Identifying dynamic discrete choice models off short panels

This paper analyzes the identification of flow payoffs and counterfactual choice probabilities (CCPs) in single-agent dynamic discrete choice models. We develop new results on non-stationary models where the time horizon for the agent extends beyond the length of the data (short panels). We show tha...

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Bibliographic Details
Published inJournal of econometrics Vol. 215; no. 2; pp. 473 - 485
Main Authors Arcidiacono, Peter, Miller, Robert A.
Format Journal Article
LanguageEnglish
Published Amsterdam Elsevier B.V 01.04.2020
Elsevier Sequoia S.A
Subjects
Conditional choice probabilities
Counterfactual thinking
Data analysis
Decision making models
Discrete choice
Discrete element method
Dynamic discrete choice
Economic models
Identification
Innovations
Nonstationary models
Policy making
Probability
C53
Conditional choice probabilities
Dynamic discrete choice
C35
Nonstationary models
Identification
C61
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Summary:This paper analyzes the identification of flow payoffs and counterfactual choice probabilities (CCPs) in single-agent dynamic discrete choice models. We develop new results on non-stationary models where the time horizon for the agent extends beyond the length of the data (short panels). We show that counterfactual CCPs in short panels are identified when induced by temporary policy changes affecting payoffs, even though the utility flows are not. Counterfactual CCPs induced by innovations to state transitions are generally not identified unless the model exhibits single action finite dependence, and the payoffs of those actions establishing single action finite dependence are known.
ISSN:0304-4076
1872-6895
DOI:10.1016/j.jeconom.2018.12.025