Two potentially asymmetric players compete for a prize of common value, which is initially unknown, by exerting efforts. A designer has two instruments for contest design. First, she decides whether and how to disclose an informative signal of the prize value to players. Second, she sets the...

Despite extensive use of bargaining models in economics and despite Becker's insistence on the importance of altruism in families, the theoretical literature on bargaining ignores altruism and assumes that everyone is an egoist. This paper shows that incorporating altruism into cooperative...

We propose an equilibrium theory of data-driven antitrust oversight in which regulators launch investigations on the basis of suspicious bidding patterns and cartels can adapt to the statistical screens used by regulators. We emphasize the use of asymptotically safe tests, i.e. tests that are...

We study the ability of multi-group teams to undertake binary projects in a decentralized environment. The equilibrium outcomes of our model display familiar features in collaborative settings, including inefficient gradualism, inaction, and contribution cycles, wherein groups alternate taking...

Immigrants in economies with a dominant native language exhibit substantial heterogeneities in language acquisition of the majority language. We model partial equilibrium language acquisition as an equilibrium phenomenon. We consider an environment where heterogeneous agents from various...

We propose a general simulation-based procedure for estimating quality of approximate policies in heterogeneous-agent equilibrium models, which allows to verify that such approximate solutions describe a near-rational equilibrium. Our procedure endows agents with superior knowledge of the future...

The primary motivation behind quantitative modeling in international trade and many other fields is to shed light on the economic consequences of policy changes. To help assess and potentially strengthen the credibility of such quantitative predictions we introduce an IV-based goodness-of-fit...

Missing data for return predictors is a common problem in cross sectional asset pricing. Most papers do not explicitly discuss how they deal with missing data but conventional treatments focus on the subset of firms with no missing data for any predictor or impute the unconditional mean. Both...

We survey the nascent literature on machine learning in the study of financial markets. We highlight the best examples of what this line of research has to offer and recommend promising directions for future research. This survey is designed for both financial economists interested in grasping...

We propose a statistical model of differences in beliefs in which heterogeneous investors are represented as different machine learning model specifications. Each investor forms return forecasts from their own specific model using data inputs that are available to all investors. We measure...