Do Informal Referrals Lead to Better Matches? Evidence from a Firm's Employee Referral System

68 Pages Posted: 15 Aug 2012

See all articles by Meta Brown

Meta Brown

Federal Reserve Bank of New York

Elizabeth Setren

Massachusetts Institute of Technology (MIT)

Giorgio Topa

Federal Reserve Bank of New York

Multiple version iconThere are 2 versions of this paper

Date Written: August 1, 2012

Abstract

The limited nature of data on employment referrals in large business and household surveys has so far impeded our efforts to understand the relationships among employment referrals, match quality, wage trajectories, and turnover. Using a new firm-level data set that includes explicit information on whether a worker at the company was referred by a current employee, we are able to provide rich detail on these empirical relationships for a single U.S. corporation and to test various predictions of theoretical models of labor market referrals. Our results align with the following predictions: 1) referred candidates are more likely to be hired, 2) referred workers experience an initial wage advantage, 3) the wage advantage dissipates over time, 4) referred workers have longer tenure in the firm, and 5) the variances of the referred and nonreferred wage distributions converge over time. The richness of the data allows us to analyze the role of referrer-referee relationships, and the size and diversity of the corporation permit analysis of referrals at a wide variety of skill and experience levels.

Keywords: referrals, networks, personnel, wage mobility, turnover

JEL Classification: J30, J63, J64

Suggested Citation

Brown, Meta and Setren, Elizabeth and Topa, Giorgio, Do Informal Referrals Lead to Better Matches? Evidence from a Firm's Employee Referral System (August 1, 2012). FRB of New York Staff Report No. 568. Available at SSRN: https://ssrn.com/abstract=2130009 or http://dx.doi.org/10.2139/ssrn.2130009

Meta Brown (Contact Author)

Federal Reserve Bank of New York ( email )

33 Liberty Street
New York, NY 10045
United States

Elizabeth Setren

Massachusetts Institute of Technology (MIT) ( email )

77 Massachusetts Avenue
50 Memorial Drive
Cambridge, MA 02139-4307
United States

Giorgio Topa

Federal Reserve Bank of New York ( email )

33 Liberty Street
New York, NY 10045
United States

Register to save articles to
your library

Register

Paper statistics

Downloads
243
rank
25,149
Abstract Views
1,172
PlumX Metrics
!

Under construction: SSRN citations while be offline until July when we will launch a brand new and improved citations service, check here for more details.

For more information