We discuss the identification and estimation of discrete games of complete information. Following Bresnahan and Reiss (1990, 1991), a discrete game is a generalization of a standard discrete choice model where utility depends on the actions of other players. Using recent algorithms to compute...

A basic problem in applied settings is that different parameters may apply to the same model in different populations. We address this problem by proposing a method using moment trees; leveraging the basic intuition of a classification tree, our method partitions the covariate space into...

We estimate a structural model of the market for automatic teller machines (ATMs) in order to evaluate the implications of regulating ATM surcharges on ATM entry and consumer and producer surplus. We estimate the model using data on firm and consumer locations, and identify the parameters of the...

We study the transmission of monetary policy through bank securities portfolios using granular supervisory data on U.S. bank securities, hedging positions, and corporate credit. Banks that experienced larger losses on their securities during the 2022-2023 monetary tightening cycle extended less...

This paper studies the asymptotic relationship between Bayesian model averaging and post-selection frequentist predictors in both nested and nonnested models. We derive conditions under which their difference is of a smaller order of magnitude than the inverse of the square root of the sample...

We develop tests for common values at first-price sealed-bid auctions. Our tests are nonparametric, require observation only of the bids submitted at each auction, and are based on the fact that the winner's curse' arises only in common values auctions. The tests build on recently developed...

We study the identification and estimation of preferences in hedonic discrete choice models of demand for differentiated products. In the hedonic discrete choice model, products are represented as a finite dimensional bundle of characteristics, and consumers maximize utility subject to a budget...

In academic and policy circles, there has been considerable interest in the impact of "big data" on firm performance. We examine the question of how the amount of data impacts the accuracy of Machine Learned models of weekly retail product forecasts using a proprietary data set obtained from...

Using data from the Panel Study of Income Dynamics (PSID) we specify, estimate and simulate a dynamic structural model of housing demand. Our model generalizes previous applied econometric work by incorporating realistic features of the housing market including non-convex adjustment costs from...

We propose a new strategy for a pervasive problem in the hedonics literature--recovering hedonic prices in the presence of time-varying correlated unobservables. Our approach relies on an assumption about homebuyer rationality, under which prior sales prices can be used to control for...