History Dependence, Cohort Attachment, and Job Referrals in Networks of Close Relationships

43 Pages Posted: 14 Oct 2019 Last revised: 8 Jan 2023

See all articles by Ayal Chen-Zion

Ayal Chen-Zion

Amazon.com, Inc.

James E. Rauch

University of California, San Diego (UCSD) - Department of Economics; National Bureau of Economic Research (NBER)

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Date Written: October 2019

Abstract

We model network formation in a firm. Agents learn about the quality of their working relationships with each other. Their good relationships become their networks. Accumulating relationships becomes increasingly costly, however. Over time agents become less open to forming relationships with others unknown to them, leading their networks to be front-loaded with agents they met near the beginning of their careers. The interaction of this dynamic with turnover yields predictions about the time pattern of history dependence in an agent’s network as a function of his tenure. Mutual openness of newly arrived agents in a firm also leads to the cross-section prediction of “cohort attachment,” a tendency for members of an agent’s hiring cohort to be disproportionately represented in his network. When members of a network formed within a firm are subsequently split across many firms, the desire to renew their successful working relationships can lead to job referrals. Former co-workers who provide referrals will be drawn disproportionately from the referred workers’ hiring cohorts at their previous employers.

Suggested Citation

Chen-Zion, Ayal and Rauch, James E., History Dependence, Cohort Attachment, and Job Referrals in Networks of Close Relationships (October 2019). NBER Working Paper No. w26358, Available at SSRN: https://ssrn.com/abstract=3469384

Ayal Chen-Zion (Contact Author)

Amazon.com, Inc. ( email )

Seattle, WA 98144
United States

James E. Rauch

University of California, San Diego (UCSD) - Department of Economics ( email )

9500 Gilman Drive
La Jolla, CA 92093-0508
United States
619-534-2405 (Phone)
619-534-7040 (Fax)

National Bureau of Economic Research (NBER)

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