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Practical Methods for Estimation of Dynamic Discrete Choice Models

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  • 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)

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    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.

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    Bibliographic Info

    Article provided by Annual Reviews in its journal Annual Review of Economics.

    Volume (Year): 3 (2011)
    Issue (Month): 1 (09)
    Pages: 363-394

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    Handle: RePEc:anr:reveco:v:3:y:2011:p:363-394

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    Related research

    Keywords: dynamic structural models; unobserved heterogeneity; conditional choice probabilities;

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    References

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    Cited by:
    1. Che-Lin Su, 2014. "Estimating discrete-choice games of incomplete information: Simple static examples," Quantitative Marketing and Economics, Springer, vol. 12(2), pages 167-207, June.

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