Dr. Jonas Krampe
Postdoctoral Researcher at the Chair of Empirical Economic Research

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
Theory
Preprints:
- 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
Publications:
- 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.
Application
Publications:
- 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.