Econometrics and Business Analytics

Welcome to the Econometrics and Business Analytics section. Overall, the section conducts research within the fields of business intelligence, econometrics, operations management and operations research.

Our research and teaching is undertaken by a team of 40 faculty members and 15 PhD students. We foster close collaboration within our section and with the international research community. Our research activities are supported by seminar series in business analytics and econometrics.

The section hosts Aarhus Center for Econometrics (ACE), which is designated as a centre of excellence in econometrics.

11 Mar

Wednesday 11 March 2026, at 12:15 Universitetsbyen 51, Building 1816, room 613

Title: The information matrix test for Markov switching autoregressive models with covariate-dependent transition probabilities

18 Mar

Wednesday 18 March 2026, at 12:30 Universitetsbyen 51, Building 1814, Room 151

Title: Solving block–structured Integer programs with soft coupling constraint using Multi–Objectivization

All seminars in this section

Centre of Excellence

Aarhus Center for Econometrics – ACE

ACE is a Centre of Excellence funded by the Danish National Research Foundation. The centre will gather the world's leading econometricians.

Recent publications

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Birch, C. R., Paaske, S. E., Jensen, M. B., Baunwall, S. M. D., Ehlers, L. H. & Hvas, C. L. (2025). Cost-effectiveness of faecal microbiota transplantation compared with vancomycin monotherapy for early Clostridioides difficile infection: economic evaluation alongside a randomized controlled trial. Journal of Hospital Infection, 155(1), 145-149. https://doi.org/10.1016/j.jhin.2024.11.003

Liengaard, B. D., Becker, J.-M., Bennedsen, M., Heiler, P., Taylor, L. N. & Ringle, C. M. (2025). Dealing with regression models’ endogeneity by means of an adjusted estimator for the Gaussian copula approach. Journal of the Academy of Marketing Science, 53, 279–299. https://doi.org/10.1007/s11747-024-01055-4

Guðmundsson, G. S. (2025). Detecting Giver and Receiver Spillover Groups in Large Vector Autoregressions. Journal of Business and Economic Statistics, 44(1), 297-308. https://doi.org/10.1080/07350015.2025.2526430

Bellia, M., Christensen, K., Kolokolov, A., Pelizzon, L. & Renò, R. (2025). Do designated market makers provide liquidity during downward extreme price movements? Journal of Financial Markets, 76, Article 100988. https://doi.org/10.1016/j.finmar.2025.100988

Clausen, J., Li, H. & Forget, N. J. (2025). Empirical risk minimization for big data driven prescriptive analytics: An exploration of two-stage stochastic programs with recourse. Expert Systems with Applications, 261, Article 125503. https://doi.org/10.1016/j.eswa.2024.125503

Bennedsen, M., Hillebrand, E., Koopman, S. J., Larsen, K. B. & Lupien, R. (2025). Estimating breakpoints in the Cenozoic Era: an econometric approach. Climate of the Past, 21(11). https://doi.org/10.5194/cp-21-1981-2025

Pedersen, C., Wulff, J. & Villadsen, A. R. (2025). Exploring the Relevance of Two-Part Models in Innovation Research: Towards a Better Understanding of Innovation Sales. International Journal of Innovation Management, 29(1-2), Article 2550007. https://doi.org/10.1142/S1363919625500070

Rafner, J., Tudoran, A. A., Beliatis, M. & Sherson, J. (2025). Framing the Future of Work: How Narrative Influences Perceptions of AI. In D. Pedreschi, M. Milano, I. Tiddi, S. Russell, C. Boldrini, L. Pappalardo, A. Passerini & S. Wang (Eds.), HHAI 2025 - Proceedings of the 4th International Conference on Hybrid Human-Artificial Intelligence (pp. 528-530). IOS Press. https://doi.org/10.3233/FAIA250683

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