I am an assistant professor at Southwestern University of Finance and Economics (SWUFE), China.

I am a theorist with focus in decision theory and information economics. I am motivated in understanding the process of how economic agents perceive risk, uncertainty and information, update beliefs, and make corresponding economic decisions.

Prior to joining SWUFE, I worked as a postdoctoral fellow at IGIER, Bocconi. I obtained my PhD at the Department of Economics, National University of Singapore (NUS), and my bachelor’s degree in mathematics and physics and double degree in economics from Tsinghua University. Here is my CV.

Working Papers

1. Consistency and Pairwise Consistency (with Yi-Chun Chen)

We study the finite Harsanyi model where each agent’s type is associated with a posterior belief over some fundamental uncertainty and type profiles of other agents. We show that if the agents’ posteriors have full support, the model admits a common prior (i.e., is consistent in Harsanyi’s sense) if and only if any pair of agents have a common prior. We extend the result to Aumann models where posteriors need not have full support but satisfy a condition called double irreducibility which strengthens the irreducibility condition of Samet (1998). Our results imply circumstances where characterizations of consistency such as the no-trade theorems and the convergence of higher-order expectations reduce to the corresponding characterizations for pairwise consistency.

2. Axiomatizing Correlation Preference (with Yi-Chun Chen, Soo Hong Chew)

The importance of correlation sensitivity in binary choice is evident in the increasing influence of regret and salience in the decision-making literature. We begin with a general framework to investigate choice between pairs of possibly correlated lotteries. This encompasses the development from regret theory reflecting counterfactual thinking arising from state-by-state comparisons in pairs of interdependent lotteries to salience theory, which incorporates sensorydriven contrast effects on probability weighting. We axiomatize two classes of preference corresponding respectively to the correlation counterparts of the independence axiom for expected utility and two axioms in non-expected utility characterizing weighted utility. The resulting correlation expected utility and correlation weighted utility can be discriminated using recent evidence of correlationsensitive Allais behavior which supports the latter model.

3. How to Ask for Belief Statistics without Distortion? (with Yi-Chun Chen, Ruoyu Wang)

Belief elicitation is ubiquitous in experiments but can distort behavior in the main tasks. We study when, and how, an experimenter can ask for a series of action-dependent belief statistics after a subject chooses an action, while incentivize truthful reports without distorting the subject’s optimal action in the main experimental tasks. We first propose a novel mechanism called the Counterfactual Scoring Rule (CSR), which achieves such nondistortionary elicitation of any single belief statistic by decomposing it into supplemental action-independent statistics. In contrast, when eliciting a fixed set of belief statistics without such decomposition, we show that robust nondistortionary elicitation is achievable if and only if the questions satisfy a joint alignment condition with the task payoff. The necessity of joint alignment is established through a graph theoretical approach, while its sufficiency follows from invoking an adaptation of the Becker–DeGroot–Marschak mechanism. Our characterization applies to experiments with general task-payoff structures and belief elicitation questions.

4. Age Discrimination in Hiring: Evidence from Online Job Ads (with Qinyue Luo, Liaoliang Zhang)

We analyze explicit age discrimination in an online job market and job seekers’ responses to it in China, using nearly 8 million job postings with ad-level group characteristics of applicants. In nearly half of job postings, employers explicitly state age restrictions and often exclude older applicants. To rationalize this, we develop a dynamic game in which older workers incur a disutility from employment at a biased firm, while biased employers trade off a larger applicant pool against higher screening costs. Consistent with the model’s predictions, empirical results show that age restrictions encourage younger workers but discourage middle-aged and older workers, although some ineligible candidates still apply to high-wage or high-skill positions. Firms are more likely to impose age limits when jobs demand high work intensity, low skill levels, or when they face greater hiring costs and weaker market competition. Our results highlight that explicit age preferences, by altering both the composition of applicants and the costs of screening, can sustain discriminatory hiring equilibria even in competitive labor markets.

Teaching

PhD courses: Behavioral Economics, Mathematics for Economists UG courses: Market and Mechanism Design