``Revealed Reciprocity" Journal of Economic Theory (2025)
We propose and characterize the General Reciprocity Model in a framework of context-dependent choice. In the model, the second mover can establish their own rules regarding when or why to reciprocate. The model disentangles the baseline social preference from reciprocity: reciprocity occurs when people deviate from their baseline preference due to the context in which the first mover's choice is made. Our model provides a condition to reveal reciprocity, which aligns with the standard model-free criterion commonly used to identify reciprocity in experimental settings. Thus, it enables us to examine the behavioral foundation of this criterion through the lens of our model. Moreover, in some situations where the standard criterion cannot be applied due to imperfect data, our model offers an additional condition to reveal reciprocity by imposing assumptions about the second mover’s psychological processes. Finally, we apply the model to several past experiments, demonstrating how it identifies reciprocity.
``Guilt Moderation" Economic Theory (2023)
We propose and axiomatize the inequality-averse model with rank-dependent (dis-)utility under risk and uncertainty. The model highlights an important linkage, Guilt Moderation, between different other-regarding behaviors: when choices are risky, decision maker feels less guilt by assigning more weight to the fairer outcomes, creating a tendency to exhibit self-centered (or altruistic) behavior when outcomes are mixed with a fairer (or unfairer) outcome. Our model provides a unifying explanation for two seemingly distinct reversal behaviors known in the literature as moral wiggle room and ex-ante fairness for you that put into question the consistency of attitudes towards inequality in the presence of uncertainty. Moreover, we characterize guilt moderation with the reversal behaviors and risk preference for others. Lastly, the model sheds light on the self-other risk attitudes gap and increased envy in wage transparency.
``Disentangling Attention and Utility Channels in Recommendations'' with Yusufcan Masatlioglu (under review)
The empirical literature argues that recommendation can influence demand through two distinct channels: i) by enlarging awareness (attention), or ii) by altering preferences (utility). In this paper, we develop a framework to study these two channels using a parsimonious parametric model, which can be characterized by simple and intuitive behavioral postulates. We show that our simple model can accommodate a wide range of empirical observations. Also, our unique identification enables us to measure the degree to which each channel affects choice behavior and to make out-of-sample predictions for counterfactual analysis for policy design purposes.
``Attention Overload" with Matias Cattaneo, Xinwei Ma, Yusufcan Masatlioglu (Revise and Resubmit, Journal of Political Economy)
We introduce an Attention Overload Model that captures the idea that alternatives compete for the decision maker’s attention, and hence the attention that each alternative receives decreases as the choice problem becomes larger. Using this non-parametric restriction on the random attention formation, we show that a fruitful revealed preference theory can be developed and provide testable implications on the observed choice behavior that can be used to (point or partially) identify the decision maker’s preference and attention frequency. We then enhance our attention overload model to accommodate heterogeneous preferences. Due to the nonparametric nature of our identifying assumption, we must discipline the amount of heterogeneity in the choice model: we propose the idea of List-based Attention Overload, where alternatives are presented to the decision makers as a list that correlates with both heterogeneous preferences and random attention. We show that preference and attention frequencies are (point or partially) identifiable under nonparametric assumptions on the list and attention formation mechanisms, even when the true underlying list is unknown to the researcher. Building on our identification results, for both preference and attention frequencies, we develop econometric methods for estimation and inference that are valid in settings with a large number of alternatives and choice problems, a distinctive feature of the economic environment we consider. We also provide a software package in R implementing our empirical methods, and illustrate them in a simulation study.
``Social Preference, Reversals, and Non-isolation'' with Keaton Ellis (Revise and Resubmit, Games and Economic Behavior)
Recent evidence suggests that non-isolation behavior could significantly impact laboratory experiments using the random problem selection (RPS) payment mechanism through lottery integration. Theoretical work also highlights social preferences that can violate state-wise monotonicity, a necessary and sufficient condition for incentive compatibility with the RPS payment mechanism in case of lottery integration. Additionally, non-isolation can influence decisions through non-consequential dynamic concerns. In a series of three simple and parsimonious experiments and three tests, we examine the occurrence of the two kinds of non-isolation and reversal behaviors. We find significant evidence for positive reversal behavior, where subjects are more likely to make a fair choice if there is an alternative possible realization of an unfair outcome (which they chose themselves). In addition, the lower bounds for the prevalence of non-isolation in terms of lottery integration and dynamic non-consequential concern are estimated to be approximately 10% and 20%, respectively.
``Frame-Dependent Random Utility'' with Yusufcan Masatlioglu (under review)
We explore the influence of framing on decision-making, where some products are framed (e.g., displayed, recommended, endorsed, or labeled). We introduce a novel choice function that captures observed variations in framed alternatives. Building on this, we conduct a comprehensive revealed preference analysis, employing the concept of frame-dependent utility using both deterministic and probabilistic data. We demonstrate that simple and intuitive behavioral principles characterize our frame-dependent random utility model (FRUM), which offers testable conditions even with limited data. Finally, we introduce a parametric model to increase the tractability of FRUM. We also discuss how to recover the choice types in our framework.
``Revealed Attentional Influence'' with Yi-Husan Lin and Chung-Hao Sheu
``Motivational Karmic Investment'' with Haomin He and King King Li
``Belief Bias, Source Preference, and Preference for Robo-Advisor'' with Haomin He and King King Li
``Revealed Moral Consideration'' with Zhenxun Liu