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Sam Desiere

Ghent University, Belgium

IZA World of Labor role

Author

Current position

Department of Economics, Ghent University, Belgium

Research interest

Labor economics, development economics

Website

https://biblio.ugent.be/person/802001203341

Qualifications

PhD Agricultural Economics, Ghent University, 2015

Selected publications

  • "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).

article(s)

  • Statistical profiling of unemployed jobseekers

    The increasing availability of big data allows for the profiling of unemployed jobseekers via statistical models

    Bert van Landeghem Sam Desiere Ludo Struyven , February 2021
    Statistical 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.
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