A simulation estimator for dynamic models of discrete choice

Published

Journal Article

This paper analyses a new estimator for the structural parameters of dynamic models of discrete choice. Based on an inversion theorem due to Hotz and Miller (1993), which establishes the existence of a one-to-one mapping between the conditional valuation functions for the dynamic problem and their associated conditional choice probabilities, we exploit simulation techniques to estimate models which do not possess terminal states. In this way our Conditional Choice Simulation (CCS) estimator complements the Conditional Choice Probability (CCP) estimator of Hotz and Miller (1993). Drawing on work in empirical process theory by Pakes and Pollard (1989), we establish its large sample properties, and then conduct a Monte Carlo study of Rust’s (1987) model of bus engine replacement to compare its small sample properties with those of Maximum Likelihood (ML). © 1994 The Review of Economic Studies Limited.

Full Text

Duke Authors

Cited Authors

  • Hotz, VJ; Miller, RA; Sanders, S; Smith, J

Published Date

  • January 1, 1994

Published In

Volume / Issue

  • 61 / 2

Start / End Page

  • 265 - 289

Electronic International Standard Serial Number (EISSN)

  • 1467-937X

International Standard Serial Number (ISSN)

  • 0034-6527

Digital Object Identifier (DOI)

  • 10.2307/2297981

Citation Source

  • Scopus