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Department of Economics

Dr Sebastian Kripfganz

Dr Sebastian Kripfganz

Senior Lecturer in Econometrics

 S.Kripfganz@exeter.ac.uk

 2110

 +44 (0) 1392 722110

 Streatham Court 1.23

 

Streatham Court, University of Exeter, Rennes Drive, Exeter, EX4 4PU, UK


Overview

Prior to joining the University of Exeter Business School in 2015 as a Lecturer in Economics, Sebastian Kripfganz completed his doctoral studies at Goethe University Frankfurt, where he also held a position as a research and teaching assistant. Previously, he received an Economics diplom from the University of Mannheim. He can also look back to 19 months of professional experience in the Economics Department of Bayerische Landesbank after receiving his Economics diploma from the University of Mannheim.

His international experience includes a research visit at Michigan State University on invitation by Professor Jeffrey Wooldridge and a short-term consultancy in the Poverty Reduction and Economic Management Network of The World Bank in Washington, DC. He has also been invited as a Visiting Associate Professor to Tohoku University in Sendai, Japan.

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Research

Research interests

The focus of Dr Kripfganz' research is on the advancement of econometric methods, which are relevant to a wide audience of applied economists and theoretical econometricians, but also beyond the economics science. His main focus in on methods for estimation and specification testing in dynamic panel data models. This includes approaches for data sets with either short or long time horizon, as well as methods for dealing with cross-sectional dependence. Further contributions to date include work on endogeneity-robust inference with and without instrumental variables, and on statistical inference in time series models. In his research, Dr Kripfganz places special emphasis on the robustness of estimation and inference methods to model misspecification.

A significant part of his research involves the development of widely disseminated packages for the statistical software Stata. Besides his methodological work, Dr Kripfganz is interested in the application of these methods to the analysis of human well-being, both at an aggregate and disaggregate level. This includes the determinants of economic growth and regional convergence, the dynamics of individual and family income, as well as the analysis of social interactions and network effects.

Research networks

Dr Kripfganz is well connected in the research community. Many of his projects are joint work with international collaborators. This includes academics from Germany, The Netherlands, and Japan.

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Publications

Journal articles

Kripfganz S (2023). Review of A. Colin Cameron and Pravin K. Trivedi’s Microeconometrics Using Stata, Second Edition. The Stata Journal Promoting communications on statistics and Stata, 23(4), 1062-1073. Abstract.
Kripfganz S, Schneider DC (2023). ardl: Estimating autoregressive distributed lag and equilibrium correction models. Stata Journal, 23(4), 983-1019. Abstract.
Breitung J, Kripfganz S, Hayakawa K (2021). Bias-corrected method of moments estimators for dynamic panel data models. Econometrics and Statistics, 24, 116-132. Abstract.
Kiviet JF, Kripfganz S (2021). Instrument approval by the Sargan test and its consequences for coefficient estimation. Economics Letters, 205 Abstract.
Kripfganz S, Sarafidis V (2021). Instrumental-variable estimation of large-T panel-data models with common factors. Stata Journal, 21(3), 659-686. Abstract.
Kripfganz S, Kiviet JF (2021). kinkyreg: Instrument-free inference for linear regression models with endogenous regressors. Stata Journal, 21(3), 772-813. Abstract.
Kripfganz S, Schneider DC (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. Abstract.
Kripfganz S, Schwarz C (2019). Estimation of linear dynamic panel data models with time-invariant regressors. Journal of Applied Econometrics, 34(4), 526-546. Abstract.
Kripfganz S (2016). Quasi–maximum likelihood estimation of linear dynamic short-T panel-data models. Stata Journal, 16(4), 1013-1038. Abstract.

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Teaching

The teaching interests of Dr Kripfganz are closely related to his research area. He enjoys teaching fundamental and state-of-the-art econometric methods, particularly concerning the analysis of panel data sets. In his courses, he aims to provide the students with a requisite know-how that will be of practical use for them irrespective of whether they want to follow the path of an academic or a professional career.

Besides his teaching at the University of Exeter, Dr Kripfganz has also received invitations to give short courses on panel data methods at universities and research institutions abroad.

Modules

2023/24


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