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Published online by Cambridge University Press:  21 March 2016

Le-Yu Chen*
Academia Sinica
*Address correspondence to Le-Yu Chen, Institute of Economics, Academia Sinica, Nankang, Taipei, 115, Taiwan; e-mail:
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This paper presents semiparametric identification results for the Rust (1994) class of discrete choice dynamic programming (DCDP) models. We develop sufficient conditions for identification of the deep structural parameters for the case where the per-period utility function ascribed to one choice in the model is parametric but the distribution of unobserved state variables is nonparametric. The proposed identification strategy does not rely on availability of the terminal period data and can therefore be applied to infinite horizon structural dynamic models. Identifying power comes from assuming that the agent’s per-period utilities admit continuous choice-specific state variables that are observed with sufficient variation and satisfy certain conditional independence assumptions on the joint time series of observables. These conditions allow us to formulate exclusion restrictions for identifying the primitive structural functions of the model.

Copyright © Cambridge University Press 2016 


This paper is a significant revision of my earlier Cemmap working papers (Chen (2007, 2009)) and the first chapter of my doctoral thesis (Econometric Inference Involving Discrete Indicator Functions, 2009, University College London). I thank my advisor Sokbae Lee for his encouragement and insightful advice on this research work. I am grateful to the co-editor and two anonymous referees for valuable comments and suggestions on previous versions of the paper. I am indebted to the editor Peter Phillips for constructive advice and comments which have considerably improved the presentation of this paper. I also benefited from helpful comments provided by Richard Blundell, Andrew Chesher, Hidehiko Ichimura, Oliver Linton, Pedro Mira, Lars Nesheim, Adam Rosen, and seminar participants at Aarhus, University of St. Gallen, Alicante, Academia Sinica, UCL/Cemmap and 2009 Far East and South Asia Meeting of the Econometric Society.



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