IDEAS home Printed from https://ideas.repec.org/a/fip/fedhep/00018.html

What Does Online Job Search Tell Us about the Labor Market?

Author

Listed:
  • R. Jason Faberman
  • Marianna Kudlyak

Abstract

This article finds that in 2011, online job search was much more prevalent and significantly more effective in helping job seekers gain employment than about a decade earlier. Moreover, it shows that online job search data generally capture the aggregate patterns of the U.S. labor market. The authors discuss the advantages and disadvantages of using these data for research, and summarize related studies.

Suggested Citation

  • R. Jason Faberman & Marianna Kudlyak, 2016. "What Does Online Job Search Tell Us about the Labor Market?," Economic Perspectives, Federal Reserve Bank of Chicago, issue 1, pages 1-15.
  • Handle: RePEc:fip:fedhep:00018
    as

    Download full text from publisher

    File URL: https://www.chicagofed.org/~/media/publications/economic-perspectives/2016/ep2016-1-pdf.pdf?la=en
    File Function: Full text
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Vera Brenčič, 2012. "Wage posting: evidence from job ads," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 45(4), pages 1529-1559, November.
    2. Jennifer Brown & David A. Matsa, 2016. "Boarding a Sinking Ship? An Investigation of Job Applications to Distressed Firms," Journal of Finance, American Finance Association, vol. 71(2), pages 507-550, April.
    3. Robert E. Hall & Alan B. Krueger, 2012. "Evidence on the Incidence of Wage Posting, Wage Bargaining, and On-the-Job Search," American Economic Journal: Macroeconomics, American Economic Association, vol. 4(4), pages 56-67, October.
    4. Peter Kuhn & Hani Mansour, 2014. "Is Internet Job Search Still Ineffective?," Economic Journal, Royal Economic Society, vol. 124(581), pages 1213-1233, December.
    5. Ioana Marinescu & Ronald Wolthoff, 2020. "Opening the Black Box of the Matching Function: The Power of Words," Journal of Labor Economics, University of Chicago Press, vol. 38(2), pages 535-568.
    6. Marinescu, Ioana, 2017. "The general equilibrium impacts of unemployment insurance: Evidence from a large online job board," Journal of Public Economics, Elsevier, vol. 150(C), pages 14-29.
    7. Moen, Espen R, 1997. "Competitive Search Equilibrium," Journal of Political Economy, University of Chicago Press, vol. 105(2), pages 385-411, April.
    8. Kory Kroft & Devin G. Pope, 2014. "Does Online Search Crowd Out Traditional Search and Improve Matching Efficiency? Evidence from Craigslist," Journal of Labor Economics, University of Chicago Press, vol. 32(2), pages 259-303.
    9. Delgado Helleseter, Miguel & Kuhn, Peter J. & Shen, Kailing, 2016. "Age and Gender Profiling in the Chinese and Mexican Labor Markets: Evidence from Four Job Boards," IZA Discussion Papers 9891, IZA Network @ LISER.
    10. Kory Kroft & Fabian Lange & Matthew J. Notowidigdo, 2013. "Duration Dependence and Labor Market Conditions: Evidence from a Field Experiment," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 128(3), pages 1123-1167.
    11. Amanda Pallais & Emily Glassberg Sands, 2016. "Why the Referential Treatment? Evidence from Field Experiments on Referrals," Journal of Political Economy, University of Chicago Press, vol. 124(6), pages 1793-1828.
    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. Miguel Delgado Helleseter & Peter Kuhn & Kailing Shen, 2020. "The Age Twist in Employers’ Gender Requests: Evidence from Four Job Boards," Journal of Human Resources, University of Wisconsin Press, vol. 55(2), pages 428-469.
    14. Laura Gee, 2014. "The More you Know: Information Effects in Job Application Rates by Gender in a Large Field Experiment," Discussion Papers Series, Department of Economics, Tufts University 0780, Department of Economics, Tufts University.
    15. Peter Kuhn & Mikal Skuterud, 2004. "Internet Job Search and Unemployment Durations," American Economic Review, American Economic Association, vol. 94(1), pages 218-232, March.
    16. Coles, Melvyn G & Smith, Eric, 1998. "Marketplaces and Matching," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(1), pages 239-254, February.
    Full references (including those not matched with items on IDEAS)

    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. Suguru Otani, 2024. "Nonparametric Estimation of Matching Efficiency and Elasticity on a Private On-the-Job Search Platform: Evidence from Japan, 2014-2024," Papers 2410.17011, arXiv.org, revised Nov 2025.
    2. Fabo, B., 2017. "Towards an understanding of job matching using web data," Other publications TiSEM b8b877f2-ae6a-495f-b6cc-9, Tilburg University, School of Economics and Management.
    3. Otani, Suguru, 2026. "Nonparametric estimation of matching efficiency and elasticity on a private on-the-job search platform: Evidence from Japan, 2014–2024," Journal of the Japanese and International Economies, Elsevier, vol. 79(C).
    4. Michèle Belot & Philipp Kircher & Paul Muller, 2022. "How Wage Announcements Affect Job Search—A Field Experiment," American Economic Journal: Macroeconomics, American Economic Association, vol. 14(4), pages 1-67, October.
    5. Hayato Kanayama & Suguru Otani, 2024. "Nonparametric Estimation of Matching Efficiency and Elasticity in a Spot Gig Work Platform: 2019-2023," Papers 2412.19024, arXiv.org, revised Jun 2026.
    6. R. Jason Faberman & Marianna Kudlyak, 2019. "The Intensity of Job Search and Search Duration," American Economic Journal: Macroeconomics, American Economic Association, vol. 11(3), pages 327-357, July.
    7. Ioana Marinescu & Ronald Wolthoff, 2020. "Opening the Black Box of the Matching Function: The Power of Words," Journal of Labor Economics, University of Chicago Press, vol. 38(2), pages 535-568.
    8. 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.
    9. Morgan Raux, 2019. "Looking for the "Best and Brightest": Hiring difficulties and high-skilled foreign workers," AMSE Working Papers 1934, Aix-Marseille School of Economics, France.
    10. Faberman, R. Jason & Menzio, Guido, 2018. "Evidence on the relationship between recruiting and the starting wage," Labour Economics, Elsevier, vol. 50(C), pages 67-79.
    11. He, Chuan & Mau, Karsten & Xu, Mingzhi, 2021. "Trade Shocks and Firms Hiring Decisions: Evidence from Vacancy Postings of Chinese Firms in the Trade War," Labour Economics, Elsevier, vol. 71(C).
    12. repec:crm:wpaper:2511 is not listed on IDEAS
    13. Bhuller, Manudeep & Kostøl, Andreas & Vigtel, Trond Christian, 2019. "How Broadband Internet Affects Labor Market Matching," Memorandum 10/2019, Oslo University, Department of Economics.
    14. Tara Sinclair & Mariano Mamertino, 2016. "Online Job Search and Migration Intentions Across EU Member States," Working Papers 2016-5, The George Washington University, Institute for International Economic Policy.
    15. Potter, Tristan, 2024. "Destabilizing search technology," Journal of Monetary Economics, Elsevier, vol. 145(C).
    16. Philipp Kircher & Paul Muller & Michele Belot, 2017. "How Wage Announcements Affect Job Search Behaviour - A Field Experimental Investigation," 2017 Meeting Papers 722, Society for Economic Dynamics.
    17. Brenčič, Vera, 2024. "Terms of use and network size: Evidence from online job boards and CV banks in the U.S," Information Economics and Policy, Elsevier, vol. 67(C).
    18. Stefano Banfi & Benjamín Villena-Roldán, 2019. "Do High-Wage Jobs Attract More Applicants? Directed Search Evidence from the Online Labor Market," Journal of Labor Economics, University of Chicago Press, vol. 37(3), pages 715-746.
    19. Edward P. Lazear & Kathryn L. Shaw & Christopher T. Stanton, 2016. "Who Gets Hired? The Importance of Finding an Open Slot," NBER Working Papers 22202, National Bureau of Economic Research, Inc.
    20. Kircher, Philipp & Wright, Randall & Julien, Benoit & Guerrieri, Veronica, 2017. "Directed Search: A Guided Tour," CEPR Discussion Papers 12315, Centre for Economic Policy Research.
    21. Bhole, Monica & Fradkin, Andrey & Horton, John, 2021. "Information About Vacancy Competition Redirects Job Search," SocArXiv p82fk, Center for Open Science.

    More about this item

    Keywords

    ;
    ;

    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:fip:fedhep:00018. 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: Lauren Wiese (email available below). General contact details of provider: https://edirc.repec.org/data/frbchus.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.