Quantitative / Empirical Methods and Data Science
The Quant group is dedicated to developing and utilizing advanced quantitative methods in the context of operations research, econometrics, and experimental economics. We firmly believe that important challenges and problems can only be adequately addressed by further development of research methods. The development of new concepts and techniques are therefore required to better analyze and understand a multitude of empirical problems that are relevant for economics and business. Whether through developing new methods, applying existing techniques to new contexts, or collaborating with other researchers and practitioners, the group is always striving to push the boundaries of what is possible and to contribute to theoretically sound and data-based solutions.
We work with a wide range of methods including machine learning, optimization, forecasting, time series analysis, revealed preferences, experimental methods, simulation, panel data econometrics, micro econometrics, and benchmarking. These methods allow us to approach problems in a systematic and data-driven way, using rigorous analytical techniques to uncover insights and inform decision-making.
In terms of subject areas, the group is focused on addressing a range of societal and business challenges such as energy, innovation, health, inequality, and transparency., We emphasize, though, the interdisciplinary relevance of our contributions, which is manifested by publications and citations in leading statistics, medical research and industrial engineering journals.
Faculty
External Funding
International and national public and private foundations have supported the research carried out in our group. Below a list of current externally funded projects:
1) Public Sector Performance Measurement (Peter Bogetoft). Rockwool Foundation.
2) Benchmarking-based incentives and regulatory applications (Peter Bogetoft, Dolores Romero Morales, Aleksandrs Smilgins). Danish Research Council.
3) H2020 MSCA RISE NeEDS (Peter Bogetoft, Dolores Romero Morales). EU.
4) Market design for a decentralized integrated European energy transformation (Jens Weibezahn), H2020 project, European Commission.
5) Sustainable Innovative digitalized Network of Urban logistics (Dolores Romero Morales), Sino-European Call, European Commission and InnovationFund.
Courses
Our group teaches courses in Operations Research, Game Theory, Econometrics, Time Series Analysis, Data Science, Machine Learning and Benchmarking at both BSc, MSc and PhD levels. It offers the Minor in Quantitative Methods in Economics, Business and Finance.
Publications
We carry out research at a high international level published in highly ranked journals. Below are a few examples from the past five years:
2023:
[1] How flexible electrification can integrate fluctuating renewables, Energy, 2023. (Jens Weibezahn)
2022:
[1] Distinguishing Useful and Wasteful Slack, Operations Research, 2022. (Peter Bogetoft)
[2] Fertility, Economic Incentives and Individual Heterogeneity: Register Data‐based Evidence from France and Germany, Journal of the Royal Statistical Society, Series A, 2022. (Ralf Wilke)
[3] Goals, Constraints, and Transparently Fair Assignments: A Field Study of Randomization Design in the UEFA Champions League, Management Science, 2022. (Marta Boczon)
[2] Interpreting Clusters via Prototype Optimization, Omega, 2022. (Dolores Romero Morales)
[3] Measuring the Ex-ante Incentive Effects of Creditor Control Rights during Bankruptcy Reorganization, Journal of Financial Economics, 2022. (Jimmy Martinez-Correa)
[4] On Sparse Optimal Regression Trees, European Journal of Operational Research, 2022. (Dolores Romero Morales)
[5] Responses to Eliminating Saving Commitments: Evidence from Mortgage Run-off, Journal of Money, Credit and Banking, 2022. (Jimmy Martinez-Correa)
[6] Risk Attitudes, Sample Selection and Attrition in Longitudinal Field Experiment, Review of Economics & Statistics, 2020. (Morten Lau)
2020:
[1] Balanced Growth Approach to Tracking Recessions, Econometrics, 2020 (Marta Boczon)
[2] Feature Selection in Data Envelopment Analysis: A Mathematical Optimization Approach, Omega, 2020. (Dolores Romero Morales)
[3] Foreign Influence, Control, and Indirect Ownership: Implications for Productivity Spillovers, Journal of International Business Studies, 2020. (Lisbeth la Cour)2019:
[1] Mix Stickiness under Asymmetric Cost Information, Management Science, 2019. (Peter Bogetoft)
2018:
[1] Asset Integration and Attitudes to Risk: Theory and Practice, Review of Economics & Statistics, 2018. (Morten Lau)
[2] Multiattribute Utility Theory, Intertemporal Utility and Correlation Aversion, International Economic Review, 2018. (Morten Lau)
[3] Procurement with Asymmetric Information about Fixed and Variable Costs, Journal of Accounting Research, 2018. (Peter Bogetoft)