Dr. Jonas Krampe

Postdoctoral Researcher at the Chair of Empirical Economic Research

Dr. Jonas Krampe

Jonas Krampe is a Postdoctoral Researcher at the Department of Economics, University of Mannheim. He received his doctoral degree in mathematics at the TU Braunschweig in 2018. His research interests are:

  • High-dimensional statistics
  • Univariate and multivariate time series
  • Bootstrap methods
  • Statistics in Accident Research

Current working papers can be found on arXiv and Google Scholar.

  • Research



    • Krampe, J. and Margaritella, L. Dynamic Factor Models with Sparse VAR Idiosyncratic Components
    • Krampe, J. and Subba Rao, S. Inverse covariance operators of multivariate nonstationary time series


    • Krampe, J., Paparoditis, E., & Trenkler, C. (2022). Structural Inference in Sparse High-Dimensional Vector Autoregressions. Accepted in Journal of Econometrics.
    • Krampe, J., and Paparoditis, E. (2021) Sparsity Concepts and Estimation Procedures for High- Dimensional Vector Autoregressive Models. Journal of Time Series Analysis 42: 554–579.
    • Krampe, J., Kreiss, J.-P., and Paparoditis, E. (2021). Bootstrap Based Inference for Sparse High-Dimensional Time Series Model. Bernoulli 27.3: 1441–1466.
    • Krampe, J. and McMurry, T.L. (2021), Estimating Wold Matrices and Vector Moving Average Processes. Journal of Time Series Analysis, 42: 201–221
    • Krampe, J. (2019). Time Series Modeling on Dynamic Networks. Electronic Journal of Statistics, 13(2), 4945–4976.
    • Krampe, J., Kreiss, J.-P., and Paparoditis, E. (2018). Estimated Wold Representation and Spectral-density-driven Bootstrap for Time Series. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 80(4), 703–726.
    • Krampe, J., Kreiss, J.-P., and Paparoditis, E. (2015). Hybrid Wild Bootstrap for Nonparametric Trend Estimation in Locally Stationary Time Series. Statistics and Probability Letters, 101, 54–63.



    • Krampe, J., and Junge, M. (2021) Deriving functional safety (ISO 26262) S-parameters for vulnerable road users from national crash data. Accident Analysis and Prevention, 150, 105884.
    • Krampe, J., and Junge, M. (2020). Injury Severity for Hazard and Risk Analyses: Calculation of ISO 26262 S-parameter Values from Real-world Crash Data. Accident Analysis and Prevention, 138, 105321.
    • Suppes, R., Ebrahimi, A., and Krampe, J. (2019). Optimising Casing Milling Rate Of Penetration (ROP) by Applying the Concept of Mechanical Specific Energy (MSE): A Justification of the Concept’s Applicability by Literature Review and a Pilot Study. Journal of Petroleum Science and Engineering, 180, 918–931.
    • Krampe, J., and Junge, M. (2019). Population-based Assessment of a Vehicle Fleet with Seat Belts Providing Lower Shoulder Belt Forces than Today. Traffic Injury Prevention, 20(3), 320–324.
    • Andricevic, N., Junge, M., and Krampe, J. (2018). Injury Risk Functions for Frontal Oblique Collisions. Traffic Injury Prevention, 19(5), 518–522.


Dr. Jonas Krampe

Postdoctoral Researcher at the Chair of Empirical Economic Research
University of Mannheim
Department of Economics
Chair of of Empirical Economic Research
L 7, 3–5 – Room 108
68161 Mannheim