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Mismatch Unemployment

Listed author(s):
  • Ayşegül Şahin
  • Joseph Song
  • Giorgio Topa
  • Giovanni L. Violante

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.

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File URL: http://www.nber.org/papers/w18265.pdf
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Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 18265.

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Date of creation: Aug 2012
Publication status: 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.
Handle: RePEc:nbr:nberwo:18265
Note: EFG LS
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