englisch Lehrstuhl für Statistik und ihre Anwendungen in Wirtschafts- und Sozialwissenschaften

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Prof. Dr. Göran Kauermann


Ludwigstr. 33
80539 München

Room: L 242
Phone: +49 89 2180 3224

Office hours:
on appointment

Curriculum Vitae

17.10.1965 Born in Hagen, Germany
1991 Graduation (Diplom) in Economic Mathematics, Technical University Berlin
1994 PhD in Statistics
1996 Visiting Scholar (Post-Doc), Department of Statistics, University of Chicago, USA
1998 - 2000 Assistant Professor (C1), Ludwig-Maximilians-University Munich
2000 Habilitation (Venia Legendi) in Statistics
2000 - 2003 Lecturer/ Senior Lecturer, Department of Statistics, University of Glasgow, Scotland
2003 - 2011 Full Professor of Statistics (C4, W3 since 2007), Department of Economics and Business Administration, University Bielefeld
2005 (Aug - Dec) Visting Professor, Department of Statistics, University of New South Wales, Sydney, Australia
2011 - present Full Professor of Statistics (W3), Head of Chair of Statistics - in Economics, Business Administration and Social Sciences, Department of Statistics, LMU Munich


  • De Nicola, Giacomo and Kauermann, G. (2024). Estimating excess mortality in high-income countries during the COVID-19 pandemic. Journal of the Royal Statistical Society, Series A (to appear).
  • Fritz, C.; Mehrl, M.; Thurner, P.W.; Kauermann, G. (2024). Exponential Random Graph Models for Dynamic Signed Networks: An Application to International Relations. Political Analysis (to appear)
  • Gruber, C.; Hechinger, K.; Aßenmacher, M.; Kauermann, G. and Planck, B. (2024). More Labels or Cases? Assessing Label Variation in Natural Language Inference. EACL2024.
  • Rave, M. and Kauermann, G. (2024). The Skellam Distribution revisited - Estimating the unobserved incoming and outgoing ICU COVID-19 patients on a regional level in Germany. Statistical Modelling (to appear).
  • Meyer, J.F.; Kauermann, G.; Alder, C. and Cleophas, C. (2025). Modeling price-sensitive demand in turbulent times: An application to continuous pricing. Journal of Revenue and Pricing Management (to appear).
  • Fritz, C., De Nicola, G., Rave, M., Weigert, M., Khazaei, Y., Berger, U., Küchenhoff, H. and Kauermann G. (2024). Statistical modelling of COVID-19 data: Putting Generalised Additive Models to work. Statistical Modelling (to appear).
  • Striegel, C., Kauermann, G. and Biehler, J. (2024). Weighted high dimensional data reduction of finite Element Features - An Application on High Pressure of an Abdominal Aortic Aneurysm. Computational Statistics (to appear).
  • Hechinger, K., Zhu, X.-X. and Kauermann, G. (2024). Categorizing the World into Local Climate Zones - Towards Quantifying Labeling Uncertainty for Machine Learning Models. Journal of the Royal Statistical Society, Series C. (to appear).
  • Racek, D.; Thurner, P.W.; Davidson, B.I.; Zhu, X. and Kauermann, G. (2024) Conflict Forecasting using Remote Sensing Data: An Application to the Syrian Civil War. International Journal of Forecasting, 40(1), 373-391.
  • Racek, D.; Davidson, B.I.; Thurner, P.; Zhu, X.Z. and Kauermann, G. (2024) The Politics of Language Choice: How the Russian-Ukrainian War Influences Ukrainians' Language Use on Social Media. Nature: Communications Psychology (to appear).
  • Koller, C.; Kauermann, G. and Zhu, X.Z. (2024) Going Beyond One-Hot Encoding in Classification: Can Human Uncertainty Improve Model Performance in Earth Observation? Transactions in Geoscience & Remote Sensing (to appear).
  • Trinkaus, O. and Kauermann, G. (2023). Can Machine Learning Algorithms deliver superior Models for Rental Guides? AStA Wirtschafts- und Sozialstatistisches Archiv, 17, 305-330.
  • De Nicola, G. Fritz, C. Mehrl, M. and Kauermann, G. (2023). Dependence matters: Statistical models to identify the drivers of tie formation in economic networks. Journal of Economic Behavior and Organization, 215, 351-363.
  • De Nicola, G.; Tuekam Mambou, V.H. and Kauermann, G. (2023). COVID-19 and social media: Beyond polarization - PNAS Nexus, 2, issue 8, August 2023.
  • Kauermann, G.; Windmann, M.; (2023). Die Berücksichtigung von außergesetzlichen Merkmalen bei der Mietspiegelerstellung – Kausalität versus Vorhersage. AStA Wirtschafts- und Sozialstatistisches Archiv. AStA Wirtschafts- und Sozilstatistisches Archiv, 17, 145-160.
  • Kauermann, G. and De Nicola, G. (2023). Übersterblichkeit durch Corona? WISTA-Wirtschafts- und Sozialstatistik. Ausgabe 1-2023
  • Fritz, C., De Nicola, G., Kevork, S., Harhoff, D. and Kauermann, G. (2023). Modelling the large and dynamically growing bipartite network of German patents and inventors. Journal of the Royal Statistical Society, Series A, 186(3), 557-576.
  • Fahrmeir, L., Kauermann, G., Tutz, G. and Windmann, M. (2023). Spatial Smoothing Revisited - An Application to Rental Data in Munich. Statistical Modelling, 23(5-6):480-494. doi:10.1177/1471082X231158465
  • Lindskog, W., Huang, Y.-W., Prehofer, Ch., Puts, R., Mosca, P., and Kauermann, G. (2022). Predictive Energy Management for Battery Electric Vehicles with Hybrid Models. EAI INTSYS 2022 (6th EAI International Conference on Intelligent Transport Systems).
  • Fritz, C., Mehrl, M., Thurner, P. and Kauermann, G. (2022). All that Glitters is not Gold: Relational Events Models with Spurious Events. Network Science (to appear)
  • Fritz, C., De Nicola, G., Günther, F., Rügamer, D., Rave, M., Schneble, M., Bender, A., Weigert, M., Brinks, R., Hoyer, A., Berger, U., Küchenhoff, H. and Kauermann, G. (2022). Challenges in Interpreting Epidemiological Surveillance Data - Experiences from Germany. Jorunal of Computational and Graphical Statistics 32(2), 765-766.
  • Berger, U., Kauermann, G. and Küchenhoff, H. (2022). Discussion on "On the role of data, statistics and decisions in a pandemic". Advances in Statistical Analysis 106, 387-390.
  • Berger, U., Fritz, C. and Kauermann, G. (2022). Reihentestungen an Schulen können die Dunkelziffer von COVID-19 Infektionen unter Schülern signifikant senken. Das Gesundheitswesen 84(06), 495-502.
  • De Nicola, G. and Kauermann, G. (2022). An update on excess mortality in the second year of the COVID-19 pandemic in Germany. AStA Wirtschafts- und Sozialstatistisches Archiv 116, 21-24.
  • Meyer, F., Kauermann G. and Smith, M.S. (2022). Interpretable Modeling of Retail Demand and Price Elasticity for Passenger Flights using Booking Data. Statistical Modelling (to appear).
  • Kevork, S. and Kauermann, G. (2022). Bipartite Exponential Random Graph Models with Nodal Random Effects. Social Networks, 70:90-99, ISSN 0378-8733, https://doi.org/10.1016/j.socnet.2021.11.002
  • De Nicola, G., Schneble, M., Kauermann, G. and Berger, U. (2022). Regional now- and forecasting for data reported with delay: Towards surveillance of COVID-19 infections. AStA Advances in Statistical Analysis 106, 407-426.
  • Kevork, S. and Kauermann, G. (2022). Iterative Estimation of Mixed Exponential Random Graph Models with Nodal Random Effects. Network Science 9, 478–498. https://doi.org/10.1017/nws.2021.22.
  • Striegel, C., Biehler, J., Wall, W.A. and Kauermann, G. (2022). A Multifidelity Function-on-Function Model applied to an Abdominal Aortic Aneurysm. Technometrics. https://doi.org/10.1080/00401706.2021.2024453.
  • De Nicola, G., Kauermann, G. and Höhle, M. (2022): On assessing excess mortality in Germany during the COVID-19 pandemic. AStA Wirtschafts- und Sozialstatistisches Archiv (to appear).
  • Fritz, C. and Kauermann, G. (2022) On the Interplay of Regional Mobility, Social Connectedness, and the Spread of COVID-19 in Germany. Journal of the Royal Statistical Society, Series A. Royal Statistical Society, vol. 185(1), pages 400-424, January.
  • Sischka, B. and Kauermann, G. (2022) EM-Based Smooth Graphon Estimation Using MCMC and Spline-Based Approaches. Social Networks, 68, 279 - 295.
  • Fritz C., Mehrl M., Thurner P. W. and Kauermann G. (2021): The Role of Governmental Weapons Procurements in Forecasting Monthly Fatalities in Intrastate Conflicts: A Semiparametric Hierarchical Hurdle Model, International Interactions. https://doi.org/10.1080/03050629.2022.1993210.
  • Fritz, C., Thurner, P.W. and Kauermann, G. (2021) Separable and Semiparametric Network-based Counting Processes applied to the International Combat Aircraft Trades. Network Science, 9(3), 291 - 311.
  • De Nicola, G., Sischka, B. and Kauermann, G. (2021) Mixture Models and Networks: The Stochastic Block Model. Statistical Modelling. https://doi.org/10.1177/1471082X211033169.
  • Schneble, M. and Kauermann, G. (2021) Intensity Estimation on Geometric Networks with Penalized Splines. Annals of Applied Statistics (to appear).
  • Schneble M., De Nicola, G., Kauermann, G. and Berger, U. (2021) A statistical model for the dynamics of COVID-19 infections and their case detection ratio in 2020. Biometrical Journal, 63 (8), 1623 – 1632, https://doi.org/10.1002/bimj.202100125
  • Lebacher, M., Thurner, P. and Kauermann, G. (2021) Censored Regression for Modelling Small Arms Trade Volumes and its "Forestic" Use of Exploring Unreported Trades. Journal of the Royal Statistical Society, Series C, https://doi.org/10.1111/rssc.12491
  • Bauer, V., Harhoff, D. and Kauermann, G. (2021) A smooth dynamic network model for patent collaboration data. AStA Advances in Statistical Analysis, https://doi.org/10.1007/s10182-021-00393-w
  • Ali, M. and Kauermann, G. (2021) A Split Questionnaire Survey Design in the Context of Statistical Matching. Journal of Statistical Methods and Applications, 30, 1219 – 1236.
  • Schneble; de Nicola; Kauermann; Berger (2021). Nowcasting fatal COVID-19 Infections on a regional Level in Germany. Biometrical Journal, 63(3), 471 – 489, https://doi.org/10.1002/bimj.202000143 
  • Lebacher, M., Thurner, P. und Kauermann, G. (2021) A Dynamic Separable Network Model with Actor Heterogeneity: An Application to Global Weapons Transfers, Journal of the Royal Statistical Society, Series A, 184(1), 201 – 226.
  • Schneble, M. and Kauermann, G. (2020). Estimation of Latent Network Flows in Bike-Sharing Systems. Statistical Modelling, https://doi.org/10.1177/1471082X20971911
  • A. Beyer, G. Kauermann & H. Schütze (2020). Embedding Space Correlation as a Measure of Domain Similarity. LREC 2020 Proceedings. https://www.aclweb.org/anthology/2020.lrec-1.296/
  • Kauermann, G.; Windmann, M.; Münnich, R. (2020). Datenerhebung bei Mietspiegeln: Überblick und Einordnung aus Sicht der Statistik, AStA Wirtschafts- und Sozialstatistisches Archiv. AStA Wirtschafts- und Sozilstatistisches Archiv, 14, 145 – 162, doi:10.1007/s11943-020-00272-x
  • Kauermann, G. and Ali, M. (2020) Semi-parametric Regression When Some (Expensive) Covariates Are Missing By Design. Statistical Papers, 62, 1675 – 1696, . doi:10.1007/s00362-019-01152-5
  • Shao, S., Kauermann, G. and Smith, M.S. (2020) Whether, when and which: modelling advanced seat reservations by airline passengers.Transportation Research Part A. Volume 132, February 2020, Pages 490-514. doi:10.1016/j.tra.2019.12.002
  • Carballo, A. Durban, M., Kauermann, G. & Lee, D.-J. (2020). A general framework for prediction in penalized regression. Statistical Modelling. doi:10.1177/1471082X19896867
  • Kauermann, G. (2019). Data Science - aus Sicht eines Statistikers. Informatik Spektrum. 42, 387–393.
  • Fritz C., Lebacher M. and Kauermann, G. (2020) Tempus Volat, Hora Fugit - A Survey of Tie-Oriented Dynamic Network Models in Discrete and Continuous Time. Statistica Neerlandica, 74(3), 275 – 299, doi:10.1111/stan.12198
  • Lebacher, M., Cook, S., Klein, N. and Kauermann, G. (2019). In Search of Lost Edges: A Case Study on Reconstructing Financial Networks. Journal of Network Theory in Finance, Vol 5(4), 29 – 61.
  • Bauer, V., Fürlinger, K. and Kauermann, G. (2019): A Note on Parallel Sampling in Markov Graphs. Computational Statistics. 34, 1087–1107
  • Shao, S. und Kauermann, G. (2019):
    Understanding price elasticity for airline ancillary services.
    Journal of Revenue and Pricing Management. 19, pages74–82
  • Lebacher, M., Thurner, P. und Kauermann, G. (2018):
    Exploring Dependence Structures in the International Arms Trade Network: A Network Autocorrelation Approach.
    Statistical Modelling. doi:10.1177/1471082X18817673.
  • Thurner, P., Cranmer, S., Kauermann, G. und Schmid, C. (2018):
    Network Interdependencies and the Evolution of the International Arms Trade.
    Journal of Conflict Resolution. doi:10.1177/0022002718801965
  • Kauermann, G. und Seidl, T. (2018):
    Data Science - A proposal for a Curriculum.
    International Journal of Data Science and Analytics. 6, pages195–199
  • Bothmann, L., Menzel, A., Menze, B. und Kauermann, G. (2017):
    Automated Processing of Webcam Images for Phenological Classification.
    PLOS ONE 12(2): 1-23. doi:10.1371/journal.pone.0171918.
  • Schulze Waltrup, L. und Kauermann, G. (2017):
    Smooth Expectiles for Panel Data using Penalized Splines.
    Statistics and Computing 27(1): 271-282. doi:10.1007/s11222-015-9621-2.
  • Bruns, P., Paschedag, H. und Kauermann, G. (2016):
    Anerkannte wissenschaftliche Grundsätze zur Erstellung qualifizierter Mietspiegel.
    Zeitschrift für Miet- und Raumrecht 69: 669 - 679. doi:10.1515/zmr-2016-0902.
  • Kauermann, G., Thomschke, L. und Braun, R. (2016):
    Scheinargumente bei Mietspiegeldebatte - Was definiert „moderne Mietspiegel“?
    Zeitschrift für Wirtschaftspolitik 65(3). doi:10.1515/zfwp-2016-0020.
  • Kauermann, G. und Windmann, M. (2016):
    Mietspiegel heute zwischen Realität und statistischen Möglichkeiten.
    AStA Wirtschafts - und Sozialstatistisches Archiv. 10, pages205–223. doi:10.1007/s11943-016-0197-x.
  • Kauermann, G., Becher H. und Maier, V. (2016):
    Exploring the Statistical Uncertainty in Acceptable Exposure Limit Values for Hexavalent Chromium Exposure (CR(VI)).
    Journal Of Exposure Science And Environmental Epidemiology. 28, pages69–75 doi: 10.1038/jes.2017.4.
  • Kauermann, G. und Kuechenhoff, H. (2016):
    Statistik, Data Science und Big Data.
    AStA Wirtschafts - und Sozialstatistisches Archiv. 10, pages141–150 doi:10.1007/s11943-016-0188-y.
  • Bothmann, L., Windmann, M. und Kauermann, G. (2016):
    Real Time Classification of Fish in Underwater Sonar Videos.
    Journal of the Royal Statistical Society: Series C (Applied Statistics) 65(4): 565-584. doi:10.1111/rssc.12139.
  • Brenner, T. und Kauermann, G. (2016):
    Specialization and Convergence of Industry-Specific Employment in Germany: A Linear Mixed-Model Approach with Spatial Components
    Regional Studies 50(2): 326-341. doi:10.1080/00343404.2014.920082.
  • Schulze Waltrup, L. und Kauermann, G. (2016):
    A Short Note on Quantile and Expectile Estimation in Unequal Probability Samples.
    Survey Methodology 42(1): 179-187.
  • Thiemichen, S., Friel, N., Caimo, A. und Kauermann, G. (2016):
    Bayesian Exponential Random Graph Models with Nodal Random Effects.
    Social Networks 46: 11-28. doi:10.1016/j.socnet.2016.01.002.


Further publicationsnach oben

Editorial Duties

Further Activities / Awards

  • Chair (Vorstand) of the Deutsche Arbeitsgemeinschaft Statistik (2005 - 2013)
  • Speaker of Elite Master Program Data Science  (2016 - 2026)
  • Dean, Faculty of Mathematics, Computer Science and Statistics (2019 - 2021)
  • Elected Reviewer (Fachkollegiat) for Statistics and Econometrics, Deutsche Forschungsgemeinschaft (2020 - 2024)
  • Bruce Russett Award, together with Christian Schmid, Skyler Cranmer and Paul Thurner, 2020

Forschungsinteressen / Research Interests

  • Nonparametric Models (Local Likelihood and Penalised Regression)
  • Semi- and nonparametric analysis
  • Generalized Linear Models
  • Generalized Mixed Models
  • Network Data Analysis nach oben

Responsible for content: Göran Kauermann