Efficient estimation of heterogeneous coefficients in panel data models with common shocks

Kunpeng Li, Guowei Cui and Lina Lu

Journal of Econometrics, 2020, vol. 216, issue 2, 327-353

Abstract: This paper investigates the estimation and inference issues of heterogeneous coefficients in panel data models with common shocks. We propose a novel two-step method to estimate the heterogeneous coefficients. We establish the asymptotic theory of our estimators, including consistency, asymptotic representation, and limiting distribution. Our two-step method can effectively address the limitations of the existing methods, such as the common correlated effects method proposed by Pesaran (2006) and the iterated principal components method proposed by Song (2013). The two-step estimator is as efficient as the two existing competitors in the basic model, and more efficient in the model with zero restrictions. Intensive Monte Carlo simulations show that the proposed estimator performs robustly in a variety of data setups.

Keywords: Factor analysis; Block diagonal covariance; Panel data models; Common shocks; Maximum likelihood estimation; Heterogeneous coefficients; Inferential theory; Extreme value theory (search for similar items in EconPapers)
JEL-codes: C33 C35 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (11)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:216:y:2020:i:2:p:327-353

DOI: 10.1016/j.jeconom.2019.08.011

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