Affiliation:
1. Department of Economics, Harvard University
2. Stern School of Business, New York University
3. Department of Economics, University of Toronto
Abstract
Dynamic discrete choice (DDC) models are not identified nonparametrically, but the non‐identification of models does not necessarily imply the nonidentification of counterfactuals. We derive novel results for the identification of counterfactuals in DDC models, such as non‐additive changes in payoffs or changes to agents' choice sets. In doing so, we propose a general framework that allows the investigation of the identification of a broad class of counterfactuals (covering virtually any counterfactual encountered in applied work). To illustrate the results, we consider a firm entry/exit problem numerically, as well as an empirical model of agricultural land use. In each case, we provide examples of both identified and nonidentified counterfactuals of interest.
Funder
European Research Council
Seventh Framework Programme
Agence Nationale de la Recherche
Subject
Economics and Econometrics
Cited by
13 articles.
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