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Network Search: Climbing the Job Ladder Faster

Marcelo Arbex, Dennis O'Dea () and David Wiczer
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Dennis O'Dea: Department of Economics, University of Washington

No 1606, Working Papers from University of Windsor, Department of Economics

Abstract: We introduce a complex network into a search model in which workers find jobs through their network or directly from firms. This framework links heterogeneity in network position to heterogeneity in wage-employment dynamics: better-connected workers climb the job ladder faster, drawing more frequently from the network offer distribution which stochastically dominates the direct-search distribution. The mean- field approach allows a tractable, recursive formulation and our calibrated version is consistent with several empirical findings. Further, we present new evidence consistent with our model: Job-to-job switches use networks more frequently at higher rungs of the ladder.

Keywords: Labor Markets; Social networks; Job search; Unemployment; Wages dispersion. (search for similar items in EconPapers)
JEL-codes: D83 D85 E24 J31 J64 (search for similar items in EconPapers)
Pages: 46 pages
Date: 2016-08
New Economics Papers: this item is included in nep-dge, nep-lab, nep-mac and nep-ure
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http://web2.uwindsor.ca/economics/RePEc/wis/pdf/1606.pdf First version, 2016 (application/pdf)

Related works:
Journal Article: NETWORK SEARCH: CLIMBING THE JOB LADDER FASTER (2019) Downloads
Working Paper: Network Search: Climbing the Job Ladder Faster (2018) Downloads
Working Paper: Network Search: Climbing the Job Ladder Faster (2018) Downloads
Working Paper: Network Search: Climbing the Job Ladder Faster (2016) Downloads
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