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Conditional Choice Probability Estimation of Dynamic Discrete Choice Models with 2-period Finite Dependence

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  • Yu Hao
  • Hiroyuki Kasahara

Abstract

This paper extends the work of Arcidiacono and Miller (2011, 2019) by introducing a novel characterization of finite dependence within dynamic discrete choice models, demonstrating that numerous models display 2-period finite dependence. We recast finite dependence as a problem of sequentially searching for weights and introduce a computationally efficient method for determining these weights by utilizing the Kronecker product structure embedded in state transitions. With the estimated weights, we develop a computationally attractive Conditional Choice Probability estimator with 2-period finite dependence. The computational efficacy of our proposed estimator is demonstrated through Monte Carlo simulations.

Suggested Citation

  • Yu Hao & Hiroyuki Kasahara, 2024. "Conditional Choice Probability Estimation of Dynamic Discrete Choice Models with 2-period Finite Dependence," Papers 2405.12467, arXiv.org.
    • Handle: RePEc:arx:papers:2405.12467
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