Sufficient Statistics for Markovian Feedback Processes and Unobserved Heterogeneity in Dynamic Panel Logit Models

Sukgyu Shin

Papers from arXiv.org

Abstract: In this paper, we examine identification in dynamic panel logit models with state dependence, a first-order Markov feedback process, and individual unobserved heterogeneity by introducing sufficient statistics for the feedback process and the unobserved heterogeneity. If a sequentially exogenous discrete covariate follows a first-order Markov process, identification via conditional likelihood is infeasible regardless of the time period. We also establish the failure of point identification beyond the conditional likelihood framework, which necessitates additional restrictions for identification. We present two assumptions for identification via conditional likelihood, imposed on the feedback process and the initial condition, respectively.

Date: 2025-11, Revised 2026-04
New Economics Papers: this item is included in nep-dcm and nep-ecm
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