Sebastian Kripfganz

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

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I have presented the xtseqreg Stata program on June 23, 2017, at the German Stata Users Group Meeting in Berlin. It can be used to estimate two-stage panel data models as described in my paper with Claudia Schwarz on the estimation of linear dynamic panel data models with time-invariant regressors. A Stata replication file for our empirical results is available as supplementary material.

I have recently given seminar presentations on my work about unconditional transformed likelihood estimation of time-space dynamic panel data models at the University of Hamburg (April 18, 2017) and the University of Cologne (June 20, 2017).

Since May 31, 2017, the new xtdpdgmm Stata program for efficient generalized method of moments estimation of linear dynamic panel data models is available for installation from this website. In particular, it allows to incorporate nonlinear moment conditions derived under the assumption of serially uncorrelated errors.

The article on quasi-maximum likelihood estimation of linear dynamic short-T panel data models that describes the xtdpdqml Stata program appeared in the Stata Journal in December 2016. I have presented this work on September 9, 2016, at the UK Stata Users Group Meeting in London. The program has been updated to version 1.4.3 on February 26, 2017.

In the fall term of the 2016/2017 academic year, I was teaching again the first part of the third-year undergraduate module Econometric Analysis (BEE3015) and the postgraduate module Quantitative Research Techniques 1 (BEEM102) at the University of Exeter Business School.

I have delivered a presentation about the Stata module to estimate autoregressive distributed lag models on July 29, 2016, at the Stata Conference in Chicago. The presentation slides are available online. The significantly improved version 0.7.0 of the ardl Stata program has been released on April 29, 2016.

On April 27, 2016, I gave a lecture on recent developments in static and dynamic linear panel model estimation at the Max Planck Institute for Demographic Research in Rostock. The presentation included references to my current work on quasi-maximum likelihood estimation of linear dynamic short-T panel data models and the estimation of linear dynamic panel data models with time-invariant regressors.

Contact

University of Exeter
Business School
Department of Economics

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