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This article reviews the econometrics of static games, with a focus on discrete-choice cases. These models have been used to study a rich variety of empirical problems, ranging from labor force participation to entry decisions. We outline the components of a general game and describe the problem of doing robust inference in the presence of multiple solutions, as well as the different econometric approaches that have been applied to tackle this problem. We then describe the specific challenges that arise in different variations of these models depending on whether players are assumed to have complete or incomplete information, as well as whether or not nonequilibrium play is allowed. We describe the results in 2 × 2 games (the most widely studied games in econometrics), and we present extensions and recent results in games with richer action spaces. Areas for future research are also discussed.
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