Identification of mixtures of dynamic discrete choices

Ayden Higgins and Koen Jochmans

Journal of Econometrics, 2023, vol. 237, issue 1

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)
JEL-codes: C14 C23 C51 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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Related works:
Working Paper: 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:eee:econom:v:237:y:2023:i:1:s0304407623001562

DOI: 10.1016/j.jeconom.2023.04.006

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