Higher-Order Beliefs and (Mis)Learning from Prices
with Kevin He
American Economic Journal: Microeconomics, Accepted
In an incomplete-information Cournot duopoly game, higher-order belief misperceptions induce mistaken inferences about price elasticity.
Exaggerating signal correlation (a la projection bias) is beneficial when learning elasticity from prices, but harmful when dogmatic beliefs about elasticity are held.
Results from this paper originally appeared in Evolutionarily Stable (Mis)specifications: Theory and Applications.
Research Registries and the Credibility Crisis:
An Empirical and Theoretical Investigation
with Eliot Abrams and John A. List
Economic Journal, Conditionally Accepted (pending final checks)
We evaluate the performance of research registries as a solution to the credibility crisis, focusing primarily but not exclusively on the AEA RCT Registry.
Empirically, we document a number of patterns and evaluate the extent to which the file drawer problem and p-hacking appear to be mitigated. Theoretically, we provide a model of registration and use it to discuss the incentives driving registration patterns and guide policy prescriptions.
Retractions: Updating from Complex Information
with Duarte Gonçalves and Jack Willis
Review of Economic Studies, Forthcoming
In a belief-updating experiment, we find that subjects underreact to information when it comes in the form of a retraction.
We argue retractions — the provision of indirect information — are treated as more complex than equivalent direct information.
With a Grain of Salt:
Investor Reactions to Uncertain News and (Non)Disclosure
with Beatrice Michaeli and Elyashiv Wiedman
Journal of Accounting and Economics, 2026, Forthcoming
Uncertainty about whether external news is accurate creates an incentive for managers to delay disclosure decision. A consequence is that the market's expectation of firm value may worsen with better news.
The model introduces uncertain informativeness of external news into a dynamic disclosure setting.
Misspecified Learning and Evolutionary Stability
with Kevin He
Journal of Economic Theory, 2025, 230: 106082
We introduce a selection criterion on behavioral biases in environments with learning.
The framework extends the indirect evolutionary approach to model selection, identifying new stability phenomena that emerge as a result.
Results from this paper originally appeared in Evolutionarily Stable (Mis)specifications: Theory and Applications.
Identifying Wisdom (of the Crowd): A Regression Approach
Journal of Political Economy: Microeconomics, 2025, 3(4): 798-826
Blackwell experiments can be determined via a regression procedure. Priors solve an eigenvector equation derived from this procedure.
The findings are relevant to the crowd wisdom problem, and have implications for the geometric structure of information.
Learning Underspecified Models
with In-Koo Cho
Journal of Economic Theory, 2025, 226: 106015
We present an algorithm which, by positing linear demand, allows the monopolist to learn the optimal price even if demand is non-linear.
Our framework introduces the concepts of a dominant algorithm that is simplest.
Iterative Weak Learnability and Multiclass Adaboost
witH IN-KOO CHO AND CHENG DING
Proc. of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024, 466-477
We propose a procedure for multi-label classification problems based on iteratively eliminating worst-performing labels.
We identify desireable theoretical properties of our procedure and illustrate its practical performance.
False Positives and Transparency
American Economic Journal: Microeconomics, 2022, 14(2): 478-505.
Lack of transparency over research methods can induce bias. But the incentive to de-bias may lead to more informative experiments.
The model introduced is one of costly communication with partial (sender) commitment.
Informational Robustness in Intertemporal Pricing
with Xiaosheng Mu
Review of Economic Studies, 2021, 88(3): 1224-1252.
Constant price paths deliver the optimal profit guarantee when a seller does not know how buyers learn about a product.
Formally, this paper introduces an informationally robust approach into the dynamic pricing literature.
© 2025