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The Evolution of Regional Beveridge Curves

Author

Listed:
  • Michael T. Owyang
  • Hannah Shell
  • Daniel Soques

Abstract

The slow recovery of the labor market in the aftermath of the Great Recession highlighted mismatch, the misallocation of workers across space or across industries. We consider the historical evolution of regional mismatch. We construct MSA-level unemployment rates and vacancy data using techniques similar to Barnichon (2010) and a new dataset of online help-wanted ads by MSA. We estimate regional Beveridge curves, identifying the slopes by restricting them to be equal across locations with similar labor market characteristics. We find that the 51 U.S. cities in our sample have four groupings which are influenced by industry classification, union membership, and geographic proximity. Additionally, allowing for a structural break suggests match efficiency increased across regions after adoption of the internet.

Suggested Citation

  • Michael T. Owyang & Hannah Shell & Daniel Soques, 2022. "The Evolution of Regional Beveridge Curves," Working Papers 2022-037, Federal Reserve Bank of St. Louis.
    • Handle: RePEc:fip:fedlwp:95203
    DOI: 10.20955/wp.2022.037
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    References listed on IDEAS

    as
    1. Kaufmann, Sylvia, 2015. "K-state switching models with time-varying transition distributions—Does loan growth signal stronger effects of variables on inflation?," Journal of Econometrics, Elsevier, vol. 187(1), pages 82-94.
    2. Neville Francis & Michael T. Owyang & Ozge Savascin, 2017. "An endogenously clustered factor approach to international business cycles," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(7), pages 1261-1276, November.
    3. Howard J. Wall & Gylfi Zoega, 2002. "The British Beveridge curve: A tale of ten regions," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 64(3), pages 257-276, July.
    4. Oliver Jean Blanchard & Peter Diamond, 1989. "The Beveridge Curve," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 20(1), pages 1-76.
    5. Patricia M. Anderson & Simon M. Burgess, 2000. "Empirical Matching Functions: Estimation and Interpretation Using State-Level Data," The Review of Economics and Statistics, MIT Press, vol. 82(1), pages 93-102, February.
    6. Tomohiro Ando, 2007. "Bayesian predictive information criterion for the evaluation of hierarchical Bayesian and empirical Bayes models," Biometrika, Biometrika Trust, vol. 94(2), pages 443-458.
    7. repec:bla:obuest:v:64:y:2002:i:3:p:261-80 is not listed on IDEAS
    8. Paul Gregg & Barbara Petrongolo, 1997. "Random or Non-Random matching? Implications for the use of the UV 234 curve as a measure of matching effectiveness," CEP Discussion Papers dp0348, Centre for Economic Performance, LSE.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    mismatch; vacancies; clustering;
    All these keywords.

    JEL classification:

    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • J63 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Turnover; Vacancies; Layoffs

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