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Place of Work and Place of Residence: Informal Hiring Networks and Labor Market Outcomes

  • Patrick Bayer

    (Yale University)

  • Stephen L. Ross

    (University of Connecticut)

  • Giorgio Topa

    (Federal Reserve Bank of New York)

We use a novel dataset and research design to empirically detect the effect of social interactions among neighbors on labor market outcomes. Specifically, using Census data that characterize residential and employment locations down to the city block, we examine whether individuals residing in the same block are more likely to work together than individuals in nearby but not identical blocks. We find significant evidence of social interactions operating at the block level: residing on the same versus nearby blocks increases the probability of working together by over 33 percent. The results also indicate that this referral effect is stronger when individuals are similar in sociodemographic characteristics (e.g., both have children of similar ages) and when at least one individual is well attached to the labor market. These findings are robust across various specifications intended to address concerns related to sorting and reverse causation. Further, having determined the characteristics of a pair of individuals that lead to an especially strong referral effect, we provide evidence that the increased availability of neighborhood referrals has a significant impact on a wide range of labor market outcomes including employment and wages.

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Paper provided by University of Connecticut, Department of Economics in its series Working papers with number 2004-07.

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Length: 51 pages
Date of creation: Mar 2004
Date of revision: Oct 2005
Handle: RePEc:uct:uconnp:2004-07
Note: The authors are grateful for helpful suggestions and comments from Joe Altonji, Pat Bajari, Ed Glaeser, Kevin Lang, Rob McMillan, David Neumark, Wilbert van der Klaauw, Ken Wolpin, and seminar participants at AEA, Boston College, Brown, Columbia, Cornell, Econometric Society, NY Fed, NYU, Southern Methodist, Stanford and Yale. Shihe Fu and Anupam Nanda have provided excellent research assistance. The authors are grateful to the Department of Housing and Urban Development, the Federal Reserve Bank of New York, and the Center for Real Estate and Urban Economic Studies at the University of Connecticut for financial support. The research in this paper was conducted while the authors were Special Sworn Status researchers of the U.S. Census Bureau at the Boston Census Research Data Center (BRDC). Research results and conclusions expressed are those of the authors and do not necessarily reflect the views of the Census Bureau. This paper has been screened to insure that no confidential data are revealed. The views and opinions offered in this paper do not necessarily reflect the position of the Federal Reserve Bank of New York, the Federal Reserve System, the U.S. Department of Housing and Urban Development or any other agency of the U.S. Government.
Contact details of provider: Postal: University of Connecticut 365 Fairfield Way, Unit 1063 Storrs, CT 06269-1063
Phone: (860) 486-4889
Fax: (860) 486-4463
Web page: http://www.econ.uconn.edu/

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