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Learning Through Coworker Referrals

Authors: Glitz, Albrecht; Vejlin, Rune;

Learning Through Coworker Referrals

Abstract

In this paper, we study the role of coworker referrals for labor market outcomes. Using comprehensive Danish administrative data covering the period 1980 to 2005, we first document a strong tendency of workers to follow their former coworkers into the same establishments and provide evidence that these mobility patterns are likely driven by coworker referrals. Treating the presence of a former coworker in an establishment at the time of hiring as a proxy for a referral, we then show that referred workers initially earn 4.6 percent higher wages and are 2.3 percentage points less likely to leave their employers than workers hired through the external market. Consistent with a theoretical framework characterized by higher initial uncertainty in the external market but the possibility of subsequent learning about match-specific productivity, we show that these initial differences gradually decline as tenure increases. We structurally estimate a stylized model using indirect inference and find that the noise of the initial signal about a worker’s productivity is 14.5 percent lower in the referral market than in the external market, and that firms learn about their workers’ true match-specific productivity with a probability of 48.4 percent per year. Counterfactual simulations show that average wages are lower in the absence of a referral market, primarily because of lower average match productivity in the external market.

Albrecht Glitz gratefully acknowledges financial support from the Spanish Ministerio de Economía y Competitividad (through the Severo Ochoa Programme for Centres of Excellence in R&D (SEV-2015-0563) and Project No. ECO2014-52238-R) and the Spanish Ministerio de Ciencia, Innovación y Universidades (Project No. ECO2017-83668-R (AEI/FEDER, UE) and Ramón y Cajal Grant RYC-2015-18806). He also thanks the German Research Foundation (DFG) for funding his Heisenberg Fellowship (GL 811/1-1) and Alexandra Spitz-Oener for hosting him at Humboldt University Berlin between October 2014 and December 2016.

Countries
Denmark, Spain
Keywords

Employer learning, ddc:330, turnover, Wages, wages, Referrals, employer learning, Turnover, networks, referrals, J63, J31, J64, Networks

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
16
Top 10%
Average
Top 10%
Green
bronze