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Practical Methods for Estimation of Dynamic Discrete Choice Models

Author

Listed:
  • Peter Arcidiacono

    (Department of Economics, Duke University, Durham, North Carolina 27708)

  • Paul B. Ellickson

    (Simon School of Business Administration, University of Rochester, Rochester, New York 14627)

Abstract

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.

Suggested Citation

  • Peter Arcidiacono & Paul B. Ellickson, 2011. "Practical Methods for Estimation of Dynamic Discrete Choice Models," Annual Review of Economics, Annual Reviews, vol. 3(1), pages 363-394, September.
    • Handle: RePEc:anr:reveco:v:3:y:2011:p:363-394
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    More about this item

    Keywords

    dynamic structural models; unobserved heterogeneity; conditional choice probabilities;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

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