 Network Search: Climbing the Job Ladder FasterMarcelo Arbex, Dennis O'Dea and David Wiczer Department of Economics Working Papers from Stony Brook University, Department of Economics Abstract: 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 that jobs found through network search have wages that stochastically dominate those found through direct contact. In irregular networks, heterogeneity in the worker’s position within the network leads to heterogeneity in wage and employment dynamics: better-connected workers climb the job ladder faster. Despite this rich heterogeneity from the network structure, the mean-field approach allows the problem of our workers to be formulated tractably and recursively. We then calibrate a quantitative version of our mechanism, showing it is consistent with several empirical findings regarding networks and labor markets: jobs found through networks have higher wages and last longer. Finally, we present new evidence consistent with our model that job-to-job switches at higher rungs of the ladder are more likely to use networks. Date: 2018 Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:nys:sunysb:18-04 Access Statistics for this paper More papers in Department of Economics Working Papers from Stony Brook University, Department of Economics Contact information at EDIRC. |
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