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Mismatch unemployment

Author

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  • Aysegul Sahin
  • Joseph Song
  • Giorgio Topa
  • Giovanni L. Violante

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 one-third of the total observed increase in the unemployment rate. Geographical mismatch plays no apparent role. Occupational mismatch has become especially more severe for college graduates, and in the West of the United States.

Suggested Citation

  • Aysegul Sahin & Joseph Song & Giorgio Topa & Giovanni L. Violante, 2012. "Mismatch unemployment," Staff Reports 566, Federal Reserve Bank of New York.
  • Handle: RePEc:fip:fednsr:566
    Note: For a published version of this report, see Ayşegül Şahin, Joseph Song, Giorgio Topa, and Giovanni L. Violante, "Mismatch Unemployment," American Economic Review 104, no. 11 (November 2014): 3529-64.
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    More about this item

    Keywords

    unemployment; vacancies; mismatch;
    All these keywords.

    JEL classification:

    • E24 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Employment; Unemployment; Wages; Intergenerational Income Distribution; Aggregate Human Capital; Aggregate Labor Productivity
    • J23 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Demand
    • J63 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Turnover; Vacancies; Layoffs
    • J64 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Unemployment: Models, Duration, Incidence, and Job Search

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