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Nonparametric Identification and Estimation of Finite Mixture Models of Dynamic Discrete Choices

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  • Hiroyuki Kasahara

    ()
    (Department of Economics, University of Western Ontario)

  • Katsumi Shimotsu

    ()
    (Department of Economics, Queen's University)

Abstract

In dynamic discrete choice analysis, controlling for unobserved heterogeneity is an important issue, and finite mixture models provide flexible ways to account for unobserved heterogeneity. This paper studies nonparametric identifiability of type probabilities and type-specific component distributions in finite mixture models of dynamic discrete choices. We derive sufficient conditions for nonparametric identification for various finite mixture models of dynamic discrete choices used in applied work. Three elements emerge as the important determinants of identification; the time-dimension of panel data, the number of values the covariates can take, and the heterogeneity of the response of different types to changes in the covariates. For example, in a simple case, a time-dimension of T=3 is sufficient for identification, provided that the number of values the covariates can take is no smaller than the number of types, and that the changes in the covariates induce sufficiently heterogeneous variations in the choice probabilities across types. Type-specific components are identifiable even when state dependence is present as long as the panel has a moderate time-dimension (T>=6). We also develop a series logit estimator for finite mixture models of dynamic discrete choices and derive its convergence rate.

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File URL: http://qed.econ.queensu.ca/working_papers/papers/qed_wp_1092.pdf
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Bibliographic Info

Paper provided by Queen's University, Department of Economics in its series Working Papers with number 1092.

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Length: 40 pages
Date of creation: Oct 2006
Date of revision:
Handle: RePEc:qed:wpaper:1092

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Keywords: dynamic discrete choice models; finite mixture; nonparametric identification; panel data; sieve estimator; unobserved heterogeneity;

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References

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Citations

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Cited by:
  1. Bound, John & Stinebrickner, Todd & Waidmann, Timothy, 2010. "Health, economic resources and the work decisions of older men," Journal of Econometrics, Elsevier, vol. 156(1), pages 106-129, May.
  2. Victor Aguirregabiria & Pedro mira, 2007. "Dynamic Discrete Choice Structural Models: A Survey," Working Papers tecipa-297, University of Toronto, Department of Economics.
  3. Kasahara, Hiroyuki & Shimotsu, Katsumi, 2008. "Pseudo-likelihood estimation and bootstrap inference for structural discrete Markov decision models," Journal of Econometrics, Elsevier, vol. 146(1), pages 92-106, September.
  4. Hiroyuki Kasahara & Katsumi Shimotsu, 2008. "Sequential Estimation of Structural Models with a Fixed Point Constraint," CESifo Working Paper Series 2507, CESifo Group Munich.

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