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The More you Know: Information Effects in Job Application Rates by Gender in a Large Field Experiment

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Abstract

This paper presents the results from a field experiment which varies the amount of information seen by two million job seekers when viewing 100,000 job postings on a large online job posting website. The information seen is the true number of people who previously started an application. This intervention increases the likelihood a person will start/finish an application by 2-5%, representing a potential increase of thousands of applications per day. Beyond increasing applications, the treatment also changes the makeup of the applicant pool by increasing the number of women who apply.Firms in industries like high tech and finance that are highly represented on this job posting website, may be particularly interested in this low cost, light touch intervention to increase the number of female applicants.

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  • 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.
    • Handle: RePEc:tuf:tuftec:0780
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    Cited by:

    1. Bhole, Monica & Fradkin, Andrey & Horton, John, 2021. "Information About Vacancy Competition Redirects Job Search," SocArXiv p82fk, Center for Open Science.
    2. Mamertino, Mariano & Sinclair, Tara M., 2019. "Migration and online job search: A gravity model approach," Economics Letters, Elsevier, vol. 181(C), pages 51-53.
    3. Yan Chen & Joseph Konstan, 2015. "Online field experiments: a selective survey of methods," Journal of the Economic Science Association, Springer;Economic Science Association, vol. 1(1), pages 29-42, July.
    4. 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.
    5. Chen, Yan & Lu, Fangwen & Zhang, Jinan, 2017. "Social comparisons, status and driving behavior," Journal of Public Economics, Elsevier, vol. 155(C), pages 11-20.
    6. 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.
    7. 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.
    8. 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.
    9. Anya Samek, 2019. "Gender Differences in Job Entry Decisions: A University-Wide Field Experiment," Management Science, INFORMS, vol. 65(7), pages 3272-3281, July.

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