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Structural Empirical Evaluation Of Job Search Monitoring

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  • Gerard J. van den Berg
  • Bas van der Klaauw

Abstract

To evaluate search effort monitoring of unemployed workers, it is important to take account of post‐unemployment wages and job‐to‐job mobility. We structurally estimate a model with search channels, using a controlled trial in which monitoring is randomized. The data include registers and survey data on search behavior. We find that the opportunity to move to better‐paid jobs in employment reduces the extent to which monitoring induces substitution toward formal search channels in unemployment. Job mobility compensates for adverse long‐run effects of monitoring on wages. We examine counterfactual policies against moral hazard, like reemployment bonuses and changes of the benefits path.

Suggested Citation

  • Gerard J. van den Berg & Bas van der Klaauw, 2019. "Structural Empirical Evaluation Of Job Search Monitoring," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 60(2), pages 879-903, May.
  • Handle: RePEc:wly:iecrev:v:60:y:2019:i:2:p:879-903
    DOI: 10.1111/iere.12376
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    References listed on IDEAS

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    1. Gerard J. van den Berg & Bas van der Klaauw, 2006. "Counseling And Monitoring Of Unemployed Workers: Theory And Evidence From A Controlled Social Experiment," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 47(3), pages 895-936, August.
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    Cited by:

    1. Bart Cockx & Muriel Dejemeppe & Andrey Launov & Bruno Van der Linden, 2018. "Imperfect Monitoring of Job Search: Structural Estimation and Policy Design," Journal of Labor Economics, University of Chicago Press, vol. 36(1), pages 75-120.
    2. Oliver Falck & Siegfried Schönherr, 2016. "An Economic Reform Agenda for Croatia: a comprehensive economic reform package prepared for the Croatian Statehood Foundation," ifo Forschungsberichte, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 70, September.
    3. Gürtzgen, Nicole & (né Nolte), André Diegmann & Pohlan, Laura & van den Berg, Gerard J., 2021. "Do digital information technologies help unemployed job seekers find a job? Evidence from the broadband internet expansion in Germany," European Economic Review, Elsevier, vol. 132(C).
    4. Lochner, Benjamin & Merkl, Christian & Stüber, Heiko & Gürtzgen, Nicole, 2021. "Recruiting intensity and hiring practices: Cross-sectional and time-series evidence," Labour Economics, Elsevier, vol. 68(C).
    5. Jonas Maibom, 2023. "The Welfare Effects Of Mandatory Reemployment Programs: Combining A Structural Model And Experimental Data," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 64(2), pages 607-640, May.
    6. Paul Muller & Bas van der Klaauw & Arjan Heyma, 2020. "Comparing econometric methods to empirically evaluate activation programs for job seekers," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(5), pages 526-547, August.
    7. Girum Abebe & Stefano Caria & Marcel Fafchamps & Paolo Falco & Simon Franklin & Simon Quinn & Forhad Shilpi, 2023. "Matching Frictions and Distorted Beliefs:Evidence from a Job Fair Experiment," Working Papers 958, Queen Mary University of London, School of Economics and Finance.
    8. Michael Weber, 2016. "The short-run and long-run effects of decentralizing public employment services," ifo Working Paper Series 209, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    9. Nicholas Lawson, 2023. "Optimal unemployment policy," Economic Inquiry, Western Economic Association International, vol. 61(3), pages 675-692, July.
    10. Lachowska, Marta & Meral, Merve & Woodbury, Stephen A., 2016. "Effects of the unemployment insurance work test on long-term employment outcomes," Labour Economics, Elsevier, vol. 41(C), pages 246-265.
    11. Malory Rennoir & Ilan Tojerow, 2019. "Évaluation de l’ensemble du dispositif de contrôle de la disponibilité des chômeurs, tel que mis en œuvre au sein du Forem," ULB Institutional Repository 2013/292150, ULB -- Universite Libre de Bruxelles.
    12. De Groote, Olivier, 2019. "Dynamic Effort Choice in High School: Costs and Benefits of an Academic Track," TSE Working Papers 19-1002, Toulouse School of Economics (TSE), revised Jun 2023.

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    More about this item

    JEL classification:

    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • J62 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Job, Occupational and Intergenerational Mobility; Promotion
    • J64 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Unemployment: Models, Duration, Incidence, and Job Search
    • J65 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Unemployment Insurance; Severance Pay; Plant Closings
    • J68 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Public Policy

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