dr. Patricia Prüfer

About Patricia Prüfer

Since January 2022 Patricia Prüfer has been Head of the Policy Research & Analytics Department at Centerdata. This department applies quantitative methods such as Data Science & Machine Learning, econometrics and behavioral experiments to evaluate and predict (effects of) policies. Moreover, our department helps to design more effective and efficient data-driven policies, often focused on prevention.

In her research Patricia combines a deep knowledge of (educational) economics, the labor market, behavioral economics, data science and data-driven decision making with appropriate (experimental) research designs and advanced data analysis techniques. One of the main topics is how individuals and institutions respond to (changes in) policy, and how behavior can be optimally influenced. In addition, Patricia supports organizations, such as ministries, municipalities, or companies, in applying more data-driven strategies and acts as a linking pin between the worlds of research and policy.

Patricia has extensive experience in conducting scientific (contract) research, managing large and complex projects, writing scientific articles and policy reports, and presenting research results to diverse audiences. She regularly gives workshops and (guest) lectures and participates in scientific committees, for example at NRO or ZonMw.

Patricia received her PhD in Economics from Tilburg University in 2008 with a thesis on “Model Uncertainty in Growth Empirics” (applying Bayesian Model Averaging and MC³ algorithms, in fact just a form of Random Forest ;). From 2008-2015 she worked as researcher at the Netherlands Bureau for Economic Policy Analysis (CPB). During this period, Patricia had also been affiliated researcher at Tilburg University. Since 2015 Patricia has been working at Centerdata, first as senior researcher at the Quantitative Analyses Department and as of 2018 as Head of Centerdata’s Data Science Unit.

Publications (peer-reviewed)

Prüfer, J., & Prüfer, P. (2020). Data Science for Entrepreneurship Research: Studying Demand Dynamics for Entrepreneurial Skills in the Netherlands, Small Business Economics, 55, 651-6712.

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

Gerritsen, S. and Prüfer, P. (2015), “Veldexperimenten voor beleid”, 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. and 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).

Scientific Reports (in Dutch)

Prüfer, P., Den Uijl, M. and P. Kumar (2021), Arbeidsmarktonderzoek ICT met Topsectoren 2021, Centerdata.

Prüfer, P. and Den Uijl, M. (2021), Instrument Transitiepaden Klimaatakkoord, Centerdata.

Prüfer, P., Den Uijl, M. and P. Kumar (2020), Arbeidsmarktonderzoek ICT 2020, Centerdata.

Prüfer, P. and Den Uijl, M. (2020), Transitiemogelijkheden in coronatijd voor de topsector Energie, Centerdata.

Höcük, S., Prüfer, P., Den Uijl, M. and Kumar, P. (2020), AI-handleiding en stappenplan voor de casus bijstand van gemeente Den Haag: AI binnen de Overheid, Centerdata.

Prüfer, P., Den Uijl, M. and P. Kumar (2019), Arbeidsmarktonderzoek ICT met topsectoren, Centerdata.

Bolsius, Y., Höcük, S. and P. Prüfer (2018), Indicatoren van (georganiseerde) criminaliteit en ondermijning op bedrijventerreinen: Een verkennend onderzoek in de gemeente Tilburg, Centerdata.

Prüfer, P. and Kieruj, N. (2017), Data science maturity van gemeenten: Centerdata & JADS.

Prüfer, P., Kieruj, N. and Mulder, J. (2017), Evaluatie “Wie wil jij zijn?”, Centerdata.

Prüfer, P., Cuelenaere, B., Mulder, J. and Kieruj, N. (2017), Experiment inlichtingenplicht Algemene nabestaandenwet (Anw): Centerdata.

Fontein, P.F., Vloet, A., M. Uijl, den, Prüfer, P., Adriaens, H. and de Vos, K. (2017), IPTO: vakken en bevoegdheden peildatum 1 oktober 2015: Centerdata.

Fontein, P.F., Prüfer, P., de Vos, K. and Vloet, A. (2016), IPTO: vakken en bevoegdheden peildatum 1 oktober 2014: Centerdata.

Prüfer, P. (2015). Knelpuntregio’s lerarenarbeidsmarkt: een eerste verkenning: CPB Achtergronddocument, CPB, The Hague.

Working Papers

Prüfer, P., Den Uijl, M. and P. Kumar (2021), Digitalisering en transformatie van de arbeidsmarkt: een skills-based data science benadering, mimeo, Centerdata. Submitted for publication.

Prüfer, P., Den Uijl, M. and P. Kumar (2019), Dynamics of skills demand and job transitions opportunities: A machine learning approach, mimeo, Centerdata.

Prüfer, P. and Tondl. G. (2008), “The FDI-growth nexus in Latin America: the role of source countries and local conditions”, CentER DP No. 2008-61.

Prüfer, P. and Klump, R. (2006), “A robust ranking of pro-poor growth policies: the case of Vietnam”, CentER DP No. 2006-117.