Heteroskedasticity-Robust Standard Errors for Dynamic Panel Data Models with Fixed Effects

Chirok Han and Hyoungjong Kim

No 1703, Discussion Paper Series from Institute of Economic Research, Korea University

Abstract: For linear dynamic panel data models with fixed effects, practitioners often use clustered covariance estimators for inference in the presence of cross-sectional or temporal heteroskedasticity in idiosyncratic errors. The performance of a clustered estimator heavily depends on the magnitude of the cross-sectional dimension(n). When n is small, inferences using clustered estimators are compromised. A paper by Stock and Watson (2008) provides a solution under strict exogeneity if the idiosyncratic errors are possibly heteroskedastic but serially uncorrelated. Their method, however, is not generalizable to dynamic panel data models, although heteroskedasticity-robust inferences have natural relevance to dynamic models due to the requirement of serial uncorrelatedness for model identification. In the present paper, we provide a solution for instrumental variables and generalized method of moments estimators using predetermined instruments, including popular estimators for dynamic panel models. Asymptotics are established, and the findings are verified by simulations.

Keywords: Heteroskedasticity-robust covariance estimation; Dynamic panel data; Cluster co- variance estimator; Instrumental variable estimation (search for similar items in EconPapers)
JEL-codes: C12 C23 (search for similar items in EconPapers)
Date: 2017
New Economics Papers: this item is included in nep-ecm
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Journal Article: Heteroskedasticity‐Robust Standard Errors for Dynamic Panel Data Models with Fixed Effects (2023)
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