Dr. Rouven E. Haschka
Universität zu Köln
Institut für Ökonometrie und Statistik
Universitätsstr. 24
Wiso, Gebäude 101
Bauteil 3
Raum: 2.314
D-50923 Köln
E rhaschka
uni-koeln.de
T +49 221 470-6561
Short CV
2019: PhD.
2016: M.Sc.
2014: B.Sc.
Veröffentlichungen
- Haschka, R. E., and Herwartz, H. (2022). Endogeneity in pharmaceutical knowledge generation: An instrument‐free copula approach for Poisson frontier models, Journal of Economics & Management Strategy (forthcoming).
- 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
- Haschka, R. E., Herwartz, H., Struthmann, P., Tran, V. T., and Walle, Y. (2022). The joint effects of financial development and the business environment on firm growth: Evidence from Vietnam, Journal of Comparative Economics, 50(2), 486-506.
- Haschka, R. E., and Herwartz, H. (2020). Innovation efficiency in European high-tech industries: Evidence from a Bayesian stochastic frontier approach, Research Policy, 49(8), 104054.
- Haschka, R. E., Schley, K., and Herwartz, H. (2020). Provision of health care services and regional diversity in Germany: Insights from a Bayesian health frontier analysis with spatial dependencies, European Journal of Health Economics, 21, 55–71.
- Haschka, R. E., Schley, K., and Herwartz, H. (2020). Individual health-related quality of life and the regional allocation of medical services: Insights from a stochastic health frontier analysis, Public Health Policy and Planning, 4(4), 42–57.
Working Papers
- Haschka, R. E. (2022). Bayesian inference for joint estimation models using copulas to handle endogenous regressors, SSNR Working Paper
- Haschka, R. E., and Wied, D. (2022). Estimating fixed effects stochastic frontier panel models under ‘wrong’ skewness with an application to health care efficiency in Germany, SSNR Working Paper.
- Haschka, R. E. (2021). Exploiting between-regressor correlation to robustify copula correction models for handling endogeneity, SSNR Working Paper.