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

Research, Preprint OPEN
Hiroyuki Kasahara; Katsumi Shimotsu;
  • Publisher: Kingston (Ontario): Queen's University, Department of Economics
  • Subject: C13 | C23 | panel data | C14 | C25 | sieve estimator | nonparametric identification | dynamic discrete choice models; finite mixture; nonparametric identification; panel data; sieve estimator; unobserved heterogeneity | finite mixture | dynamic discrete choice models | unobserved heterogeneity | dynamic discrete choice models, finite mixture, nonparametric identification, panel data, sieve estimator, unobserved heterogeneity
    • jel: jel:C23 | jel:C14 | jel:C25 | jel:C13
      ddc: ddc:330

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-... View more
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