Prof. Dr. Jannis Kück

Professor für Volkswirtschaftslehre, insb. Data Science in Economics

Düsseldorf Institute for Competition Economics (DICE)
Heinrich-Heine-Universität Düsseldorf
Universitätsstr. 1
40225 Düsseldorf Gebäude: 24.31
Etage/Raum: 01.07

+49 211 81-10238
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2022	Forschungsaufenthalt an der Universität Freiburg, Schweiz (Lehrstuhl für Angewandte Ökonometrie), Prof. Martin Huber
2020	Promotion in Statistik unter der Betreuung von Herr Prof. Dr. Martin Spindler
2019	Forschungsaufenthalt an der University of California, Irvine (Department of Economics/Deep Data Lab), Prof. Matthew Harding
2016	M.Sc. Wirtschaftsmathematik, Universität Hamburg
2014	B.Sc. Wirtschaftsmathematik, Universität Hamburg

Seit 2023	Professor für Volkswirtschaftslehre, insb. Data Science in Economics, Düsseldorf Institute for Competition Economics (DICE), Heinrich-Heine-Universität Düsseldorf
2021 - 2023	Postdoc am Lehrstuhl für Statistik, Universität Hamburg

Bach, P., Klaassen, S., Kueck, J., & Spindler, M. (2025). Estimation and uniform inference in sparse high-dimensional additive models. Journal of Econometrics, 249(B), 105973.
Chernozhukov, V., Klaaßen, S., Kueck J., Spindler, M. (2022): Uniform Inference in High-Dimensional Gaussian Graphical Models. (Biometrika, available here)
Kueck, J., Luo, Y., Spindler, M., Wang, Z. (2022): Estimation and Inference of Treatment Effects with L2-Boosting in High-Dimensional Settings. (Journal of Econometrics, available here)
Felderer, B., Kueck, J., Spindler, M. (2022): Using Double Machine Learning to Understand Nonresponse in the Recruitment of a Mixed-mode Online Panel (Social Science Computer Review, available here).
Klaaßen, S., Kueck, J., Spindler, M. (2021): Transformation Models in High Dimensions. (Journal of Business & Economic Statistics, available here)
Kueck, J. (2020): Advances in Machine Learning: Valid Inference about High-Dimensional Parameters. (available here) Dissertation, Staats-und Universitätsbibliothek Hamburg Carl von Ossietzky.

Bach, P., Klaaßen, S., Kueck, J., Spindler, M. (2020): Uniform Inference in High-Dimensional Additive Models. (R&R at Journal of Econometrics, available here)
Luo, Y., Spindler, M., Kueck, J. (2022): High-Dimensional L2-Boosting: Rate of Convergence. (R&R at Journal of Machine Learning Research, available here)
Huber, M., Kueck, J. (2022): Testing the Identification of Causal Effects in Observational Data. (available here)
Transformed Failure Time Models in High-Dimensions (with Oliver Schacht)
Adaptive Smoothing for Nonparametric Estimation (with Ye Luo and Martin Spindler)
Double Machine Learning for Partial Correlations and Partial Copulas (with Malte Kurz)

Hochdimensionale Statistik
Ökonometrie
Kausale Inferenz
Maschinelles Lernen
Deep Learning
Graphische Modelle

Verantwortlichkeit: DICE