Prof. Dr. Jannis Kück

Professor of Economics, in particular Data Science in Economics

Düsseldorf Institute for Competition Economics (DICE)
Heinrich-Heine-Universität Düsseldorf
Universitätsstr. 1
40225 Düsseldorf Building: 24.31
Floor/room: 01.07

+49 211 81-10238
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2022	Visiting Scholar at University of Fribourg, Switzerland (Chair of Applied Econometrics), Prof. Martin Huber
2020	Ph. D. in Statistics, Faculty of Business Administration (University of Hamburg), Prof. Martin Spindler
2019	Visiting Scholar at University of California, Irvine (Department of Economics/Deep Data Lab), Prof. Matthew Harding
2016	M.Sc. Business Mathematics, University of Hamburg
2014	B.Sc. Business Mathematics, University of Hamburg

Since 2023	Professor of Economics, esp. Data Science in Economics, Düsseldorf Institute for Competition Economics (DICE), Heinrich Heine University Düsseldorf
2021 - 2023	Post-Doctoral Research Associate at University of Hamburg, Faculty of Business Administration, Institute of Statistics - Research in Causal Machine Learning and Econometrics

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)

High dimensional statistics
Econometrics
Causal Inference
Machine Learning
Deep Learning
Graphical Models

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