dr. Patricia Prüfer

About Patricia Prüfer

Patricia Prüfer is head of the Policy Research & Analysis Department at Centerdata. This department applies analytics, such as Data Science, Machine Learning and AI alongside quantitative methods, such as Econometrics and Behavioral Experiments. Patricia and her department evaluate and predict (effects of) policy and support the design of effective and efficient interventions: for example, in the program Smart Start in which a data-driven and knowledge-based method has been developed to work on prevention of complex social problems.

In her research, Patricia focuses on questions from education, labor, and behavioral economics, and combines data-driven decision making with appropriate (experimental) research designs as well as advanced data analysis techniques. As a linking pin between the worlds of research and policy, she regularly gives workshops, master classes, talks and guest lectures about digital transformation and the application of analytics to support diverse organizations, such as ministries, municipalities or civil society organizations.

Patricia is a member of the Analytics Advisory Committee of the Dutch Ministry of Finance and its subordinated public agencies. Moreover, she is a member of an Advisory Board at the Ministry of the Interior and the Ministry of Justice to advise on risk models and algorithms.

Since her PhD in Economics at Tilburg University on a dissertation in Econometrics in 2008, Patricia has remained an affiliate researcher at the Department of Economics at Tilburg University. For recent scientific publications, see below. For the whole list of publications, see: https://www.centerdata.nl/publicaties.

Publications (peer-reviewed)

Klein, T., Kurmangaliyeva, M., Prüfer J. and P. Prüfer (2025), How important are user-generated data for search-result quality? Experimental evidence, Journal of Law & Economics, 68(3).

Prüfer, P. & Den Uijl, M. (2024), Can occupational switches reduce labor market shortages? A skills-based optimization for labor market mobility [article in Dutch], Tijdschrift voor Arbeidsvraagstukken, 40, 222-235.

Prüfer, P., Den Uijl, M. and P. Kumar (2022), From jobs to skills: a data science approach [article in Dutch], Tijdschrift voor Arbeidsvraagstukken, 38.2, 237-260.

Prüfer, J., & Prüfer, P. (2020). Data Science for Entrepreneurship Research: Studying Demand Dynamics for Entrepreneurial Skills in the Netherlands, Small Business Economics, 55, 651-672.

Prüfer, P. & Kolthoff, E. (2020), Using data science to predict indicators of organized crime and subversion [article in Dutch],  Proces, 99, 85-101.

Gerritsen, S. & Prüfer, P. (2015), Field experiments for policy [article in Dutch], TPEdigitaal, 9, 21-31.

Magnus, J.R., Powell, O., and Prüfer, P. (2010), A comparison of two model averaging techniques with an application to growth empirics, Journal of Econometrics, 154, 139-153.

Other Publications

Prüfer, J. & Prüfer, P. (2018), Data Science for Institutional and Organizational Economics, in: A Research Agenda for New Institutional Economics, Claude Ménard and Mary M. Shirley (eds.), Edward Elgar Publishers, ISBN: 978 1 78811 250 5, (pp. 248-259).