IDEAS home Printed from https://ideas.repec.org/p/nbr/nberwo/33819.html
   My bibliography  Save this paper

Advising Job Seekers in Occupations with Poor Prospects: A Field Experiment

Author

Listed:
  • Michèle Belot
  • Bart K. de Koning
  • Didier Fouarge
  • Philipp Kircher
  • Paul Muller
  • Sandra Phlippen

Abstract

We study the impact of online information provision to unemployed job seekers who are looking for work in occupations in slack markets, i.e. with only few vacancies per job seeker. Job seekers received suggestions about suitable alternative occupations, and how the prospects of these alternatives compare to their current occupation of interest. Some additionally received a link to a motivational video. We evaluate the interventions using a randomized field experiment covering all eligible job seekers registered to search in the target occupations. The vast majority of treated job seekers open the message revealing the alternative suggestions. The motivational video is rarely watched. Effects on unemployed job seekers in structurally poor labor markets are large: their employment, hours of work and labor income all improve by 5% to 6% after 18 months. Additional survey evidence shows that treated job seekers find employment in more diverse occupations.

Suggested Citation

  • Michèle Belot & Bart K. de Koning & Didier Fouarge & Philipp Kircher & Paul Muller & Sandra Phlippen, 2025. "Advising Job Seekers in Occupations with Poor Prospects: A Field Experiment," NBER Working Papers 33819, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:33819
    Note: EFG LS
    as

    Download full text from publisher

    File URL: http://www.nber.org/papers/w33819.pdf
    Download Restriction: Access to the full text is generally limited to series subscribers, however if the top level domain of the client browser is in a developing country or transition economy free access is provided. More information about subscriptions and free access is available at http://www.nber.org/wwphelp.html. Free access is also available to older working papers.
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or

    for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Christopher A. Pissarides & Barbara Petrongolo, 2001. "Looking into the Black Box: A Survey of the Matching Function," Journal of Economic Literature, American Economic Association, vol. 39(2), pages 390-431, June.
    2. repec:hal:pseose:halshs-00840901 is not listed on IDEAS
    3. Michèle Belot & Philipp Kircher & Paul Muller, 2019. "Providing Advice to Jobseekers at Low Cost: An Experimental Study on Online Advice," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 86(4), pages 1411-1447.
    4. Bruno Crépon & Esther Duflo & Marc Gurgand & Roland Rathelot & Philippe Zamora, 2013. "Do Labor Market Policies have Displacement Effects? Evidence from a Clustered Randomized Experiment," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 128(2), pages 531-580.
    5. Broersma, Lourens & Van Ours, Jan C., 1999. "Job searchers, job matches and the elasticity of matching," Labour Economics, Elsevier, vol. 6(1), pages 77-93, March.
    6. David H. Autor & Frank Levy & Richard J. Murnane, 2003. "The Skill Content of Recent Technological Change: An Empirical Exploration," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 118(4), pages 1279-1333.
    7. van der Klaauw, Bas & Vethaak, Heike, 2022. "Empirical Evaluation of Broader Job Search Requirements for Unemployed Workers," IZA Discussion Papers 15698, Institute of Labor Economics (IZA).
    8. Altmann, Steffen & Glenny, Anita Marie & Mahlstedt, Robert & Sebald, Alexander, 2022. "The Direct and Indirect Effects of Online Job Search Advice," IZA Discussion Papers 15830, Institute of Labor Economics (IZA).
    9. Luc Behaghel & Sofia Dromundo & Marc Gurgand & Yagan Hazard & Thomas Zuber, 2022. "Encouraging and Directing Job Search: Direct and Spillover Effects in a Large Scale Experiment," Working papers 900, Banque de France.
    10. David H. Autor & Frank Levy & Richard J. Murnane, 2003. "The skill content of recent technological change: an empirical exploration," Proceedings, Federal Reserve Bank of San Francisco, issue nov.
    11. Bächli, Mirjam & Lalive, Rafael & Pellizzari, Michele, 2025. "Helping Jobseekers with Recommendations Based on Skill Profiles or Past Experience: Evidence from a Randomized Intervention," IZA Discussion Papers 17713, Institute of Labor Economics (IZA).
    12. Ioana Marinescu & Roland Rathelot, 2018. "Mismatch Unemployment and the Geography of Job Search," American Economic Journal: Macroeconomics, American Economic Association, vol. 10(3), pages 42-70, July.
    13. Danielle Li & Lindsey R. Raymond & Peter Bergman, 2020. "Hiring as Exploration," NBER Working Papers 27736, National Bureau of Economic Research, Inc.
    14. Ljubica Nedelkoska & Glenda Quintini, 2018. "Automation, skills use and training," OECD Social, Employment and Migration Working Papers 202, OECD Publishing.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Dabed, Diego & Genz, Sabrina & Rademakers, Emilie, 2025. "Equalising the effects of automation? The role of task overlap for job finding," Labour Economics, Elsevier, vol. 96(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Dabed, Diego & Genz, Sabrina & Rademakers, Emilie, 2025. "Equalising the effects of automation? The role of task overlap for job finding," Labour Economics, Elsevier, vol. 96(C).
    2. Diego Dabed Sitnisky & Sabrina Genz & Emilie Rademakers, 2023. "Resilience to Automation: The Role of Task Overlap for Job Finding," Working Papers 2312, Utrecht School of Economics.
    3. Leonardo Bonilla-Mejía & Luz A. Florez & Didier Hermida & Francisco Lasso & Leonardo Fabio Morales & Juan Jose Ospina & José Pulido, 2023. "Is the COVID-19 Pandemic Fast-Tracking Automation in Developing Countries? Evidence from Colombia," Journal of Human Capital, University of Chicago Press, vol. 17(4), pages 593-616.
    4. Tschopp, Jeanne, 2015. "The Wage Response to Shocks: The Role of Inter-Occupational Labour Adjustment," Labour Economics, Elsevier, vol. 37(C), pages 28-37.
    5. Kudoh, Noritaka & Miyamoto, Hiroaki, 2025. "Robots, AI, and unemployment," Journal of Economic Dynamics and Control, Elsevier, vol. 174(C).
    6. Isabel Cairó & Tomaz Cajner, 2018. "Human Capital and Unemployment Dynamics: Why More Educated Workers Enjoy Greater Employment Stability," Economic Journal, Royal Economic Society, vol. 128(609), pages 652-682, March.
    7. Mirjam Bächli & Hélène Benghalem & Doriana Tinello & Damaris Aschwanden & Sascha Zuber & Matthias Kliegel & Michele Pellizzari & Rafael Lalive, 2024. "Ranking occupations by their proximity to workers’ profiles," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 160(1), pages 1-17, December.
    8. Caselli, Mauro & Fracasso, Andrea & Scicchitano, Sergio & Traverso, Silvio & Tundis, Enrico, 2025. "What workers and robots do: An activity-based analysis of the impact of robotization on changes in local employment," Research Policy, Elsevier, vol. 54(1).
    9. Goos, Maarten & Rademakers, Emilie & Röttger, Ronja, 2021. "Routine-Biased technical change: Individual-Level evidence from a plant closure," Research Policy, Elsevier, vol. 50(7).
    10. Montobbio, Fabio & Staccioli, Jacopo & Virgillito, Maria Enrica & Vivarelli, Marco, 2022. "Robots and the origin of their labour-saving impact," Technological Forecasting and Social Change, Elsevier, vol. 174(C).
    11. Włoch, Renata & Śledziewska, Katarzyna & Rożynek, Satia, 2025. "Who's afraid of automation? Examining determinants of fear of automation in six European countries," Technology in Society, Elsevier, vol. 81(C).
    12. Guo, Yuchen Mo & Falck, Oliver & Langer, Christina & Lindlacher, Valentin & Wiederhold, Simon, 2024. "Training, Automation, and Wages: Worker-Level Evidence," VfS Annual Conference 2024 (Berlin): Upcoming Labor Market Challenges 302366, Verein für Socialpolitik / German Economic Association.
    13. Fernández-Macías, Enrique & Klenert, David & Antón, José-Ignacio, 2021. "Not so disruptive yet? Characteristics, distribution and determinants of robots in Europe," Structural Change and Economic Dynamics, Elsevier, vol. 58(C), pages 76-89.
    14. Cairo, Sofie & Mahlstedt, Robert, 2023. "The disparate effects of information provision: A field experiment on the work incentives of social welfare," Journal of Public Economics, Elsevier, vol. 226(C).
    15. Hensvik, Lena & Skans, Oskar Nordström, 2023. "The skill-specific impact of past and projected occupational decline," Labour Economics, Elsevier, vol. 81(C).
    16. Carlos Carrillo‐Tudela & Ludo Visschers, 2023. "Unemployment and Endogenous Reallocation Over the Business Cycle," Econometrica, Econometric Society, vol. 91(3), pages 1119-1153, May.
    17. Kaltenberg, Mary & Foster-McGregor, Neil, 2020. "The impact of automation on inequality across Europe," MERIT Working Papers 2020-009, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    18. Richiardi, Matteo & Westhoff, Leonie & Astarita, Caterina & Ernst, Ekkehard & Fenwick, Clare & Khabirpour, Neysan & Pelizzari, Lorenzo, 2024. "The impact of a decade of digital transformation on employment, wages, and inequality in the EU: a “conveyor belt†hypothesis," Centre for Microsimulation and Policy Analysis Working Paper Series CEMPA5/24, Centre for Microsimulation and Policy Analysis at the Institute for Social and Economic Research.
    19. Brunello, Giorgio & Wruuck, Patricia, 2019. "Skill Shortages and Skill Mismatch in Europe: A Review of the Literature," IZA Discussion Papers 12346, Institute of Labor Economics (IZA).
    20. Malo, Miguel & Cueto, Begoña, 2019. "Do old and new labour market risks overlap? Automation, offshorability, and non-standard employment," MPRA Paper 95058, University Library of Munich, Germany.

    More about this item

    JEL classification:

    • C93 - Mathematical and Quantitative Methods - - Design of Experiments - - - Field Experiments
    • 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

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nbr:nberwo:33819. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/nberrus.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.