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Mismatch unemployment

  • Aysegül Sahin
  • 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 one-third 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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Paper provided by Federal Reserve Bank of New York in its series Staff Reports with number 566.

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Date of creation: 2012
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Handle: RePEc:fip:fednsr:566
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