Sufficient statistics for unobserved heterogeneity in structural dynamic logit models

Victor Aguirregabiria (), Jiaying Gu and Yao Luo

Journal of Econometrics, 2021, vol. 223, issue 2, 280-311

Abstract: We study the identification and estimation of structural parameters in dynamic panel data logit models where decisions are forward-looking and the joint distribution of unobserved heterogeneity and observable state variables is nonparametric, i.e., fixed-effects model. We consider models with two endogenous state variables: the lagged decision variable, and the time duration in the last choice. This class of models includes as particular cases important economic applications such as models of market entry–exit, occupational choice, machine replacement, inventory and investment decisions, or dynamic demand of differentiated products. We prove the identification of the structural parameters using a conditional likelihood approach. The structure of the model implies that there is a sufficient statistic such that the likelihood function conditional on this statistic no longer depends on the unobserved heterogeneity – neither through the current utility nor through the continuation value of the forward-looking decision problem – but still depends on the structural parameters. We apply this estimator to a machine replacement model.

Keywords: Panel data discrete choice models; Dynamic structural models; Fixed effects; Unobserved heterogeneity; Structural state dependence; Identification; Sufficient statistic (search for similar items in EconPapers)
JEL-codes: C23 C25 C41 C51 C61 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (13)

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Related works:
Working Paper: Sufficient Statistics for Unobserved Heterogeneity in Structural Dynamic Logit Models (2018)
Working Paper: Sufficient Statistics for Unobserved Heterogeneity in Structural Dynamic Logit Models (2018)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:223:y:2021:i:2:p:280-311

DOI: 10.1016/j.jeconom.2019.07.010

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