Econometrics and Business Analytics
Welcome to the Econometrics and Business Analytics section. Overall, the section conducts research within the fields of business analytics, business intelligence and econometrics.
Our focus on business intelligence, econometrics, and operations management is supported by a team of 40 faculty members and 15 PhD students. We run two research seminars: One in business statistics and econometrics, and another in operations research and logistics. We collaborate closely within our group and with the international research community.
The section hosts the DNFR Chair in Econometrics and will host Aarhus Center for Econometrics when it opens in 2025.
Recent publications
Marks, K. P., Aalders, J., Liu, S., Broadley, M., Thastum, M., Jensen, M. B., Ibfelt, E. H., Birkebæk, N. H. & Pouwer, F. (2024). Associations between disordered eating behaviors and HbA1c in young people with type 1 diabetes: a systematic review and meta-analysis. Current Diabetes Reviews, 20(4), Article e220823220144 . https://doi.org/10.2174/1573399820666230822095939
Cavaliere, G., Gonçalves, S., Nielsen, M. Ø. & Zanelli, E. (2024). Bootstrap Inference in the Presence of Bias. Journal of the American Statistical Association, 119(548), 2908-2918. https://doi.org/10.1080/01621459.2023.2284980
Aabo, T., Pantzalis, C., Park, J. C., Trigeorgis, L. & Wulff, J. (2024). CEO personality traits, strategic flexibility, and firm dynamics. Journal of Corporate Finance, 84, Article 102524. https://doi.org/10.1016/j.jcorpfin.2023.102524
Silvennoinen, A. & Teräsvirta, T. (2024). Consistency and asymptotic normality of maximum likelihood estimators of a multiplicative time-varying smooth transition correlation GARCH model. Econometrics and Statistics, 32, 57-72. https://doi.org/10.1016/j.ecosta.2021.07.008
Sørensen, M. M. & Letchford, A. N. (2024). CP-Lib: Benchmark instances of the clique partitioning problem. Mathematical Programming Computation, 16(1), 93-111. https://doi.org/10.1007/s12532-023-00249-1
Verma, S., Singh, V., Tudoran, A. A. & Bhattacharyya, S. S. (2024). Elevating employees’ psychological responses and task performance through responsible artificial intelligence. Information Technology and People, 37(7), 2551-2567. https://doi.org/10.1108/ITP-05-2023-0431
Richter, N. F. & Tudoran, A. A. (2024). Elevating theoretical insight and predictive accuracy in business research: Combining PLS-SEM and selected machine learning algorithms. Journal of Business Research, 173(114453), Article 114453. https://doi.org/10.1016/j.jbusres.2023.114453
Christensen, B. J., Neri, L. & Parra-Alvarez, J. C. (2024). Estimation of continuous-time linear DSGE models from discrete-time measurements. Journal of Econometrics, 244(2), Article 105871. https://doi.org/10.1016/j.jeconom.2024.105871