Philipp Adämmer is a scientific researcher focusing on applied econometrics, machine learning and nonlinear statistics. His teaching activities aim to help students in the social sciences and humanities build a strong foundation in data science. He earned his doctorate in economics from the University of Münster in 2016.
Email: philipp.adaemmer (@) uni-greifswald.de.
Phone: +49 3834 420 5506
University of Greifswald
Felix-Hausdorff-Straße 18
17489 Greifswald
 
Recent Publications:

  • Adämmer, P., Wittenberg, P., Weiß, C.H. and Testik, M.C. (2025): Nonparametric monitoring of spatial dependence, Technometrics, in press [Link].
  • Adämmer, P., Lehmann, S. and Schüssler, R. A. (2025): Local Predictability in High Dimensions, Journal of Business & Economic Statistics, in press [Link].
  • Adämmer, P., Prüser, J. and Schüssler, R. (2025): Forecasting macroeconomic tail risk in real time: Do textual data add value?, International Journal of Forecasting, Volume 41, Issue 1, pp. 307-320 [Link].

Research grants:

Software:

  • StatsOP.jl: A Julia package, which provides (sequential) tests for time series data, using ordinal patterns [GitHub].
  • Tin Gustaf: An App, which uses AI to guide through the Dalman Collection at the University of Greifswald [Webpage].
  • hdflex: An R package for local predictability in high dimensions [CRAN] [GitHub].
  • lpirfs: An R package to estimate impulse response functions by local projections[CRAN] [GitHub].

Teaching experience:

   • Data Science 101 for the Social Sciences and Humanities
   • Econometrics & Empirical Economics
   • Seminar Machine Learning for Economists
   • Julia for Data Science and Scientific Computing
   • Machine Learning for Economic Data
   • Statistics for Political Scientists