Mismatch Unemployment

Aysegul Sahin, Joseph Song, Giorgio Topa and Giovanni Violante

No 18265, NBER Working Papers from National Bureau of Economic Research, Inc

Abstract: We develop a framework where mismatch between vacancies and job seekers across sectors translates into higher unemployment by lowering the aggregate job-finding rate. We use this framework to measure the contribution of mismatch to the recent rise in U.S. unemployment by exploiting two sources of cross-sectional data on vacancies, JOLTS and HWOL, a new database covering the universe of online U.S. job advertisements. Mismatch across industries and occupations explains at most 1/3 of the total observed increase in the unemployment rate, whereas geographical mismatch plays no apparent role. The share of the rise in unemployment explained by occupational mismatch is increasing in the education level.

JEL-codes: E24 J24 J61 J62 J63 J64 (search for similar items in EconPapers)
Date: 2012-08
New Economics Papers: this item is included in nep-lab and nep-mac
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Citations: View citations in EconPapers (17)

Published as Ay?egül ?ahin & Joseph Song & Giorgio Topa & Giovanni L. Violante, 2014. "Mismatch Unemployment," American Economic Review, American Economic Association, vol. 104(11), pages 3529-64, November.

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Related works:
Journal Article: Mismatch Unemployment (2014)
Working Paper: Mismatch Unemployment (2012)
Working Paper: Mismatch unemployment (2012)
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