Premium
NETWORK SEARCH: CLIMBING THE JOB LADDER FASTER
Author(s) -
Arbex Marcelo,
O'Dea Dennis,
Wiczer David
Publication year - 2019
Publication title -
international economic review
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.658
H-Index - 86
eISSN - 1468-2354
pISSN - 0020-6598
DOI - 10.1111/iere.12375
Subject(s) - climbing , climb , field (mathematics) , computer science , hill climbing , labour economics , mathematics , economics , artificial intelligence , engineering , structural engineering , pure mathematics , aerospace engineering
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 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.