Uniform inference in linear panel data models with two-dimensional heterogeneity

Xun Lu and Liangjun Su ()

Journal of Econometrics, 2023, vol. 235, issue 2, 694-719

Abstract: This paper studies uniform inference in a linear panel data model when the slope coefficients may exhibit heterogeneity over both the individual and time dimensions and they can be correlated with the regressors. We propose a generalized two-way fixed effects (GTWFE) estimation procedure to estimate the model. To establish the asymptotic properties of the GTWFE estimators, we invert a number of large dimensional square matrices by approximating them with quasi-Kronecker structured matrices. We establish the asymptotic normality of our GTWFE estimators and show that their convergence rates depend on the unknown degree of parameter heterogeneity. To make a uniform inference on the common slope component, we propose a novel triple-bootstrap procedure to estimate the asymptotic variance. Simulations show the superb performance of our estimators and inference procedure. We apply our method to study the relationship between savings and investments, and find significant parameter heterogeneity along both the individual and time dimensions.

Keywords: Feldstein–Horioka puzzle; Heterogeneity; High-dimension; Least squares dummy variable estimator; Parameter instability; Uniform inference (search for similar items in EconPapers)
JEL-codes: C23 C33 C51 C55 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:235:y:2023:i:2:p:694-719

DOI: 10.1016/j.jeconom.2022.07.002

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