Practical methods for estimation of dynamic discrete choice models

Published

Journal Article

Many discrete decisions are made with an eye toward how they will affect future outcomes. Formulating and estimating the underlying models that generate these decisions is difficult. Conditional choice probability (CCP) estimators often provide simpler ways to estimate dynamic discrete choice problems. Recent work shows how to frame dynamic discrete choice problems in a way that is conducive to CCP estimation and demonstrates that CCP estimators can be adapted to handle rich patterns of unobserved state variables. Copyright © 2011 by Annual Reviews. All rights reserved.

Full Text

Duke Authors

Cited Authors

  • Arcidiacono, P; Ellickson, PB

Published Date

  • August 22, 2011

Published In

Volume / Issue

  • 3 /

Start / End Page

  • 363 - 394

Electronic International Standard Serial Number (EISSN)

  • 1941-1391

International Standard Serial Number (ISSN)

  • 1941-1383

Digital Object Identifier (DOI)

  • 10.1146/annurev-economics-111809-125038

Citation Source

  • Scopus