Referrals and Search Efficiency: Who Learns What and When?

• 成果类型: Article
• 署名作者: Barr, Tavis; Bojilov, Raicho; Munasinghe, Lalith
• 署名单位: Pontificia Universidad Catolica de Chile; Institut Polytechnique de Paris; ENSAE Paris; Ecole Polytechnique; Columbia University; Columbia University
• 刊物名称: JOURNAL OF LABOR ECONOMICS
• ISSN/ISSBN: 0734-306X
• DOI: 10.1086/703163
• 发表日期: 2019
• 页码: 1267-1300
• 关键词: Social networks; strong ties; EMPLOYMENT; selection; turnover

摘要

Referrals can improve screening and self-selection of applicants during the hiring process. We model and estimate how referral information affects the selection of employees through job offers, acceptances, and turnover. Using data from a call center company, we show that referrals help employers attract applicants of superior performance. Yet performance differences between referred and nonreferred workers diminish with tenure through selective turnover. Our estimates reveal that referrals allow employers to screen on hard-to-observe but performance-relevant attributes for employees of high performance and high propensity to stay. Thus, referred applicants complete much of the sorting during the hiring process.