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Hiring and Learning in Online Global Labor Markets

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    Abstract

    This paper uses data from the online employer-freelancer matching platform freelancer.com to study the determinants of a match between an employer and a freelancer. Having to rely on a relatively small number of characteristics, employers use the freelancer's country of origin and reputation scores to infer the expected service quality. I find that freelancers from developing countries are less likely to be hired when they have no individual reputation, and as individual reputation becomes better this country effect disappears. This setting also allows me to study how employers' experience in past hires affects their behavior in current hires. I show that following a good match with a freelancer, employers are more likely to hire freelancers from the good match's country. I discuss how these findings contribute to our understanding of matching, learning, and discrimination in online settings.

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    File URL: http://www.netinst.org/Mill_11_17.pdf
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    Bibliographic Info

    Paper provided by NET Institute in its series Working Papers with number 11-17.

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    Length: 35 pages
    Date of creation: Sep 2011
    Date of revision: Oct 2011
    Handle: RePEc:net:wpaper:1117

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    Web page: http://www.NETinst.org/

    Related research

    Keywords: International outsourcing; Online labor market; Information acquisition; Quality reputations; Country-of-origin effect; Statistical discrimination;

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    1. John List, 2004. "The nature and extent of discrimination in the marketplace: Evidence from the field," Natural Field Experiments 00299, The Field Experiments Website.
    2. Chisik, Richard, 2003. "Export industry policy and reputational comparative advantage," Journal of International Economics, Elsevier, vol. 59(2), pages 423-451, March.
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    Cited by:
    1. Ajay Agrawal & John Horton & Nicola Lacetera & Elizabeth Lyons, 2013. "Digitization and the Contract Labor Market: A Research Agenda," NBER Chapters, in: Economics of Digitization National Bureau of Economic Research, Inc.
    2. Kevin Yili Hong & Alex Chong Wang & Paul A. Pavlou, 2013. "How does Bid Visibility Matter in Buyer-Determined Auctions? Comparing Open and Sealed Bid Auctions in Online Labor Markets," Working Papers 13-05, NET Institute.

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