Sebastian Kripfganz

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

Contact details   → Curriculum vitae

 
© Sebastian Kripfganz
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Research
Stata Programs
Journal Articles
Breitung, J., S. Kripfganz, and K. Hayakawa (2022).
Bias-corrected method of moments estimators for dynamic panel data models.
Econometrics and Statistics 24, 116-132.
Kripfganz, S., and J. F. Kiviet (2021).
kinkyreg: Instrument-free inference for linear regression models with endogenous regressors.
Stata Journal 21 (3), 772-813.
Kripfganz, S., and V. Sarafidis (2021).
Instrumental-variable estimation of large-T panel-data models with common factors.
Stata Journal 21 (3), 659-686.
Kiviet, J. F., and S. Kripfganz (2021).
Instrument approval by the Sargan test and its consequences for coefficient estimation.
Economics Letters 205, 109935.
Kripfganz, S., and D. C. Schneider (2020).
Response surface regressions for critical value bounds and approximate p-values in equilibrium correction models.
Oxford Bulletin of Economics and Statistics 82 (6), 1456-1481.
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.
Working Papers
Kripfganz, S., and D. C. Schneider (2022).
ardl: Estimating autoregressive distributed lag and equilibrium correction models.
Research Center for Policy Design Discussion Paper TUPD-2022-006, Tohoku University.
Krause, M., and S. Kripfganz (2022).
Regional convergence at the county level: The role of commuters.
Economics Department Discussion Paper 22/01, University of Exeter.
Conf. Proceedings
Kripfganz, S., and J. Breitung (2022).
Bias-corrected estimation of linear dynamic panel data models.
Proceedings of the 2022 London Stata Conference.
Kripfganz, S. (2019).
Generalized method of moments estimation of linear dynamic panel data models.
Proceedings of the 2019 London Stata Conference.
Work in Progress
Kiviet, J. F., and S. Kripfganz.
Reassessment of classic case studies in labor economics with new instrument-free methods.
Kripfganz, S.
Unconditional transformed likelihood estimation of time-space dynamic panel data models.
© Sebastian Kripfganz
Twitter
@Kripfganz
ORCID
0000-0002-7670-0834

www.kripfganz.de