Professuren für Statistik und Ökonometrie

Research

Publications in Journals
2023

  • ​Rage Against the Mean – A Review of Distributional Regression Approaches​ Kneib, T.; Silbersdorff, A. & Säfken, B.​ (2023) Econometrics and Statistics, 26 pp. 99​-123​.​ DOI: https://doi.org/10.1016/j.ecosta.2021.07.006 Details
  • Erwartete Schulprobleme als Folge der Corona-Schulschließungen im Frühjahr 2020 – Empirische Evidenz zur Bedeutung familialer Ressourcen mittels nichtlinearer Modellierung​ Lorenz, J.; Ike, S.; Dammann, L. M.; Becker, D.; Säfken, B. & Silbersdorff, A.​ (2023) Zeitschrift für Erziehungswissenschaft, 26(2) pp. 403​-441​.​ DOI: https://doi.org/10.1007/s11618-023-01149-9 Details
  • ​Leitfaden zur Erstellung barrierefreier Lehrvideos im universitären Kontext: ​Projekt DaLeLe4All​ ​ Berginski, J. ; Damman, L. M.; Deitmer, A.; Finkbeiner, T. A.; Ike, S. ; Lux, K.& Meister (geb. Pendzich), N.-K. et al.​ (2023) Göttingen​: Universitätsverlag Göttingen. DOI: https://doi.org/10.17875/gup2023-2355 ​Details

2022

  • ​Firm-level energy rebound effects and relative efficiency in the German manufacturing sector​ Berner, A. ; Lange, S. & Silbersdorff, A. ​ (2022) Energy Economics, 109 art. S0140988322000834​.​ DOI: https://doi.org/10.1016/j.eneco.2022.105903 ​Details
  • ​Model averaging for linear mixed models via augmented Lagrangian​ Kruse, R.-M.; Silbersdorff, A. & Säfken, B.​ (2022) Computational Statistics & Data Analysis, 167 art. S0167947321001857​.​ DOI: https://doi.org/10.1016/j.csda.2021.107351 Details

​ ​ 2021

  • ​ ​Introductory data science across disciplines, using Python, case studies, and industry consulting projects​ Lasser, J.; Manik, D.; Silbersdorff, A. ; Säfken, B. & Kneib, T. ​ (2021) Teaching Statistics, 43 pp. S190​-S200​.​ DOI: https://doi.org/10.1111/test.12243
  • ​ ​Learning Deep Textwork: ​Perspectives on Natural Language Processing and Artificial Intelligence​ ​ Kruse, R.-M.; Säfken, B.; Silbersdorff, A. & Weisser, C.​ (Eds.) (2021) Göttingen: ​Universitätsverlag Göttingen. DOI: https://doi.org/10.17875/gup2021-1608

2020

  • ​ ​Learning deep: ​Perspectives on Deep Learning Algorithms and Artificial Intelligence​ ​ Säfken, B.; Silbersdorff, A. & Weisser, C.​ (Eds.) (2020) Göttingen: ​Universitätsverlag Göttingen. DOI: https://doi.org/10.17875/gup2020-1338

2019

  • A. Silbersdorff, K. S. Schneider (2019): Distributional Regression Techniques in Socioeconomic Research on the Inequality of Health with an Application on the Relationship between Mental-Health and Income, in: International Journal of Environmental Research and Public Health, Vol. 16(20), doi: 10.3390/ijerph16204009..
  • S. Diers, C. Blaschka, A. Silbersdorff, C. Knorr, J. Tetens (2019): Effect of glyphosate on bovine oocyte development during in vitro maturation, in: Reproduction in Domestic Animals, Vol. 64 (S1), p.2.

2018

  • A. Silbersdorff, T. Kneib, J. Lynch, S. Klasen (2018): Reconsidering the Income-Health Relationship using Distributional Regression, in Health Economics, Vol. 27, pp.1074-1088.
  • J. Hambuckers, T. Kneib, A. Silbersdorff and R. Langrock (2018): A Markov-Switching Generalized Additive Model for Compound Poisson Processes, with Applications to Operational Losses Models, in: Quantiative Finance, Vol. 18, pp. 1679-1698.

2016

  • A. Sohn (2016): Poor University Professors? The Relative Earnings Decline of German Professors During the 20th Century, in: Scandinavian Economic History Review, Vol. 64, pp. 84-102.

2015

  • R. Langrock, T. Kneib, A. Sohn, S. DeRuiter (2015): Nonparametric inference in hidden Markov models via penalized likelihood methods, in: Biometrics, Vol. 71, pp. 520-528.
  • R. Langrock, T. Michelot, A. Sohn, T. Kneib (2015): Nonparametric modelling of the conditional distribution in a stochastic volatility model, in: Computational Statistics, Vol. 30, pp. 517-537.
  • Klein, N., Kneib, T., Lang, S. and Sohn, A. (2015): Bayesian Structured Additive Distributional Regression with an Application to Regional Income Inequality in Germany, in: Annals of Applied Statistics, Vol. 9, pp. 1024-1052.
  • A. Sohn, N. Klein, T. Kneib (2015): A Semiparametric Approach to Analysing Conditional Income Distributions, in: Schmollers Jahrbuch, Vol. 135, pp. 13-22.

2014

  • A. Sohn (2014): Im Historischen Sinkflug: Die Gehälter von Professoren, in: Forschung&Lehre, 9|14, pp.736-737.
  • A. Becker, A. Rothenberger, A. Sohn (2014): Six years ahead - course and predictive value of psychopathological screening in children of the community, in: European Child & Adolescent Psychiatry, Vol. 24(6), pp. 715-725.

Books and Book Chapters
2019

  • F. Dorn, A. Berner, C. Ochsner, A. Silbersdorff (2019): Plurale Lehre in den Wirtschaftswissenschaften an der Georg-August-Universität Göttingen, in: Erfahrungen aus der pluralistischen sozio*ökonomischen Hochschullehre, to appear.
  • M. Hohberg, T. Kneib, A. Sohn (2019): Mehr als Durchschnittsstatistik. Eine kritische Einführung in Regressionsmethoden jenseits des Mittelwertes, in: Perspektiven einer Pluralen Ökonomik, Springer VS, Wiesbaden, ISBN: 978-3-658-16145-3.

2017

  • A. Sohn (2017): Analysing Inequalities in Germany: A Structured Additive Distributional Regression Approach. Springer. ISBN 978-3-319-65331-0. Link.
  • A. Sohn (2017): The Regression of an Equitable Market Economy. Analysing Inequality in Germany from the Bottom Up Using Structured Additive Distributional Regression. My dissertation thesis.

Working Papers

  • For a list of current working papers and information what I am currently working on feel free to contact me.

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