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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Title and Abstract
Quasi-maximum likelihood estimation of linear dynamic short-T panel-data models
In this article, I describe the xtdpdqml command for the quasi-maximum likelihood estimation of linear dynamic panel-data models when the time horizon is short and the number of cross-sectional units is large. Based on the theoretical groundwork by Bhargava and Sargan (1983, Econometrica 51: 1635-1659) and Hsiao, Pesaran, and Tahmiscioglu (2002, Journal of Econometrics 109: 107-150), the marginal distribution of the initial observations is modeled as a function of the observed variables to circumvent a short-T dynamic panel-data bias. Both random-effects and fixed-effects versions are available.
Suggested Citation
Kripfganz, S. (2016). Quasi-maximum likelihood estimation of linear dynamic short-T panel-data models. Stata Journal 16 (4), 1013-1038.
Related Work
Breitung, J., S. Kripfganz, and K. Hayakawa (2021). Bias-corrected method of moments estimators for dynamic panel data models. Econometrics and Statistics, forthcoming.
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.
Sebastian Kripfganz
University of Exeter
Journal Article
Stata Journal 16 (4), 1013-1038
Article DOI
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