Bayesian and maximum likelihood analysis of large-scale panel choice models with unobserved heterogeneity

Tomohiro Ando, Jushan Bai and Kunpeng Li

Journal of Econometrics, 2022, vol. 230, issue 1, 20-38

Abstract: This paper considers the estimation and inference procedures for the case of a logistic panel regression model with interactive fixed effects, where multiple individual effects are allowed and the model is capable of capturing high-dimensional cross-section dependence. The proposed model also allows for heterogeneous regression coefficients. New Bayesian and non-Bayesian approaches are introduced to estimate the model parameters. We investigate the asymptotic behaviors of the estimated parameters. We show the consistency and asymptotic normality of the estimated regression coefficients and the estimated interactive fixed effects when both the cross-section and time-series dimensions of the panel go to infinity. We prove that the dimensionality of the interactive effects can be consistently estimated by the proposed information criterion. Monte Carlo simulations demonstrate the satisfactory performance of the proposed method. Finally, the method is applied to study the performance of New York City medallion drivers in terms of efficiency.

Keywords: Cross-sectional and serial dependence; Endogeneity; Factor analysis; Heterogeneous panel; Nonlinear panel data (search for similar items in EconPapers)
JEL-codes: C11 C33 C35 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:230:y:2022:i:1:p:20-38

DOI: 10.1016/j.jeconom.2020.11.013

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