Identification of mixtures of dynamic discrete choices

Ayden Higgins and Koen Jochmans
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Abstract: This paper provides new identification results for finite mixtures of Markov processes. Our arguments yield identification from knowledge of the cross-sectional distribution of three (or more) effective time-series observations under simple conditions. We explain how our approach and results are different from those in previous work by Kasahara and Shimotsu (2009) and Hu and Shum (2012). Most notably, outside information, such as monotonicity restrictions that link conditional distributions to latent types, is not needed.

Keywords: discrete choice; heterogeneity; Markov process; mixture; state dependence (search for similar items in EconPapers)
Date: 2023-11
New Economics Papers: this item is included in nep-dcm
Note: View the original document on HAL open archive server: https://hal.science/hal-04251997v1
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Published in Journal of Econometrics, 2023, vol. 237 (n° 1), ⟨10.1016/j.jeconom.2023.04.006⟩

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Related works:
Journal Article: Identification of mixtures of dynamic discrete choices (2023)
Working Paper: Identification Of Mixtures Of Dynamic Discrete Choices (2023)
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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-04251997

DOI: 10.1016/j.jeconom.2023.04.006

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