Research
Working Papers
Mixture-Dependent Preference for Commitment (online appendix) R&R JET
The literature on temptation and self-control is motivated by evidence of a preference for commitment. This literature has typically put forth models for preferences over menus of lotteries that satisfy the Independence axiom. Independence requires that the ranking of two menus is not affected if each is mixed (probabilistically) with a common third menu. In particular, the preference for commitment is invariant under Independence. We argue that intuitive behavior may require that the preference for commitment be affected by such mixing, and hence be mixture-dependent. To capture such behavior, we generalize Gul and Pesendorfer (2001) by replacing their Independence axiom with a suitably adapted version of the Mixture-Betweenness axiom of Chew (1989)-Dekel (1986). The result is an implicit utility model in which utility is defined as the unique solution of an equation that depends on the agent's commitment and temptation rankings, neither of which satisfies the Independence axiom. Axiomatizing the model involves a novel extension of the Mixture Space Theorem to preferences that satisfy Mixture-Betweenness. Since the Mixture Space Theorem is central to decision theory, this extension is potentially useful for addressing issues in economics other than temptation and self-control.
An Axiomatic Approach to the Law of Small Numbers (joint with Jawwad Noor) R&R TE
With beliefs over the outcomes of coin-tosses as our primitive, we formalize the Law of Small Numbers (Tversky and Kahneman (1974)) by an axiom that expresses a belief that the sample mean of any sequence will tend towards the coin’s perceived bias along the entire path. The agent is represented by a belief that the bias of the coin is path-dependent and self-correcting. The model is consistent with the evidence used to support the Law of Small Numbers, such as the Gambler’s Fallacy. In the setting of Bayesian inference, we show how learning is affected by the interplay between two potentially opposing forces: a belief in the absence of streaks and a belief that the sample mean will tend to the true bias. We show that, unlike other learning results in the literature (Rabin (2002), Epstein, Noor, and Sandroni (2010)), the latter force ensures that the agent at least admits the true parameter as possible in the limit, if not learn with certainty that it is true. In an evolutionary setting, we show that agents who believe in the Law of Small Numbers are never pushed out of the evolutionary race by “standard” agents who correctly understand randomness
Updating under Imprecise Information (joint with Yi-Hsuan Lin) submitted
This paper models an agent that ranks actions with uncertain payoffs after observing a signal that could have been generated by multiple objective information structures. Under the assumption that the agent's preferences conform to the multiple priors model (Gilboa and Schmeidler (1989)) ), we show that a simple behavioral axiom characterizes a generalization of Bayesian Updating. Our axiom requires that whenever all possible sources of information agree that it is more 'likely' for an action with uncertain payoffs to be better than one with certain payoffs, the agent prefers the former. We also provide axiomatizations for several special cases. Finally, we consider the situation where the informational content of a signal is purely subjective. We characterize the existence of a subjective set of information structures under full Bayesian updating for two extreme cases: (i) No ex-ante state ambiguity, and (ii) No signal ambiguity.
Publications
Revealed Preference and the Subjective State Space Hypothesis , Journal of Mathematical Economics Volume 82, May 2019, Pages 61-68
Dekel et al. (2001) extends Kreps’ (1979) model for preference over menus of deterministic alternatives to a model for preference over menus of lotteries. They show that a simple set of axioms characterizes a representation that can be interpreted as if the agent is uncertain about her future tastes. This taste uncertainty is summarized by a set of possible future preferences which is referred to as the subjective state space. Their approach is axiomatic; thus, testability requires that the entire preference order be observable. This paper provides corresponding revealed preference analysis assuming that only finitely many choices are observed. For a particular class of data sets, it is shown that the characterizing conditions can be reformulated as nonlinear systems of inequalities for which the existence of solutions can be verified using numerical methods. The analysis covers the case where available data involves only menus of alternatives (and not lotteries). Hence, our results also provide revealed preference characterizations for Kreps (1979).
Similarity-based mistakes in choice, with L. Ülkü, Journal of Mathematical Economics Volume 61, December 2015, Pages 152-156
We characterize the following choice procedure. The decision maker is endowed with two binary relations over alternatives, a preference and a similarity. In every choice problem she includes in her choice set all alternatives which are similar to the best feasible alternative. Hence she can, by mistake, choose an inferior option because it is similar to the best. We characterize this boundedly rational behavior by suitably weakening the rationalizability axiom of Arrow (1959). We also characterize a variation where the decision maker chooses alternatives on the basis of their similarities to attractive yet infeasible options. We show that similarity-based mistakes of either kind lead to cyclical behavior.
Work in Progress
Bayesian Adaptive Choice Experiments (joint with Marshall Drake, Neil Thakral, and Linh Tô)
Package
Alpha MaxMin Updating Rules for Ambiguous Information (joint with Yi-Hsuan Lin)
Optimal Ambiguity Perception (joint with Norio Takeoka and Jianming Xia)
Deception under the Veil of Noise (joint with Jawwad Noor)
Other Publications
Implications of the Patient Protection and Affordable Care Act on Insurance Coverage and Rehabilitation Use Among Young Adult Trauma Patients with Cheryl Zogg, John Scott, Lindsey Wolf , Thomas Tsai , Peter Najjar, Olubode Olufajo, Eric Schneider, Elliott Haut, Adil Haider, Joseph Canner, JAMA surgery Volume 151, December 2016
Componentes Principales: Las Dimensiones de la Confianza with Kin Gutierrez Olivares y Max Mergenthaler, Laberintos y Infinitos No 39, Pg 35-41 2015