The Facts About Referrals: Toward an Understanding of Employee Referral Networks

62 Pages Posted: 19 Apr 2013 Last revised: 25 Jan 2015

Stephen V. Burks

University of Minnesota, Morris - Division of Social Science; Institute for the Study of Labor (IZA); Center for Decision Research and Experimental Economics (CeDEx); Center for Transportation Studies, University of Minnesota

Bo Cowgill

University of California, Berkeley

Mitchell Hoffman

University of Toronto - Rotman School of Management

Michael Gene Housman

University of Pennsylvania - Health Care Systems Department

Multiple version iconThere are 2 versions of this paper

Date Written: December 11, 2013

Abstract

Using unique personnel data from nine large firms in three industries, we document five consistent facts about hiring through employee referral networks. First, referred applicants have similar skill characteristics to non-referred applicants, both observable-to-the-firm (e.g., schooling) and unobservable-to-the-firm (e.g., cognitive and non-cognitive ability), but are more likely to be hired, more likely to accept job offers, and have higher pre-job assessment scores. Second, referred workers have similar skill characteristics to non-referred workers. Third, referred workers are less likely to quit and are more productive, but only on rare high-impact performance metrics; on most standard non-rare performance metrics, referred and non-referred workers perform similarly. Fourth, referred workers have slightly higher wages, but yield substantially higher profits per worker. Fifth, workers who make referrals have higher productivity than others, are less likely to quit after making a referral, and refer those like themselves on particular productivity metrics. Differences between referred and non-referred workers tend to be larger at low-tenure levels; for young, Black, and Hispanic workers; and in strong labor markets. No leading class of theories can alone account for all or most of these results, leading us to suggest several theoretical extensions.

Keywords: Referrals, productivity, worker selection, innovation, patents, cognitive ability, non-cognitive ability, job testing

JEL Classification: J24, M51, J30, O32, J63

Suggested Citation

Burks, Stephen V. and Cowgill, Bo and Hoffman, Mitchell and Housman, Michael Gene, The Facts About Referrals: Toward an Understanding of Employee Referral Networks (December 11, 2013). Available at SSRN: https://ssrn.com/abstract=2253738 or http://dx.doi.org/10.2139/ssrn.2253738

Stephen V. Burks

University of Minnesota, Morris - Division of Social Science ( email )

600 East 4th St.
Morris, MN 56267
United States
320-589-6191 (Phone)
320-589-6117 (Fax)

HOME PAGE: http://www.morris.umn.edu/academics/truckingproject/

Institute for the Study of Labor (IZA)

P.O. Box 7240
Bonn, D-53072
Germany

HOME PAGE: http://www.iza.org/en/webcontent/personnel/photos/index_html?key=1883

Center for Decision Research and Experimental Economics (CeDEx) ( email )

University Park
Nottingham, NG7 2RD
United Kingdom

HOME PAGE: http://www.nottingham.ac.uk/cedex/people/external/index.aspx

Center for Transportation Studies, University of Minnesota ( email )

200 Transportation & Safety Bldg.
511 Washington Ave. SE
Minneapolis, MN
United States
612-626-1077 (Phone)
612-625-6381 (Fax)

HOME PAGE: http://www.cts.umn.edu/

Bo Cowgill

University of California, Berkeley ( email )

310 Barrows Hall
Berkeley, CA 94720
United States

Mitchell Hoffman (Contact Author)

University of Toronto - Rotman School of Management ( email )

105 St. George Street
Toronto, Ontario M5S 3E6
Canada

Michael Gene Housman

University of Pennsylvania - Health Care Systems Department ( email )

3641 Locust Walk
Colonial Penn Center
Philadelphia, PA 19104-6358
United States
215-681-6955 (Phone)

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