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Turbulence and unemployment in matching models

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Abstract

Steven Weinberg (2018) says: (1) new theories that target new observations should be constrained to agree with observations successfully represented by existing theories; and(2) preserving successes of earlier theories helps to discover unanticipated understandings of yet other phenomena. Weinberg’s advice helps us to answer the question: how do higher risks of skill losses coinciding both with involuntary layoffs (“layoff turbulence†) and with voluntary quits (“quit turbulence†) affect equilibrium unemployment rates? An earlier analysis that had included only layoff turbulence had established a positive relationship between turbulence and the unemployment rate within generous welfare states, but the absence of that relationship in countries with stingier welfare states. A subsequent influential analysis found that even very small amounts of quit turbulence would lead to a negative relationship between turbulence and unemployment rates. But that finding was based on a peculiar calibration of a productivity distribution that generates returns to labor mobility that make the model miss the positive turbulence-unemployment rate relationship that has been a theoretical basis for explaining the the persistent trans-Atlantic unemployment divide that emerged in post 1970s data and also miss observations about labor market churning. Repairing the faulty calibration of that productivity distribution not only brings models with quit turbulence into line with those observations but also puts the spotlight on macro-labor calibration strategies and implied returns to labor mobility.

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  • Isaac Baley & Lars Ljungqvist & Thomas J. Sargent, 2018. "Turbulence and unemployment in matching models," Economics Working Papers 1598, Department of Economics and Business, Universitat Pompeu Fabra, revised Jul 2020.
  • Handle: RePEc:upf:upfgen:1598
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    Cited by:

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    4. Andre Luduvice & Rachel Widra, 2021. "Boomerang Kids in the Pandemic: How High-Income Families Are Their Own Safety Net," Economic Commentary, Federal Reserve Bank of Cleveland, vol. 2021(21), pages 1-7, December.
    5. Biró, Péter & Gudmundsson, Jens, 2021. "Complexity of finding Pareto-efficient allocations of highest welfare," European Journal of Operational Research, Elsevier, vol. 291(2), pages 614-628.
    6. Pianezzi, Daniela & Ashraf, Muhammad Junaid, 2022. "Accounting for ignorance: An investigation into corruption, immigration and the state," CRITICAL PERSPECTIVES ON ACCOUNTING, Elsevier, vol. 86(C).
    7. Juliana Mohd Abdul Kadir & Navaz Naghavi & Geetha Subramaniam & Nur A’amilyn Abdul Halim, 2020. "Unemployment among Graduates - Is there a Mismatch?," International Journal of Asian Social Science, Asian Economic and Social Society, vol. 10(10), pages 583-592, October.

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    More about this item

    Keywords

    matching model; skills; turbulence; unemployment; layoffs; quits; layoff costs.;
    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
    • 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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