Research

Cognitive dissonance is the internal tension individuals feel when their past actions are inconsistent with their beliefs or attitudes. I propose an intrapersonal game to model a decision-maker (DM) who distorts her beliefs to mitigate cognitive dissonance from past choices. Two selves make sequential, observable decisions, with unobservable belief manipulation occurring in the interim stage between them. The subgame perfect Nash equilibria are characterized by tractable axioms on choice patterns, with parameters identifiable from choice data. I demonstrate that the model is a useful tool for studying path dependence in decision-making. It matches a variety of experimental and real-world evidence consistent with cognitive dissonance theory. Applying the model provides new insights into existing topics, including add-on selling, behavioral poverty traps, and the value of information.

Commutativity is a normative criterion of aggregation and updating stating that the aggregation of expert posteriors should be identical to the update of the aggregated priors. I propose a thought experiment that raises questions about the normative appeal of Commutativity. I propose a weakened version of Commutativity and show how that assumption plays central roles in the characterization of linear belief aggregation, multiple-weight aggregation, and an aggregation rule which can be viewed as the outcome of a game played by “dual-selves,” Pessimism and Optimism. Under suitable conditions, I establish equivalences between various relaxations of Commutativity and classic axioms for decision-making under uncertainty, including Independence, C-Independence, and Ambiguity Aversion.

I characterize an overprecise updating model, in which an agent systematically overestimates the informativeness of their posterior beliefs. The model captures the intrapersonal trade-off between mitigating risk and avoiding distorted posteriors. My characterization establishes a connection between laboratory evidence and the psychological mechanism driving the desire for uncertainty reduction. I demonstrate that overprecision contributes to cognitive biases such as overinference, confirmation bias, and overoptimism. For an agent receiving a sequence of signals that contradict her initial belief, overprecision leads to initially updating too slowly, followed by overly rapid updates.