Ghent University, Belgium
IZA World of Labor role
Department of Economics, Ghent University, Belgium
Labor economics, development economics
PhD Agricultural Economics, Ghent University, 2015
"Using artificial intelligence to classify jobseekers: The accuracy-equity trade-off." Journal of Social Policy (2020) (with L. Struyven).
"Statistical profiling in public employment services: An international comparison." OECD Working Papers (2019) (with K. Langenbucher and L. Struyven).
"Contract farming for improving smallholder incomes: What can we learn from effectiveness studies?" World Development 104 (2018): 46–64 (with G. Ton, W. Villema, S. Weituschat, and M. D'Haese).
"Land productivity and plot size: Is measurement error driving the inverse relationship?" Journal of Development Economics 130 (2018): 84–98 (with D. Jolliffe).
"When the data source writes the conclusion: Evaluating agricultural policies." The Journal of Development Studies 52:9 (2016): 1372–1387 (with L. Staelens and M. D'Haese).
The increasing availability of big data allows for the profiling of unemployed jobseekers via statistical modelsStatistical models can help public employment services to identify factors associated with long-term unemployment and to identify at-risk groups. Such profiling models will likely become more prominent as increasing availability of big data combined with new machine learning techniques improve their predictive power. However, to achieve the best results, a continuous dialogue between data analysts, policymakers, and case workers is key. Indeed, when developing and implementing such tools, normative decisions are required. Profiling practices can misclassify many individuals, and they can reinforce but also prevent existing patterns of discrimination.MoreLess