Sebastian Kripfganz

Lecturer (assistant professor) in Economics,
University of Exeter Business School, Department of Economics

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© Sebastian Kripfganz
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Stata Programs
Title and Abstract
Asymptotically efficient method of moments estimators for dynamic panel data models
In this paper, simple variants of bias correction for dynamic panel data models are proposed and their asymptotic properties are studied when the number of time periods is fixed or tends to infinity with the number of panel units. Our approach can easily be generalized to higher-order autoregressive models and cross-sectional dependence. Panel-corrected standard errors are proposed that allow for robust inference in dynamic models with cross-sectionally correlated errors. Monte Carlo experiments suggest that the bias-corrected method of moment estimator outperforms popular GMM estimators in terms of efficiency and correctly sized tests.
Suggested Citation
Breitung, J., K. Hayakawa, and S. Kripfganz (2019). Asymptotically efficient method of moments estimators for dynamic panel data models. Working Paper, University of Cologne.
Related Work
Kripfganz, S. (2019). Generalized method of moments estimation of linear dynamic panel data models. Proceedings of the 2019 London Stata Conference.
Kripfganz, S., and C. Schwarz (2019). Estimation of linear dynamic panel data models with time-invariant regressors. Journal of Applied Econometrics 34 (4), 526-546.
Kripfganz, S. (2016). Quasi-maximum likelihood estimation of linear dynamic short-T panel-data models. Stata Journal 16 (4), 1013-1038.
Jörg Breitung
University of Cologne
Kazuhiko Hayakawa
Hiroshima University
Sebastian Kripfganz
University of Exeter
Working Paper
Working Paper, University of Cologne