NETWORK SEARCH: CLIMBING THE JOB LADDER FASTER

• 成果类型: Article
• 署名作者: Arbex, Marcelo; O'Dea, Dennis; Wiczer, David
• 署名单位: University of Windsor; University of Washington; University of Washington Seattle; State University of New York (SUNY) System; Stony Brook University
• 刊物名称: INTERNATIONAL ECONOMIC REVIEW
• ISSN/ISSBN: 0020-6598
• DOI: 10.1111/iere.12375
• 发表日期: 2019
• 页码: 693-720
• 关键词: Social networks; equilibrium search; labor-markets; wage; EMPLOYMENT; dispersion; referrals; earnings; QUALITY; friends

摘要

We introduce an irregular network structure into a model of frictional, on-the-job search in which workers find jobs through their network connections or directly from firms. We show network-found jobs have higher wages, and thus better-connected workers climb the job ladder faster. The mean field approach allows us to formulate heterogeneous workers' recursive problem tractably. Our calibration is consistent with several empirical findings because of a composition-not information-effect. We also introduce new model-consistent evidence: Job-to-job switches at higher ladder rungs are more likely to use networks.