Identifying dynamic discrete choice models off short panels

Published

Journal Article

© 2019 Elsevier B.V. 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.

Full Text

Duke Authors

Cited Authors

  • Arcidiacono, P; Miller, RA

Published Date

  • April 1, 2020

Published In

Volume / Issue

  • 215 / 2

Start / End Page

  • 473 - 485

Electronic International Standard Serial Number (EISSN)

  • 1872-6895

International Standard Serial Number (ISSN)

  • 0304-4076

Digital Object Identifier (DOI)

  • 10.1016/j.jeconom.2018.12.025

Citation Source

  • Scopus