Lebenslauf

09/2019 - present: Assistant Professor Chair of Statistics U Passau
10/2014 - 09/2019: Ph.D. in Economics U Passau
12/2012 - 07/2014: Student Assistant Chair of Statistics U Passau
10/2012 - 08/2014: M.A. International Economics & Business U Passau
04/2011 - 08/2014: M.Sc. Business Administration U Passau
10/2007 - 03/2011: B.Sc. Business Administration & Economics U Passau and San Diego State University (CA, USA)

Publikationen

Fritsch M., Pua A. A. Y. and J. Schnurbus [2024],Teaching Advanced Topics in Econometrics using Introductory Textbooks: The Case of Dynamic Panel Data Methods. International Review of Economics Education, 47, 100297

Fritsch M., Haupt H., and J. Schnurbus [2024+], Efficiency of poll-based multi-period forecasting systems for German state elections. International Journal of Forecasting, forthcoming

Ranpal S., von Bargen S., Gilles S., Luschkova D., Landgraf M., Bogawski P., Traidl-Hoffmann C., Büttner C., Damialis A., Fritsch M., and S. Jochner-Oette [2024], Continental-scale Evaluation of Downy Birch Pollen Production: Estimating the Impacts of Global Change.Environmental Research, 252, 119114

Kleinke K., Fritsch M., Stemmler M., and F. Lösel [2024], Multiple imputation of longitudinal data – A comparison of robust imputation methods regarding sample size requirements, with an application to corporal punishment data. In:Dependent Data in Social Sciences Research, 2nd edition, Springer, 565-588

Jetschni J., Fritsch M., and S. Jochner-Oette [2023], How does pollen production of allergenic species differ between urban and rural environments? International Journal of Biometeorology, 67, 1839-1852

Haupt H. and M. Fritsch [2022], Quantile Trend Regression and Its Application to Central England Temperature. Mathematics, 10 (3), 413

Fritsch M. and S. Behm [2021], Data for modeling nitrogen dioxide concentration levels across Germany.Data in Brief, 38, 107324

Kleinke K., Fritsch M., Stemmler M., Reinecke J., and F. Lösel [2021], Quantile Regression-Based Multiple Imputation of Missing Values -­­ An Evaluation and Application to Corporal Punishment Data.Methodology, 17 (3), 205-230

Fritsch M. and S. Behm [2021], Agglomeration and infrastructure effects in land use regression models for air pollution - Specification, estimation, and interpretations.Atmospheric Environment, 253, 118337

Fritsch M., Pua A. A. Y. and J. Schnurbus [2021], pdynmc: A Package for Estimating Linear Dynamic Panel Data Models Based on Nonlinear Moment Conditions.The R Journal, 13 (1), 218-231

Fritsch M., Haupt H., Lösel F. and M. Stemmler [2019], Regression trees and random forests as alternatives to classical regression modeling: Investigating the risk factors for corporal punishment. Psychological Test and Assessment Modeling,61 (4), 389-417

Fritsch, M. [2019], Five essays on linear dynamic panel data models, Dissertation

Fritsch M., Haupt H. and P.T. Ng [2016], Urban house price surfaces near a World Heritage Site: modeling conditional price and spatial heterogeneity. Regional Science and Urban Economics, 60, 260-275

Software

pdynmc: Dynamic linear panel estimation based on linear and nonlinear moment conditions. Available from: https://cran.r-project.org/web/packages/pdynmc/; for the latest version, see: https://github.com/markusfritsch/pdynmc

fixedEventFC: Functions and data for investigating the efficiency of poll-based multi-period forecasting systems for German state elections. Available from: https://github.com/markusfritsch/fixedEventFC

quantWarming: Data and functions for trend analysis of temperature time series. Available from: https://github.com/markusfritsch/quantWarming

smoothLUR: Functions and data for smooth land use regression modeling. Available from: https://github.com/markusfritsch/smoothLUR

Schwerpunkte

• Semi- and nonparametric estimation
• Quantile regression
• Panel data models
• Applied statistics and econometrics
• Data Science and statistical learning