Journal article
Bayesian and maximum likelihood analysis of large-scale panel choice models with unobserved heterogeneity
T Ando, J Bai, K Li
Journal of Econometrics | ELSEVIER SCIENCE SA | Published : 2022
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 p..
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Awarded by University of Southern California
Funding Acknowledgements
The authors would like to thank the guest editors and anonymous reviewers for their constructive and helpful comments, which have considerably improved the quality of the paper. The authors sincerely thank Mehmet Caner, Ulrich Muller, Hashem Pesaran, Matthew Shum, Liangjun Su, Michael Wolf and Jun Yu for their constructive comments, especially Liangjun Su for his comment on a panel data model with common regressors. We are grateful for the comments and suggestions from the participants in the 4th annual conference of the International Association for Applied Econometrics 2017 (IAAE 2017), the 14th International Symposium on Econometric Theory and Applications (SETA 2018), the 29th (EC)2 conference ``Big Data Econometrics with Applications'', and seminars at Monash University, Singapore Management University, the University of Southern California, and the University of Sydney. The authors are listed in alphabetical order and contribute equally to this paper. Kunpeng Li gratefully acknowledges financial support from National Natural Science Foundation of China No. 71722011 and No. 71571122.