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CLOSED-FORM IDENTIFICATION OF DYNAMIC DISCRETE CHOICE MODELS WITH PROXIES FOR UNOBSERVED STATE VARIABLES
Published online by Cambridge University Press: 06 March 2017
Abstract
Proxies for unobserved skills and technologies are increasingly available in empirical data. For dynamic discrete choice models of forward-looking agents where a continuous state variable is unobserved but its proxy is available, we derive closed-form identification of the structure by explicitly solving integral equations. In the first step, we derive closed-form identification of Markov components, including the conditional choice probabilities and the law of state transition. In the second step, we plug in these first-step identifying formulas to obtain primitive structural parameters of dynamically optimizing agents.
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- Copyright © Cambridge University Press 2017
Footnotes
The authors can be reached at yhu@jhu.edu and sasaki@jhu.edu. We benefited from useful comments by the editor (Peter C.B. Phillips), the coeditor (Arthur Lewbel), three anonymous referees, seminar participants at Cambridge, Centre de Recherche en Économie et Statistique Paris, George Washington, London School of Economics, Oxford, Rice, Shanghai University of Finance and Economics, Texas A&M, Toulouse School of Economics, University College London, Wisconsin-Madison, 2013 Greater New York Metropolitan Area Econometrics Colloquium, and 2014 Shanghai Econometrics Workshop. The usual disclaimer applies.
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