Data analytics
Disturber shows building 42

Data analytics

Prof. Dr. habil. Rouven E. Haschka

Prof. Dr. habil. Rouven E. Haschka

Chair holder

Picture of Professor Haschka

Prof. Dr. Rouven E. Haschka has held the Chair of Data Analytics at RPTU Kaiserslautern-Landau since 2025.

After studying Business Studies and Economics (Bachelor's degree) and Applied Statistics (Master's degree), he completed his doctorate in the Research Training Group "Scale Problems in Statistics" at the Georg August University of Göttingen and habilitated at the University of Cologne in economics, in particular econometrics and statistics.

He was also Assistant Professor at the University of Bradford and Junior Professor for Business Analytics and Data Science at Zeppelin University Friedrichshafen and is affiliated with Corvinus University Budapest.

Awards
  • Florenz-Sartorius Prize for the best dissertation at the Faculty of Business Studies and Economics of the Georg-August University of Göttingen
  • Top Cited Article (2022-2023) - Wiley
Third-party funded projects
  • DFG: "Nonparametric Bayesian inference for copula-based endogeneity corrections" (project number: 568088747)
Prof. Dr. Rouven E. Haschka

Address

Gottlieb-Daimler-Str.
Building: 42, Room: 428, Floor: 4
67663 Kaiserslautern

Contact details

rouven.haschka(at)rptu.de

Office hours

nach Vereinbarung.  

Please contact the office.

Further information

  • Haschka, R. E., & Dost, F. (2026). Correcting omitted-variable bias without instruments: An ICA-based alternative to Gaussian copula methods. Journal of Marketing Research (available online). https://doi.org/10.1177/00222437261499336
  • Haschka, R. E. (2026). The Effects of Structural Conditions on Sectoral Productivity in South, East, and Southeast Asia. The European Journal of Development Research (available online). https://link.springer.com/article/10.1057/s41287-026-00762-8
  • Haschka, R. E. (2025). Bayesian Inference for Joint Estimation Models Using Copulas to Handle Endogenous Regressors. Oxford Bulletin of Economics and Statistics, 88 (3), 519–534. https://doi.org/10.1111/obes.70023
  • Haschka, R. E., & Herwartz, H. (2025). Utilizing managerial beliefs for set identification of price elasticities of demand. Journal of the Academy of Marketing Science, 53, 1482–1505. https://doi.org/10.1007/s11747-025-01090-9
  • Haschka, R. E., & Wied, D. (2025). Skewness issues in quantifying efficiency: Insights from stochastic frontier panel models based on closed skew-normal approximations. Computational Economics, 66, 4381–4416. https://doi.org/10.1007/s10614-025-10857-9
  • Haschka, R. E. (2024). Robustness of copula-correction models in causal analysis: Exploiting between-regressor correlation. IMA Journal of Management Mathematics, 36 (1), 161–180. https://doi.org/10.1093/imaman/dpae018
  • Haschka, R. E. (2024). An Ethical Perspective on AI in Controlling. Controlling & Management Review, 68, 50–53. https://doi.org/10.1007/s12176-024-1418-8
  • Haschka, R. E. (2024). Examining the New Keynesian Phillips Curve in the U.S.: Why has the relationship between inflation and unemployment weakened? Research in Economics, 78 (4), 100987 (2024). https://doi.org/10.1016/j.rie.2024.100987
  • Haschka, R. E. (2024). Wrong skewness and endogenous regressors in stochastic frontier models: An instrument-free copula approach with an application to estimate firm efficiency in Vietnam. Journal of Productivity Analysis, 62, 71–90. https://doi.org/10.1007/s11123-024-00722-6
  • Haschka, R. E. (2024). Endogeneity in stochastic frontier models with “wrong” skewness: A copula approach without external instruments. Statistical Methods and Applications, 33, 807–826. https://doi.org/10.1007/s10260-024-00750-4
  • Haschka, R. E., Herwartz, H., Silva Coelho, C., & Walle, Y. (2023). Local financial development and firm growth in Vietnam: Evidence from a Bayesian geoadditive stochastic frontier approach. Journal of Productivity Analysis, 60, 203–226. https://doi.org/10.1007/s11123-023-00694-z
  • Haschka, R. E., & Herwartz, H. (2022). Endogeneity in pharmaceutical knowledge generation: An instrument-free copula approach for Poisson frontier models. Journal of Economics and Management Strategy, 31 (4), 942–960. https://doi.org/10.1111/jems.12491
  • Haschka, R. E. (2022). Handling endogenous regressors using copulas: A generalization to linear panel models with fixed effects and correlated regressors. Journal of Marketing Research, 59 (4), 860–881. https://doi.org/10.1177/00222437211070820
  • Haschka, R. E., Herwartz, H., Struthmann, P., Tran, V. T., & Walle, Y. (2021). The joint effects of financial development and the business environment on firm growth: Evidence from Vietnam. Journal of Comparative Economics, 50 (2), 486–506. https://doi.org/10.1016/j.jce.2021.11.002
  • Haschka, R. E., & Herwartz, H. (2020). Innovation efficiency in European high-tech industries: Evidence from a Bayesian stochastic frontier approach. Research Policy, 49 (8), 104054. https://doi.org/10.1016/j.respol.2020.104054
  • Haschka, R. E., Herwartz, H., & Schley, K. (2020). Provision of health care services and regional diversity in Germany: Insights from a Bayesian health frontier analysis with spatial dependencies. The European Journal of Health Economics, 21, 55–71. https://doi.org/10.1007/s10198-019-01111-9
  • Haschka, R. E., Herwartz, H., & Schley, K. (2020). Individual health-related quality of life and the regional allocation of medical services: Insights from a stochastic health frontier analysis. Journal of Public Health Policy and Planning, 4 (4), 42–57. https://doi.org/10.35841/public-health-policy.4.4.42-57