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Exponential class of dynamic binary choice panel data models with fixed effects

Al-Sadoon, M.; Li, T.; Pesaran, M.H.

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Authors

T. Li

M.H. Pesaran



Abstract

This paper proposes an exponential class of dynamic binary choice panel data models for the analysis of short T (time dimension) large N (cross section dimension) panel data sets that allow for unobserved heterogeneity (fixed effects) to be arbitrarily correlated with the covariates. The paper derives moment conditions that are invariant to the fixed effects which are then used to identify and estimate the parameters of the model. Accordingly, generalized method of moments (GMM) estimators are proposed that are consistent and asymptotically normally distributed at the root-N rate. We also study the conditional likelihood approach and show that under exponential specification, it can identify the effect of state dependence but not the effects of other covariates. Monte Carlo experiments show satisfactory finite sample performance for the proposed estimators and investigate their robustness to misspecification.

Citation

Al-Sadoon, M., Li, T., & Pesaran, M. (2017). Exponential class of dynamic binary choice panel data models with fixed effects. Econometric Reviews, 36(6-9), 898-927. https://doi.org/10.1080/07474938.2017.1307597

Journal Article Type Article
Acceptance Date Mar 28, 2017
Online Publication Date May 16, 2017
Publication Date Oct 21, 2017
Deposit Date Aug 15, 2018
Publicly Available Date Mar 28, 2024
Journal Econometric Reviews
Print ISSN 0747-4938
Electronic ISSN 1532-4168
Publisher Taylor and Francis Group
Peer Reviewed Peer Reviewed
Volume 36
Issue 6-9
Pages 898-927
DOI https://doi.org/10.1080/07474938.2017.1307597
Public URL https://durham-repository.worktribe.com/output/1351838

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