Working Papers
Robust Predictions in Information Acquisition Games (with Tommaso Denti, abstract in Economics and Computation 2024)
We derive robust predictions in games preceded by costly information acquisition, valid across all specifications of players’ learning abilities. Relative to environments with exogenously given information, costly learning restricts behavior and reduces welfare. These behavioral restrictions exhibit a stark dichotomy: they are either highly stringent or virtually negligible. Stringent restrictions occur in structured environments characterized by global indifferences, while in generic games, behavioral predictions under endogenous and exogenous information coincide. The welfare implications, however, differ systematically: optimal policy often depends on whether information is given or acquired. We illustrate the usefulness of our tools for robust policy analysis through applications to regime-change games, informational simplicity, and mechanism design with aftermarkets.
Predicting Choice from Information Costs (with Elliot Lipnowski, abstract in Economics and Computation 2023, R&R @ Journal of Economic Theory)
An agent acquires a costly flexible signal before making a decision. We explore the degree to which knowledge of the agent's information costs help predict her behavior. We establish an impossibility result: learning costs alone generate no testable restrictions on choice without also imposing constraints on actions' state-dependent utilities. By contrast, for most utility functions, knowing both the utility and information costs enables a unique behavioral prediction. Finally, we show that for smooth costs, most choices from a menu uniquely pin down the agent's decisions in all submenus.
Monopoly, Product Quality, and Flexible Learning (with Jeffrey Mensch, abstract in Economics and Computation 2024)
A seller offers a buyer a schedule of transfers and associated product qualities, as in Mussa and Rosen (1978). After observing this schedule, the buyer chooses a flexible costly signal about his type. We show it is without loss to focus on a class of mechanisms that compensate the buyer for his learning costs. Using these mechanisms, we prove the quality always lies strictly below the efficient level. This strict downward distortion holds even if the buyer acquires no information or when the buyer's posterior type is the highest possible given his signal, reversing the ``no distortion at the top'' feature that holds when information is exogenous.
Focus, Then Compare (with: Kai Steverson)
We study the following random choice procedure. First, the agent focuses on an option at random from the set of available options. Then, she compares the focal option to each other available alternative. Comparisons are binary, random and independent of each other. The agent chooses the focal option if it passes all comparisons favorably. Otherwise, the agent draws a new focal option with replacement. We characterize the procedure's revealed preference implications, show that it accommodates the Attraction effect and Choice overload, and discuss how to conduct welfare comparisons. We conclude by showing that while utility maximization is the procedure's unique deterministic special case, nearly deterministic versions of the procedure can exhibit context effects.