other includes the Leontief production function and a labor-saving technology shock. Mandelman and Zanetti (2014) show a negative employment response to a positive technology shock in a real business cycle model with search frictions. It caused by an increase in hiring costs through the technology shock. Mumtaz and Zanetti (2016) present a DSGE model with search frictions and show a negative employment response to a positive technology shock. The technology shock allows firms to produce more output with fewer labor inputs, thereby reducing employment. This study incorporates vacancy-posting costs depend positively on recruiting intensity and examines the negative relationship between technology shocks and labor input. In standard fair wage (gift-exchange) models, the worker’s optimization problem derives the relationship between worker effort and wages. This relationship is then included as a constraint in the firm’s optimization problem and serves as a source of amplified fluctuations. However, even when workers and firms bargain over wages, under which effort levels depend on wage, labor market fluctuations can be influenced by changes in worker’s and firm’s surpluses. For example, an increase in wages can lead to a higher income, higher cost, and greater output resulting from increased worker effort. The recruiting intensity in this study depend on current profits, while worker effort responds to the current wage. By endogenizing these mechanisms, the model clarifies how technology shocks affect labor market outcomes. The results show that introducing endogenous vacancy-posting costs fundamentally alters the relationship between technology shocks and labor market fluctuations. An increase in current profits due to a technology shock raises recruiting intensity and vacancy-posting costs. When the elasticity of recruiting intensity with respect to current profit is low, numerical experiments indicate that vacancies and employment increase in response to a positive technology shock. In contrast, when the elasticity is high, vacancies and employment decline. Moreover, an increase in the sensitivity of worker effort amplifies labor market fluctuations regardless of whether the employment response is positive or negative. While existing studies typically model vacancy-posting costs and worker effort separately, this study integrates both mechanisms into a single search-and-matching model. First, this study shows that the employment response to a technology shock can be either positive or negative, depending on the elasticity of recruiting intensity with respect to current profits. Second, previous studies using fair wage models find that the response of employment or unemployment to a technology shock is amplified relative to that in the Nash bargaining model. By contrast, this study shows that labor market fluctuations can also be amplified in a Nash bargaining model including worker effort. In particular, greater sensitivity of worker effort amplifies both positive and negative employment responses.
By Toyoki Matsue
Presented by: Toyoki Matsue,
3. CARE BURDEN AND WORKFORCE WITHDRAWAL AMONG PRIME-AGE PERSONS IN VIETNAM Abstract Unpaid family care in Viet Nam is largely organized within households and may constrain labour market participation among prime-age persons (those aged 28–54). Using nationally representative data from the 2022 Viet Nam Labour Force Survey, this study examines family-related workforce withdrawal, focusing on gender differences, education, and the distinction between childcare- and adult-care-associated withdrawal. The main outcome is being outside the labour force and reporting housework or family responsibilities as the primary reason for non-participation. Weighted logistic regression models with province and survey-month fixed effects are employed, alongside analyses of care participation and care intensity. The findings reveal a pronounced gender gap in family-related workforce withdrawal. Women are about eleven times more likely than men to be out of the labour force because of housework or family work, even after accounting for demographic and geographic characteristics. Higher education is associated with a lower likelihood of withdrawal, particularly among women, but does not eliminate gender disparities. Childcare-related withdrawal is substantially more common than adult-care-related withdrawal, while adult care appears underreported in the survey. Among employed persons, women are also more likely to provide childcare and spend more time on care than men. Interpreted as nationally representative associations rather than causal effects, these results demonstrate that unpaid family care remains a significant gendered constraint on labour market participation and underscore the need for expanded childcare services, long-term care support, and family-friendly workplace policies.
By Trang Dinh; Vietnam Center for Economic and Strategic Studies (VESS)    Long Giang; National Economics University    Linh Nguyen; Foreign Language Specialized School
Presented by: Trang Dinh, Vietnam Center for Economic and Strategic Studies (VESS)
4. Female Higher Education, Marriage, and Fertility in Korea: Evidence from Higher-Education Expansion Reforms Abstract This paper examines how the expansion of female higher education affected marriage and fertility in South Korea, where childbearing remains closely tied to marriage. The paper asks whether additional education reduced fertility mainly by lowering marriage entry or by reducing childbearing among married women. The analysis exploits the 1993 higher-education liberalization as a source of variation in women's tertiary attainment and combines a cohort-based instrumental-variable strategy with longitudinal data from the Korean Labor and Income Panel Study. The empirical design distinguishes early marriage, longer-run marriage entry, motherhood, total children, and fertility conditional on marriage. Reduced-form estimates indicate that the 1993 liberalization reduced marriage by age 25 by 8.2 percentage points and lowered ever-married status by about 4 percentage points in the main comparison window. The estimates indicate substantial delay in early marriage and incomplete catch-up by the end of the observation period. By contrast, fertility among women who married shows no stable decline. The full-sample fertility estimates, interpreted together with a demographic decomposition, point to the same conclusion: the decline in childbearing associated with women's expanded access to higher education operated mainly through delayed or foregone marriage rather than through lower fertility within marriage.
By Do Won Kwak; Korea University    Jong-Wha Lee; Korea University    Eunbi Song; Monash University Malaysia
Presented by: Eunbi Song, Monash University Malaysia
Session 65: Editors' Tea Reception (Tips on Publishing and ask me anything) July 30, 2026 15:30 to 16:40 Location: Ballroom 1 (level 3)
Session Chair: Te Bao, Nanyang Technological University
Session type: invited
Discussants:      Daniel Houser, George Mason University      Erik Snowberg, The University of Utah      HSIAO Cheng, University of Southern California      Chi Wai Rick Lee, World Scientific Publishing Co Pte Ltd
Session 66: AI and Digital Markets IV July 30, 2026 16:40 to 18:10 Location: Cambodia Room (level 5)
Session Chair: Eugene Or, Singapore University of Social Sciences
Session type: invited
1. Hayekian Data Economy in the Artificial Intelligence Era Abstract Data records human development and civilization for centuries. The dispersion and utilization of data have fueled the evolution of knowledge and technology. However, the development of the data economy is limited and lags behind. The current data economy is underdeveloped due to the nature of data itself. Data is characterized by six core characteristics: live, ubiquitous, tacit in meaning, fragmented in representation, susceptible to contamination, and subject to blurred sovereignty. Applying Hayek’s concepts of decentralized knowledge and spontaneous order to the data economy, this paper examines how advances in AI and AI-powered agents may help overcome longstanding structural constraints and enable substantial expansion of the data economy in the AI era. It argues that a Hayekian spontaneous order may emerge in the data economy when three conditions are in place to address the issues embedded in the six defining characteristics of data. These three conditions are value-embedded data ownership, minimum necessary data consumption at minimum cost, and precise data provision with verifiability and accountability.
By Chun-Chien Kuo; National Taipei University of Business
Presented by: Chun-Chien Kuo, National Taipei University of Business
2. Bridging the Gap: Information Access and Well-being among Older Adults in Vietnam Abstract This study examines the relationship between information access and mental health among older adults in Vietnam. Using nationally representative data from the 2011 Vietnam National Aging Survey, we analyze six dimensions of mental health, including life satisfaction, happiness, depressive feelings, sleep difficulties, poor appetite, and loneliness. Information access is broadly defined to encompass both digital and traditional media channels. To address concerns of selection bias and omitted variable bias, we employ the coefficient stability approach proposed by Oster (2019), complemented by additional sensitivity analyses under alternative assumptions. The results indicate that information access is consistently associated with better mental health outcomes: older adults with access to information report higher life satisfaction and happiness, alongside lower levels of depression, loneliness, sleep problems, and poor appetite. These findings remain robust across specifications and under conservative assumptions regarding unobserved selection. The study highlights information access as an important non-medical determinant of psychological well-being in later life and underscores the need for policies that promote inclusive and equitable access to information for aging populations in developing countries.
By Hang Nguyen; Asian Growth Research Institute
Presented by: Hang Nguyen, Asian Growth Research Institute
3. Digitalisation and Household Wellbeing: An Empirical Study in an Emerging Economy Abstract Digitalisation has been a growing feature of socioeconomic transformation in emerging economies, yet its implications for household subjective wellbeing remain limited. This study investigates how digitalisation at the household level, measured by digital financial inclusion and engagement in online activities, is related to subjective wellbeing. Using nationally representative household survey data from Vietnam this study employs the two-stage conditional logit model to address potential endogeneity. Subjective wellbeing is measured using households’ perceived economic status compared to previous years. The results consistently show that digitalised households tend to report significantly higher levels of subjective wellbeing compared to their non‑digitalised counterparts. These associations are not only found in the full sample but also among the urban and rural samples, suggesting that digitalisation may play important role in heterogeneous domestic regions. The study contributes to the literature on digital inclusion in the literature by providing empirical evidence from an emerging economy. The findings imply the necessity of policies that promote digital infrastructure as a complementary strategy for improving quality of life and supporting broader development objectives in the emerging economy settings. Key words: Digitalisation; Household Wellbeing; Emerging Economy JEL codes: I31, O12
By Luong Duy; University of Economics Ho Chi Minh City
Presented by: Luong Duy, University of Economics Ho Chi Minh City
4. Can Digital Platforms Boost Economic Growth? Evidence from the Taobao Villages Abstract This paper examines the effect of e-commerce on local economic growth in China. Using a comprehensive panel dataset covering 1,622 counties from 2009 to 2022, we employ a Propensity Score Matching Difference-in-Differences design and a Two-Stage Least Squares strategy with spatial instrumental variables to address endogeneity issue. We find robust evidence that the formation of Taobao Villages significantly accelerates local GDP growth, with treated counties experiencing an average increase of approximately 0.73-0.78 percentage points relative to the control group. Heterogeneity analysis reveals that the growth effects are significantly stronger in regions with better internet and road infrastructure, highlighting the critical role of complementary physical and digital infrastructure in enabling rural e-commerce to drive economic development. Mechanism analysis reveals that Taobao Villages drive structural transformation, diminishing agricultural sector dependence while expanding manufacturing activity, together with the productivity gain in manufacturing sectors. Moreover, Taobao Villages improve innovation activity and expanded entrepreneurship. These findings suggest the transformative potential of digital platforms in rural development and offer guidance for policymakers designing development strategies in emerging economies.
By Mengyuan CAI; Nanyang Technological University    Shu Tian; Asian Development Bank
Presented by: Mengyuan CAI, Nanyang Technological University
Session 67: Econometrics IV (Applied): Data, Mobility and Innovation in Cities July 30, 2026 16:40 to 18:10 Location: Singapore Room (level 5)
Session Chair: Zach Lee, National University of Singapore
Session type: invited
1. Data and Innovation Connected Cities: Open Public Data and Inter-City Collaborative Innovation Abstract Public data helps enterprises identify external innovation environments and reduce coordination costs, making public data openness the key to connecting "data silos." Based on Chinese city panel data from 2009 to 2022, yielding 45,677 "city-pair-year" observations, this paper treats the launch of public data open platforms as a quasi-natural experiment. We construct a multi-period Difference-in-Differences (DID) model to empirically examine the impact of public data openness on inter-city collaborative innovation and its underlying mechanisms. The findings reveal that public data openness significantly promotes inter-city collaborative innovation; specifically, average inter-city collaborative innovation increases by 10.21% following the establishment of city pairs. This conclusion remains robust after a series of robustness checks, including parallel trend tests, placebo tests, ruling out other policy shocks, and using alternative measures of the dependent variable. Heterogeneity analysis indicates that the enhancement effect of public data openness is more pronounced for city pairs with higher administrative levels, lower spatial friction, and those crossing administrative boundaries. Further analysis finds that the cross-tier and cross-regional synergies of public data openness yield the most significant effects; moreover, public data openness between cities of equal administrative levels exhibits a more pronounced impact on collaborative innovation. Mechanism tests reveal that public data openness promotes inter-city collaborative innovation primarily through three channels: enhancing technological proximity, increasing entrepreneurial activity, and alleviating financing constraints. This paper provides a theoretical foundation and empirical support for innovation entities to reconstruct collaborative innovation decisions, while offering practical references for improving the construction of public open platforms and unleashing the value of public data. Keywords: Public Data Openness, Collaborative Innovation, Technological Proximity, Entrepreneurial Activity, Financing Constraints JEL Codes: O38, R11，O31
By Limin Zhang; Lanzhou University    Yue Zhang; Lanzhou University    Lili Wei; Lanzhou University
Presented by: Yue Zhang, Lanzhou University
2. Decomposing Ride-Hailing Trip Duration Uncertainty: A Wasserstein-Based Sensitivity Analysis Framework Abstract This paper introduces a unified sensitivity analysis framework for distributional predictions based on Wasserstein geometry, comprising Global Distributional Importance (GDI) for aggregate feature sensitivity and Tangent-SHAP for local attributions. The framework extends Shapley-based explanation methods to distribution-valued outputs by operating in the tangent space of the Wasserstein manifold, yielding function-valued attributions across the quantile spectrum. We apply this methodology to 46.5 million ride-hailing trips from New York City in 2023, using CatBoost quantile regression at five quantile levels. Trip distance dominates distributional influence with 55.2% of total GDI, followed by hour of day (17.3%) and pickup location (10.0%). Weighted GDI analysis reveals that weather conditions exert 25% greater influence on upper quantiles compared to central predictions, while rush hour effects on upper tail risk exceed central impacts by a factor of 2.87. Regional decomposition shows Manhattan and outer borough trips share similar importance rankings (Spearman rho=0.984) but differ in absolute magnitudes, with temporal factors more influential in Manhattan and distance dominant in outer boroughs. The Tangent-SHAP completeness property is verified with errors below machine precision. These findings demonstrate how distributional sensitivity analysis provides insights unattainable through mean-focused measures, offering transportation planners granular understanding of uncertainty drivers across the trip duration distribution.
By Xie He; Tokyo University of Science    YU ZHAO; Tokyo University of Science
Presented by: Xie He, Tokyo University of Science
3. Travel as Production: Endogenous In-Trip Output, Scheduling, and the Bottleneck Abstract Automation, ride-hailing, and other passenger services can make travel time usable for work or rest. This paper models travel as production. Scheduled activity access is the final commodity; trips are intermediate inputs; and mode, route, departure-time, and vehicle-technology choices are production plans. At a reference allocation, active travel time costs the resource value of time plus effort, whereas passive time costs that value net of reclaimed output. A constant-returns implicit-price rule appears as a special case. Embedding these time values in a Vickrey-Arnott-de Palma-Lindsey bottleneck distinguishes three effects. In a homogeneous fixed-demand pure point bottleneck, productive in-vehicle time increases waiting and queue stock but leaves money-metric generalised user cost and the optimal time-varying toll unchanged within the model's cost accounting. A lower effective early-arrival penalty shifts arrivals earlier and reduces maximum waiting; with elastic demand, lower free-flow cost induces trips and raises the optimal toll. The production structure also yields candidate cross-equation restrictions that generic choice models need not satisfy. Stylised simulations illustrate the results. JEL: R41, R48, D13, D61, L91. Keywords: household production; value of travel time; bottleneck model; scheduling; congestion pricing; autonomous vehicles; revealed preference restrictions.
By Zach Lee; National University of Singapore
Presented by: Zach Lee, National University of Singapore
Session 68: Financial V - Stock Market July 30, 2026 16:40 to 18:10 Location: Thailand Room (level 5)
Session Chair: Ahmet Aysan, Hamad Bin Khalifa University
Session type: invited
1. Are ESG Ratings Noisy for Stock Returns? Evidence from Thailand Stock Market Abstract This study explores the relationship between Environmental, Social, and Governance (ESG) factors and stock returns in the Stock Exchange of Thailand (SET), focusing on the challenges of noise and confusion that can arise in analyzing this relationship. While evidence suggests a positive correlation between strong ESG performance and financial performance, the presence of noise can hinder accurate interpretation. This study introduces a noise-correction procedure for Environmental, Social, and Governance (ESG) ratings by utilizing ratings from multiple ESG rating agencies as instrumental variables. Drawing inspiration from the classical errors-in-variables problem as proposed in the work of Berg, Koelbel, Pavlova, and Rigobon (2022), this approach aims to address the inherent noise and inconsistencies in ESG ratings. By instrumenting ESG ratings with ratings from other agencies, the proposed procedure seeks to mitigate measurement errors and improve the accuracy of ESG assessments. We discuss the application of instrumental variable techniques in tackling the noise problem in ESG ratings and highlights the potential benefits of this approach.
By Wasin Siwasarit; Chulalongkorn University    Sitisak Leelahanon; Thammasat University
Presented by: Wasin Siwasarit, Chulalongkorn University
2. Bedtime Stories or Market Reality? How Overnight Information Shapes Next-Day Trading in Stock Exchange of Thailand Abstract This study investigates how overnight information transmits into daytime volatility in the Stock Exchange of Thailand (SET), a market whose non-synchronous trading hours allow substantial international and domestic news to accumulate while the exchange is closed. Using a unique high-frequency market microstructure dataset containing both deal and order information for SET100 constituents from 2018 to 2023, we construct a realized range-based volatility (RRV) measure and extend the heterogeneous autoregressive (HAR) framework to incorporate the direction and importance of overnight news. We further examine how firm-level microstructure characteristics, specifically trading costs and retail net buying, mediate this transmission, and assess whether volatility dynamics shifted during the COVID-19 period of heightened global uncertainty. Three main findings emerge. First, overnight information is a critical driver of daytime volatility: the direction of overnight returns produces an immediate short-term effect, while the importance of overnight news exerts a more prolonged influence. Second, stocks with lower trading costs incorporate the directional content of overnight news more efficiently, whereas stocks with high retail net buys display greater sensitivity to overnight information. Third, and most notably, large and negative shocks dominate the response, indicating that "bad news" arriving outside trading hours acts as a stronger catalyst for next-day price movements than "good news." Both overnight volatility and RRV for the SET index spiked sharply in early 2020, and the predictive power of overnight shocks strengthened during this period of elevated uncertainty. Out-of-sample forecasting comparisons across the baseline HAR-RRV, HAR-RRV augmented with global overnight information, and HAR-RRV augmented with both global and local overnight information confirm the incremental value of overnight information, particularly during high-uncertainty regimes.
By Kantapong Visantavarakul; Chulalongkorn University    Sicha Thubdimphun; Thammasat University    Wasin Siwasarit; Chulalongkorn University
Presented by: Kantapong Visantavarakul, Chulalongkorn University
3. Disclosure, Timing, and Capital Allocation: Evidence from SFDR and European Bond Fund Flows Abstract The Sustainable Finance Disclosure Regulation (SFDR) introduces standardized sustainability disclosures intended to improve the comparability of sustainable investment products. This paper examines whether SFDR affected flows into European bond funds and whether the response differed across retail and institutional investors during the issuance and implementation stages. Using fund-level data and a difference-in-differences design with the United Kingdom and Switzerland as controls, we document a statistically and economically significant increase in fund flows of approximately 1.4–1.7 percentage points per month following SFDR issuance. In contrast, formal implementation does not generate a comparable positive effect. The issuance-stage response is broad-based across investor segments, whereas the implementation-stage response is weaker and more heterogeneous. Overall, the evidence suggests that SFDR matters most when disclosure first changes the information environment, highlighting the role of disclosure design in shaping capital allocation and informing the ongoing SFDR 2.0 debate.
By Aviandini Cahyawati; Universitas Indonesia    Cynthia Utama; University of Indonesia    Arief Wibisono Lubis; Universitas Indonesia    Zaafri Husodo; University of Indonesia
Presented by: Aviandini Cahyawati, Universitas Indonesia
4. The Effect of Political Instability on Stock Markets: Evidence from Internet Searches, News Articles, and Event Studies Abstract This study analyzed the relationship between political instability and stock market returns using data from the Philippines. We measured political instability using three approaches – i) daily indexes derived from the Google Trends Search Volume Index, ii) daily indexes created from keyword search in news articles, and iii) a list of specific political instability events. Applying Vector Autoregression (VAR) and Generalized Autoregressive Conditional Heteroskedasticity (GARCH) methods on the first two approaches, we found that political instability, in general, have no significant relationship with the level of stock market returns. However, some forms of political instability – particularly those related to strikes, protests, rallies, impeachment, coup d’etat, and rebellion – are associated with higher stock returns volatility. Meanwhile, applying event study methods on the third approach, we found that certain major political instability events do affect the level of stock returns, even if overall political instability does not. The conclusion of impeachment trials, selected coup attempts, and certain presidential elections are some of the specific events that can affect the level of stock returns.
By Tristan Canare; Bangko Sentral ng Pilipinas
Presented by: Tristan Canare, Bangko Sentral ng Pilipinas
Session 69: International IV July 30, 2026 16:40 to 18:10 Location: Indonesia Room (level 5)
Session Chair: Wai Mun Chia, Nanyang Technological University
Session type: invited
1. Beyond Apples-to-Apples: A Cross-Category Explanation of the Alchian–Allen Effect Abstract This paper develops a unified framework that extends the Alchian–Allen mechanism beyond the restrictive assumption of close substitutes. The framework emphasizes a fixed-cost selection mechanism in which logistics structures filter goods according to their ability to sustain profitable long-distance exchange. Empirical analysis uses high-dimensional U.S. import data from 2023 to 2025. The main quantitative evidence is presented at the HS2 level, consistent with the cross-category logic of the paper, while HS10 specifications and stricter sample definitions are used as robustness checks. The results yield two main findings. First, more distant trade flows exhibit significantly higher observed unit values at the HS2 level, indicating that the good-apples-shipped-out pattern operates not only within narrowly defined products but also across broad product categories. Second, the positive distance–unit-value relationship is stronger for observations involving air transport, especially in broader samples, consistent with the view that higher-cost transport channels impose a stricter selection filter. Overall, the findings support a cross-category interpretation of the Alchian–Allen mechanism and suggest that lower logistics and institutional fixed costs can broaden participation in long-distance trade.
By Jian Ding; Zhejiang Guangsha Vocational and Technical University of Construction
Presented by: Jian Ding, Zhejiang Guangsha Vocational and Technical University of Construction
2. Sub-Regional (Neighbourhood) Power Grids, (Clean) Energy Transition & Policy Alternatives for Singapore Abstract Singapore's transition to a low-carbon economy is constrained by limited domestic renewable energy resources and a continued dependence on imported natural gas for electricity generation. In response, ASEAN's vision of regional electricity market integration—supported by sub-regional and cross-border power grids—offers a promising pathway to enhance energy security, accelerate decarbonisation, and strengthen regional economic integration. While initiatives such as the Lao PDR–Thailand–Malaysia–Singapore Power Integration Project (LTMS-PIP) demonstrate the feasibility of cross-border electricity trade, the long-term success of regional grid integration depends not only on technological capability but also on economic viability, institutional arrangements, and socio-political cooperation. This paper proposes a transdisciplinary framework for evaluating ASEAN energy transition from Singapore's perspective. It integrates three complementary dimensions: (i) an assessment of existing and emerging technological options for regional electricity interconnection; (ii) an examination of the socio-political and cultural contexts shaping cross-border energy cooperation, including governance, institutional trust, and public policy priorities; and (iii) an economic evaluation of alternative policy pathways for bilateral and sub-regional electricity trade. The study is grounded in ASEAN's commitment to regional energy integration and decarbonisation and draws on publicly available data from the Energy Market Authority (EMA), ASEAN Centre for Energy (ACE), and the International Energy Agency (IEA). The research adopts a staged, multi-method approach. Initial analysis focuses on bilateral electricity trading arrangements before considering broader regional integration. Policy alternatives are assessed using an expanded cost-benefit analysis (CBA) that incorporates infrastructure readiness, technological innovation, climate risks, institutional capacity, and long-term social welfare. Strategic interactions among participating economies are examined through bargaining models, while an environmental Dynamic Stochastic General Equilibrium (DSGE) model is proposed to estimate the macroeconomic and environmental impacts of cross-border electricity trade. By evaluating the trade-offs among energy security, decarbonisation, regional cooperation, and economic resilience, the paper develops practical policy insights to support Singapore's long-term energy transition strategy while contributing to broader discussions on ASEAN's evolving regional electricity market.
By Asif Siddiqui; Nanyang Technological University    Jun Rui TAN; Nanyang Technological University
Presented by: Asif Siddiqui, Nanyang Technological University
3. Geopolitical Alignment and Trade Fragmentation: Asymmetric Effects of US- and China-salient Risk Abstract This paper examines how bilateral merchandise trade responds to geopolitical risk along continuous alignment gradients. Using continuous UN ideal‑point distance data and disaggregated trade flows, we estimate structural gravity models using Poisson pseudo‑maximum likelihood (PPML) with exporter‑year, importer‑year, and dyad fixed effects. Our findings are fourfold. (1) Higher geopolitical risk fragments trade along geopolitical lines: more distant or polarized dyads trade relatively less when risk rises, while closely aligned dyads trade relatively more. (2) This fragmentation is strongly asymmetric with China‑salient risk generates a trade reallocation more than three times larger than US‑salient risk. (3) The fragmentation gradient is substantially weaker for ASEAN‑linked dyads, with nearly complete attenuation under US‑salient risk. (4) Sectoral analysis shows that this attenuation is strongest in capital‑intensive and GVC goods. These results reveal that geopolitical fragmentation is source‑dependent and that ASEAN acts as a distinct regional buffer, though its resilience is less complete when risk is centered on China. F51, F53, F14
By Deeksha Kokas; Nanyang Technological University    Wai Mun Chia; Nanyang Technological University
Presented by: Wai Mun Chia, Nanyang Technological University
Session 70: Labor V July 30, 2026 16:40 to 18:10 Location: Philippines Room (level 5)
Session Chair: Renate Schubert, ETH Zurich
Session type: invited
1. Furlough as a Match-Preservation Option Abstract This study provides an empirical and theoretical analysis of furlough in the Japanese labor market. Using the Labour Force Survey, I construct worker flows across four states: employment, furlough, unemployment, and nonparticipation, and estimate transition rates. I find that the transition rate from employment to furlough exceeds that to unemployment and has increased since around 2015, resulting in a furlough rate that exceeds the unemployment rate. To better understand these empirical facts, I extend a standard Diamond—Mortensen—Pissarides model to incorporate a furlough state. In steady state, the availability of a furlough option allows high-productivity matches to avoid separation and return to production, while lower-productivity matches are more likely to be destroyed, thereby increasing average labor productivity. Changes in furlough benefits affect the incidence of furlough and the composition of matches, with implications for resource allocation.
By TETSUAKI TAKANO
Presented by: TETSUAKI TAKANO,
2. Does Immigration Mitigate Ageing-Led Ineffectiveness of Monetary Policy for Economic Growth in OECD Countries? Abstract The OECD countries are revising their immigration policies by taking in foreign workers to combat labor shortage caused by declining fertility and a rapidly aging population. This is the first scholarly attempt to test the hypothesis that inflows of foreign workers would mitigate the ineffectiveness of monetary policies through the labor supply channel in OECD economies that are experiencing a declining demographic dividend. The first set of results based on a dynamic panel cointegration analysis reinforces the findings in the extant literature that population aging weakens the effectiveness of monetary policies for economic growth. Two new results emerge which enhance the novelty of our study. One, the higher-aged OECD economies experience a more declining effectiveness of monetary policy for economic growth. Two, an increase in net migration mitigates the ineffectiveness of monetary policy for economic growth. The results underscore the importance of immigration in strengthening monetary policy effectiveness for economic growth through the labor supply channel in the aging OECD economies.
By Rajarshi Mitra; Tokyo International University    Md. Thasinul Abedin; University of Chittagong
Presented by: Rajarshi Mitra, Tokyo International University
3. Emissions, Firm Selection, and Unemployment Abstract Due to the severe climate change, governments have adopted different policies to deal with the issue. This research consider a nationally determined emission tax and constructs a model of international trade with firm-level heterogeneity and unemployment. The main target of this research is to clarify how emission tax affects the relevant variables and to provide some theoretical explanations, especially unemployment, wage inequality, and resulting welfare level. The preliminary finding suggests that when emission tax increases, wage inequality decreases within the higher income group and increases with the lower income group in autarky equilibrium.
By Li-Wen Hung
Presented by: Li-Wen Hung,
Session 71: Public III - Taxation July 30, 2026 16:40 to 18:10 Location: Brunei Room (level 5)
Session Chair: Cheng Keat Tang, Nanyang Technological University
Session type: invited
1. Year-End Tax Sprints and Environmental Enforcement: Evidence from Mid-Year Budget Revisions Abstract Abstract: Under balanced budget constraints, local governments facing year-end shortfalls often resort to last-minute tax sprints. This paper examines how weakened environmental enforcement facilitates such behavior. Using high-frequency data from China on firm-level energy use and prefecture-level mid-year budget revisions and execution, we show that fourth-quarter tax sprints significantly reduce firms’ coal-use efficiency, particularly in jurisdictions with ambitious revenue targets, weak early-year fiscal performance, and among top taxpayers. We find evidence of this revenue-driven relaxation in fourth-quarter reductions in environmental penalties and increases in firm production and tax payments. The effect is stronger when poor air-quality performance earlier in the year makes compliance with environmental targets difficult by year end, but is attenuated by vertical environmental inspections. A multitask principal-agent framework formalizes these trade-offs and shows how imbalanced incentives distort effort allocation across tasks.
By Yixin Chen; Central University of Finance and Economics    Shen Hu; University of International Business and Economics    Zhao Li; Central University of Finance and Economics    Bingyang Lyu; Renmin University of China
Presented by: Yixin Chen, Central University of Finance and Economics
2. Nonlinear Taxation with Wealth Heterogeneity and Private Information on Inter Vivos Transfers Abstract This paper studies the joint design of the bequest and income tax schedules in an intergenerational model with altruistic parents. Bequests and income are observable, while parents’ wealth and inter vivos are not. We find that the optimal marginal estate and labor income tax schedules are interrelated and characterized by a modified inverse Euler equation, and there is a one-to-one correspondence between estate and savings income taxes. Abstracting from human capital, with the incentive effect due to unobserved wealth inequality, the optimal labor income tax rate is negative, while the optimal estate tax rate is positive but mitigated by inter vivos and further by positive externalities of bequest, and may be negative if this latter Pigouvian effect dominates. Moreover, in an infinite horizon model, the estate tax provides insurance against shocks to agents’ wealth types over generations. Thus, the incentive, the Pigouvian correction and the insurance effects determine the optimal implicit estate tax schedule in an infinite horizon model. Finally, with human capital investment, the optimal estate tax is unchanged, while the labor income tax turns positive from the second generation onwards.
By Been-Lon Chen; Academia Sinica    Fei-Chi Liang; National Chengchi University
Presented by: Fei-Chi Liang, National Chengchi University
3. AN APPLICATION OF THE OPTIMAL TAXATION THEORY WITH LEISURE COMPLEMENTARITY FOR THE PHILIPPINES Abstract AN APPLICATION OF THE OPTIMAL TAXATION THEORY WITH LEISURE COMPLEMENTARITY FOR THE PHILIPPINES ABSTRACT This paper aims to calculate the demand response using the cross section of household data in the Philippines using the Almost Ideal Demand System of Deaton and Muellbauer (1980) without automatically assuming separability of utilities. The AIDS model yields considerable and comparable estimates as with literature, mostly with statistically significant results. Substitution and complementarities across key goods are observed, while luxuries and necessities are likewise identified suggesting the possible structure of the tax rates. The second part of the paper uses the results from the AIDS model and solves an optimal taxation problem using the solution outlined by Ramsey (1927) which will derive theoretically consistent optimal commodity tax rates. It was estimated that labor supply elasticity is about 0.42which is within the range of existing estimates of other authors. Concluding remarks regarding conformity with the existing tax rules are also drawn. Unlike past research on the determination of the appropriate Philippine tax structure, this paper will provide an approach that uses the lessons from theory and applies empirical methodology demonstrating the use of a flexible demand system model. The leisure complementarity feature first observed in Corlett and Hague (1953) and empirically tested by Asano and Fukushima (2006) and West and Willliams (2007) shall be implemented. Conclusions drawn from the study are of theoretical and of empirical importance. Firstly, output from the study reveals evidence whether the assumptions of demand theory is confirmed by data for the case of a developing country which is often not tested in the literature. Secondly, income and price elasticities are used to observe the nature of the degree of responses of consumers. Fourth, the degree of complementarity with leisure of other commodity items and the labor supply elasticity were successfully estimated. The policy relevance of this analysis is highlighted in the current global economic environment characterized by heightened uncertainty, supply disruptions, and increasing volatility in international markets. Many economies are increasingly relying on domestic demand and inward-oriented consumption as a stabilizing source of growth. Understanding the structure of consumer demand and its responsiveness to prices and income has never been more crucial for designing growth and tax policies that both raise incentives, and revenue efficiently and minimize distortions in household behavior. The paper is organized as follows: Chapter II discusses about the rules of optimal commodity taxation as well as the development of optimal taxation theory which will serve as guiding framework for this study; Chapter III presents the theoretical and mathematical derivation of the AIDS and optimal tax rate problem; Chapter IV specifies the AIDS econometric model; Chapter V details the data description primarily covering Family Income and Expenditure Survey prior to the 2008 crisis period (2006), and compare this to a round of estimates for the latest non-COVID19 crisis data (2023); Chapter VI outlines the results and analysis, and finally Chapter VII concludes the paper.
By Madeleine Vinuya; Economic Society of Singapore (ESS), former AMRO and Citibank
Presented by: Madeleine Vinuya, Economic Society of Singapore (ESS), former AMRO and Citibank
4. Legal certainty in tax enforcement and investment decisions Abstract Legal certainty is a core attribute of effective tax administration, shaping corporate behaviour including investment decisions by reducing enforcement uncertainty. This paper studies how legal certainty in tax administration affects investment decisions. Using firm-level subsidiary data and regional-level venture capital investment data, we exploit the staggered adoption of regional guidelines in China that standardize discretion in tax administrative penalties and increase enforcement certainty. Difference-in-differences estimates indicate that greater tax enforcement certainty increases firms’ cross-regional investment. These effects are stronger in regions with weaker ex ante legal environment. The results highlight the role of tax legal certainty in reducing market frictions.
By Jiankun Lu; Zhejiang University of Finance and Economics    Zhuo Nie; Peking University    Yuchen Wu; Zhejiang University of Finance and Economics    Tingyu Zhou; Zhejiang University of Finance and Economics
Presented by: Tingyu Zhou, Zhejiang University of Finance and Economics
Session 72: Technology and Innovation III July 30, 2026 16:40 to 18:10 Location: Malaysia Room (level 5)
Session Chair: Mehmet Bilgin, Istanbul Medeniyet University
Session type:
1. AI Adoption Pathways and Sustainable Decision-Making: A Configurational Study of Circular Economy Startups Abstract Sustainability-oriented startups play a critical role in advancing circular economy transitions. Yet, existing research largely treats AI adoption as a uniform, technology-driven process, leaving underexplored the question of how these organisations configure AI adoption and governance to achieve sustainability outcomes. This study addresses this gap by examining the behavioural patterns through which circular economy startups adopt and govern AI from a configurational perspective. Using a comparative qualitative case study of three Japan-based startups: Epsilon Bioanalytics, Kimpax, and Mymizu, data were collected through interviews, field observations, and document analysis between 2023 and 2025. The study develops the AI for Sustainability Adoption (AISA) framework, integrating the concept of Technology-Organization-Environment perspective, Responsible AI principles, and the Triple Helix model. The findings reveal that AI adoption does not lead to uniform outcomes but instead produces three distinct behavioural pathways:: (i) a deep-tech pathway emphasizing scientific validation and long-term learning, (ii) a governance-centric pathway prioritizing transparency and ESG accountability, and (iii) a community-driven pathway leveraging behavioral change and stakeholder engagement. Across these pathways, the AISA framework demonstrates that sustainability outcomes depend on how AI reshapes learning processes, data transparency and stakeholder engagement. This study contributes to behavioural and sustainability research by reconceptualising AI adoption as a behavioral and context-dependent process, demonstrating how different configurations of governance and collaborative mechanisms lead to varied sustainability outcomes. The findings offer practical insights for designing AI-enabled interventions that influence sustainable decision-making in circular economy context
By Hoe Chin Goi; NUCB Business School    M. Mohsin Hakeem; NUCB Business School
Presented by: Hoe Chin Goi, NUCB Business School
2. Forecasting with machine learning using large survey data Abstract Survey-based forecasts produced by professional forecasters are widely used by central banks and policy institutions, and combining these forecasts is standard practice. In applied settings, simple cross-sectional averages often perform remarkably well, while more flexible combination methods frequently fail to deliver systematic improvements. This empirical regularity is commonly attributed to small sample sizes, strong cross-forecaster correlations, and real-time information constraints, all of which make the estimation of optimal combination weights difficult. As a result, the practical usefulness of machine learning and stacking methods for survey forecast combination remains an open question, particularly in small panels observed in real time. This contribution examines whether machine learning–based combination methods can improve the accuracy of survey forecasts when evaluated under realistic real-time conditions and tight data constraints. The analysis focuses on a unique monthly survey of Slovak commercial banks reporting point forecasts for current-year GDP growth and inflation. The sample spans 2007–2024 and consists of a small but stable panel of professional forecasters with complete reporting histories. The data environment is representative of forecasting problems faced by smaller central banks and policy institutions, where the number of forecasters is limited and real-time data availability is constrained by publication lags. A key feature of the empirical design is a strictly real-time rolling evaluation framework. For each forecast date, the training sample is restricted to observations that would have been available at that point in time, explicitly accounting for publication lags in official GDP and inflation data. Forecasts are generated using expanding windows subject to a minimum sample size requirement, and all model tuning is performed using time-series cross-validation that preserves the temporal ordering of the data. This design eliminates look-ahead bias and ensures that all reported results reflect genuine out-of-sample performance. The contribution evaluates a broad set of forecast combination methods. Linear approaches include ordinary least squares and regularised regressions such as Ridge, Lasso, and Elastic Net, which shrink estimated weights and mitigate overfitting in small samples. Non-linear machine learning methods include decision trees, random forests, gradient-boosted trees, support vector regression, and k-nearest neighbours, all applied directly to the vector of individual bank forecasts. In addition, stacking methods are considered, where multiple base models are first evaluated out of sample and then combined using non-negative least squares to produce a constrained ensemble forecast. All methods are compared against the simple equal-weight mean of bank forecasts, which serves as the primary benchmark. Forecast accuracy is evaluated using mean squared error, aggregated across all forecast months, and reported relative to the benchmark mean. The analysis focuses on current-year forecasts, which are of particular relevance for policy institutions, as the target variable remains fixed within the calendar year while information accumulates over time. The results reveal a clear and economically meaningful contrast between inflation and GDP forecasts. For current-year inflation, regularised linear combination methods consistently outperform the equal-weight benchmark. Ridge, Lasso, and Elastic Net combinations reduce mean squared forecast errors by approximately 10–20 percent. These gains are stable across the evaluation period and reflect the ability of shrinkage methods to downweight persistently biased or noisy forecasters without introducing excessive estimation variance. In contrast, non-linear machine learning models and stacking approaches perform poorly for inflation, often yielding higher forecast errors than the simple mean. This pattern suggests that, in a homogeneous panel of professional inflation forecasters, the scope for exploiting nonlinearities is limited and outweighed by overfitting risk. For current-year GDP growth, the results differ markedly. Several non-linear machine learning models outperform the equal-weight benchmark by a substantial margin. Support vector regression delivers the largest improvement, with mean squared forecast errors roughly 40 percent lower than those of the benchmark mean. Random forests, gradient-boosted trees, and constrained stacking of non-linear base models also achieve sizeable gains. In contrast, linear and shrinkage-based combinations fail to improve on equal weights for GDP, indicating that simple reweighting of individual forecasts is insufficient in this case. These findings suggest that nonlinear relationships between forecasters’ expectations contain useful information for GDP forecasting, which can be exploited by machine learning methods when appropriately constrained and evaluated in real time. Overall, the results demonstrate that the value of machine learning and stacking in survey forecast combination is highly target-specific and sensitive to real-time constraints. Equal weights remain a strong benchmark, but they are not universally optimal. Regularised linear methods are effective for inflation forecasting, while non-linear models and restricted ensembles can deliver large gains for GDP growth.
By Adam Csapai
Presented by: Adam Csapai,
3. Asymmetric Tolerance: A Behavioral Theory of AI Adoption and Regulation Abstract AI systems and human agents both make errors, but adoption and regulatory decisions weight equivalent errors asymmetrically by source. Standard theories of technology adoption — diffusion of innovations, the technology acceptance model, and the unified theory of acceptance and use of technology — do not predict this asymmetry, and behavioural accounts of algorithm aversion document it without theorising its consequences for governance. This paper develops a decision-theoretic model in which a single behavioural parameter — asymmetric error tolerance — captures the differential weight placed on AI versus human errors of equivalent objective severity. The parameter operates as a behavioural augmentation of adoption theory for the AI case: existing adoption-theory primitives continue to operate, but against a threshold that asymmetric tolerance shifts upward by a margin scaling with stakes. The model generates predictions about adoption distortions, regulatory stringency, and stakeholder heterogeneity, illustrated through worked examples across four AI governance domains. Three governance implications follow: frameworks calibrated against absolute rather than human-counterfactual benchmarks systematically over-regulate; stakeholder heterogeneity produces a democratic-alignment gap distinct from standard accountability concerns; and intervention design targeting counterfactual salience can attenuate the distortion. The paper opens an empirical agenda whose findings bear directly on AI governance design.
By Xun Wu; Hong Kong University of Science and Technology (Guangzhou)    Yvonne Chen; ShanghaiTech University    Ching Leong; National University of Singapore
Presented by: Xun Wu, Hong Kong University of Science and Technology (Guangzhou)
Session 73: Urban II July 30, 2026 16:40 to 18:10 Location: Vietnam Room (level 5)
Session Chair: Tomoki Fujii, Singapore Management University
Session type: invited
1. Property rights clarification and rural livelihood resilience: A land rental market participation pathway Abstract Building resilient rural livelihoods has become a major policy priority in developing countries facing structural transformation, market uncertainty, and climate-related shocks. Although existing studies emphasize the roles of assets, diversification, and social networks in shaping resilience, much less is known about whether institutional reforms—particularly property rights clarification—can strengthen livelihood resilience by enabling more efficient factor reallocation. This issue is especially important in collective or communal ownership systems, where ambiguous rights, insecure tenure, and high transaction costs often constrain households’ participation in land rental markets and reduce their ability to adjust livelihood strategies. We develop a market-enabling framework in which property rights clarification enhances livelihood resilience primarily by reducing transaction costs and strengthening tenure security, thereby facilitating land rental market participation. We focus on land rent-in as the primary transmission pathway. By enabling agricultural households to rent in land, consolidate fragmented plots, and expand farm scale, property rights clarification can stabilize farm-based livelihoods and improve households’ resilience. Beyond this mechanism, property rights clarification may also affect resilience through broader institutional effects, including improved collective governance and expanded property-based income opportunities. Using China’s Rural Collective Property Rights System Reform (RCPRSR) as an empirical case, this study examines whether and how property rights clarification enhances rural livelihood resilience through land rental market participation. We draw on data from the 2020 China Rural Revitalization Survey (CRRS) and construct a multidimensional livelihood resilience index covering overall resilience and three constituent dimensions: buffer capacity, self-organization capacity, and learning capacity. Empirically, we employ a conditional mixed process (CMP) model to address endogeneity arising from both observed and unobserved selection into reform exposure. We further assess the mediating role of land rent-in using CMP-based mediation analysis and generalized structural equation modeling (GSEM), and confirm the findings through a series of robustness checks. The results show that RCPRSR completion is associated with a significant increase in overall livelihood resilience. This positive effect is mainly driven by improvements in buffer capacity, suggesting that property rights clarification enhances households’ ability to cope with shocks by strengthening asset positions, securing land use, and improving production conditions. By contrast, the reform is associated with lower self-organization and learning capacity, indicating that institutional reforms that improve material resilience do not automatically strengthen collective action or adaptive learning. Mechanism analysis further identifies land rent-in as a key transmission pathway: RCPRSR significantly increases the likelihood that households rent in land, which in turn raises livelihood resilience, especially through buffer capacity. Heterogeneity analyses further show that while the reform consistently improves buffer capacity, its effects on self-organization and learning are more uneven across regions and village collective asset levels. Overall, this study contributes to the literature by linking property rights reform to livelihood resilience through an explicitly tested land market pathway. It shows that clarifying property rights can strengthen resilience by removing market barriers and enabling more efficient land-based strategies, but that these gains are dimension-specific and context-dependent. The findings suggest that property rights reform should be complemented by measures that strengthen land market institutions, local governance, and human capital to generate broader resilience gains.
By Chen Chen; Nanjing Agricultural University
Presented by: Chen Chen, Nanjing Agricultural University
2. The Density Dilemma: Land Use Regulation and the 15-Minute City Abstract Abstract: As the 15-minute city has moved from a planning concept to a prominent urban policy objective, understanding the conditions under which it can be realized has become increasingly important. In rapidly urbanizing developing countries, this issue depends not only on the spatial distribution of daily amenities, but also on how urban space is governed as room for outward expansion becomes more limited. Against this background, an important but underexplored question is whether land use regulation facilitates or hinders the development of the 15-minute city. Existing studies on land use regulation focus mainly on housing supply, land prices, employment, and urban expansion, whereas research on the 15-minute city remains centered on conceptual discussion, accessibility measurement, and planning assessment. The connection between land use regulation and proximity-based urban development remains insufficiently explored. China provides a particularly relevant setting for examining this question, because strong planning intervention and public control over urban land make development intensity an important channel through which governments shape urban space. Focusing on Floor Area Ratio Regulation (FARR), this study examines how land use regulation affects the development of the 15-minute city. Using panel data for Chinese municipal districts from 2012 to 2020, this study combines land transaction records, POI data, land cover data, population raster data, nighttime light data, and historical road network data. The dependent variable measures the share of residents in each district who can simultaneously access schools, hospitals, parks, and shops within 15 minutes, thereby capturing integrated daily accessibility rather than access to any single amenity. The independent variable is land use regulation, proxied by FARR. Instead of using the simple average legal FAR ceiling, the paper constructs an adjusted district-year FARR indicator from parcel-level land transaction data after controlling for parcel location, size, grade, and land price, which improves comparability across districts and over time. The empirical analysis mainly relies on a panel specification with municipal-district fixed effects and city-year fixed effects, and further evaluates robustness through alternative measures, sample exclusions, alternative fixed-effects structures, clustering adjustments, and an instrumental-variable strategy. The results show that looser land use regulation, reflected in a higher adjusted legal FAR ceiling, significantly promotes the development of the 15-minute city. Quantitatively, a 10% increase in the adjusted legal FAR ceiling corresponds to about 0.77 percentage points in the share of residents who can access schools, hospitals, parks, and shops within 15 minutes. Mechanism analysis further indicates that urban morphology is an important channel, through which stronger land use regulation reduces the development level of the 15-minute city by inducing a looser and more sprawling urban form. Heterogeneity analysis shows that this effect is more pronounced in economically more developed cities and in cities with stronger consumption demand. Across municipal districts within cities, it is more evident in peripheral districts and remains significant in districts with larger elderly populations. This study contributes to the literature in four respects. First, it extends research on the 15-minute city by examining land use regulation as an institutional driver of proximity-based urban development, thereby connecting a tool of urban spatial governance to a people-centered urban outcome. Second, it provides evidence from China, where rapid urban growth coexists with strong institutional constraints on urban development. By taking municipal districts rather than whole cities as the unit of analysis, it captures the intra-urban heterogeneity that is especially important for understanding both land use regulation and the 15-minute city. Third, it improves the measurement of both key variables by constructing an adjusted FARR indicator from parcel-level land transaction data and by measuring the 15-minute city as joint access to multiple essential amenities within a fixed time threshold. Fourth, it extends the analysis beyond average effects by identifying urban morphology as an important mechanism through which land use regulation affects the 15-minute city, and by showing that this relationship varies across city-level and district-level contexts. Together, these contributions provide a clearer institutional understanding of how land use regulation shapes the 15-minute city and offer more differentiated evidence for urban governance in rapidly urbanizing contexts. Keywords: Land use regulation; 15-minute city; Floor Area Ratio Regulation; Urban morphology JEL: R14; R52; O18
By Haoyang Wang; Southeast University
Presented by: Haoyang Wang, Southeast University
3. Issue Linkage and the Efficiency of Public Good Provision under Imperfect Monitoring Abstract We examine whether and how issue linkage can improve efficiency in repeated global public good provision under imperfect public monitoring. Motivated by global policy problems such as greenhouse gas mitigation, the analysis focuses on environments in which countries observe only their own contribution and a noisy public signal of total contributions. The study addresses two main questions: (1) whether linking a public good provision problem with an observable policy issue enhances efficiency and (2) under what conditions such improvements arise. We consider a repeated game with a continuous public signal whose noise is normally distributed. Within this framework, the key result is that issue linkage improves efficiency if and only if the optimal trigger strategy is sustainable as an equilibrium because linking multiple policy issues allows countries to reduce the probability of inefficient punishment on the equilibrium path. Sufficiently patient countries never deviate in the observable issue because the deviation is detected with certainty. Countries, therefore, focus on the deterrence of unobservable deviation in public good provision. In other words, issue linkage transfers the enforcement power of punishment from the observable issue to the unobservable issue. It makes the reversion to the static Nash equilibrium strategy more punishing, and as a result, each country believes that the others do not deviate and attributes the cause of low provision to the stochastic shock. Consequently, they can continue to cooperate under issue linkage even when they observe a relatively low level of the public good that would have triggered punishment if the issues were not linked. That is, countries become more tolerant of bad signals under issue linkage. We identify two distinct scenarios in which issue linkage yields a substantial efficiency gain. First, when countries are sufficiently patient but the public signal is highly noisy and/or the cost of public goods provision is very large, the equilibrium payoff in the standalone setting is low, implying significant inefficiency. In this case, if the gain from cooperation in the additional issue is sufficiently large, issue linkage induces greater tolerance toward unfavorable public signals. This reduces the likelihood of inefficient punishment triggered by noise and substantially mitigates efficiency losses. Second, even when the public signal is relatively precise and provision costs are moderate, cooperation may be unattainable in the standalone game due to insufficient patience (i.e., a low discount factor). In such cases, if the additional issue offers a sufficiently large cooperative gain and the temptation to deviate is small—meaning cooperation in the added issue is relatively easy—issue linkage enables the enforcement of cooperative trigger strategies. As a result, cooperation that is otherwise impossible becomes sustainable, leading to a drastic improvement in efficiency. These findings contribute to the literature on issue linkage by providing a positive perspective that contrasts with earlier pessimistic views. Previous studies, such as Ederington (2003, Economic Inquiry), emphasized the potential downside of linkage: when signals suggest possible deviations, punishments spill over across linked issues, potentially destroying cooperation that would have been sustainable if issues were treated separately. In this view, linkage amplifies the risk of inefficient punishment and reduces the overall welfare. Recent work by Wen and Zheng (2024, GEB) offers a more optimistic outlook by showing that, in models with discrete signals (particularly binary signals) and public randomization, punishment probabilities can be adjusted to avoid excessively harsh punishment. In their framework, the maximal equilibrium payoff under issue linkage remains unchanged relative to separate play, but issue linkage could lower the discount factor required to sustain optimal cooperation, thereby expanding the set of environments in which cooperation is feasible. Building on and extending this line of research, we demonstrate that similar—and in some cases stronger—efficiency improvements arise in a continuous-signal environment with normally distributed noise. The central mechanisms are the reduction of erroneous punishment under noisy monitoring and the strengthening of incentives through additional cooperative rents. This highlights a novel mechanism through which issue linkage mitigates inefficiencies caused by imperfect monitoring. We also clarify the economic environments in which issue linkage is most beneficial, particularly highlighting the roles of patience, signal noise, cost levels, and the structure of incentives in the linked issue.
By Shuichi Ohori; Kansai University    Katsunori Ohta; Kansai University    Yuji Tamura; La Trobe University
Presented by: Katsunori Ohta, Kansai University
4. China's Urban Green Transition: The Role of Digital Economy and Environmental Policy Abstract This study examines China's urban green transition using Chinese panel data. We first develop a general-equilibrium framework to examine how the expansion of the digital economy can improve cleaner production and population health through improved productivity. The economy consists of a representative consumer, a government, and three production sectors, which include traditional goods sector that generates pollution as a byproduct, environmentally protective goods sector, and digital goods sector. Consumer welfare depends on material consumption and population health, where the latter is modeled as an increasing function of expenditures on environmentally protective goods (e.g., masks, air purifiers, healthcare-related consumption) and a decreasing function of exposure to environmental pollution, which is produced as a by-product of traditional numeraire goods as well as city-level livability measure. The government levies an environmental tax on emissions and uses revenues to finance public spending, with a portion transferred to households, linking environmental regulation to private consumption possibilities and health. The model yields equilibrium conditions that jointly determine sectoral outputs, factor allocations, consumption choices, pollution emissions, and health. Comparative statics highlight that development of digital economy can lead to the reduction of emissions and increased level of welfare. Our theoretical model also offers the condition for optimal emissions tax. We then calibrate model parameters to match observed statistics from provincial and city-level statistics in China on life expectancy, consumption expenditures, pollutant-equivalent emissions, infrastructure measures, sectoral value added, employment, and investment, complemented by firm-level environmental tax, and emissions disclosures for estimating the effective tax rate, among others. We capture the city-level livability through built environment and infrastructure measures such as built-up area, per-capita road length, and population scale. Using the calibrated parameter, we compute the optimal environmental tax, which is substantially higher than the current rates. We also conduct counterfactual policy simulations to promote urban green transition.
By Han Cai; Nanjing University of Science & Technology    Tomoki Fujii; Singapore Management University
Presented by: Tomoki Fujii, Singapore Management University