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Heterogeneous Convergence

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  • Andrew T. Young

    ()
    (College of Business and Economics, West Virginia University, USA)

  • Matthew J. Higgins

    (Scheller College of Business, Georgia Institute of Technology and National Bureau of Economic Research, USA)

  • Daniel Levy

    (Department of Economics, Bar-Ilan University, Israel; Department of Economics, Emory University, USA; Rimini Centre for Economic Analysis, Italy)

Abstract

We use U.S. county-level data to estimate convergence rates for 22 individual states. We find significant heterogeneity. E.g., the California estimate is 19.9 percent and the New York estimate is 3.3 percent. Convergence rates are essentially uncorrelated with income levels.

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Bibliographic Info

Paper provided by The Rimini Centre for Economic Analysis in its series Working Paper Series with number 19_13.

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Date of creation: Apr 2013
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Publication status: Forthcoming in Economics Letters
Handle: RePEc:rim:rimwps:19_13

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Keywords: Economic Growth; Conditional Convergence; Heterogeneity; U.S. County Level Data;

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Cited by:
  1. Andrew T. Young & Matthew J. Higgins & Daniel Levy, 2008. "Sigma Convergence versus Beta Convergence: Evidence from U.S. County-Level Data," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 40(5), pages 1083-1093, 08.
  2. Higgins, Matthew & Young, Andrew & Levy, Daniel, 2007. "Robust Correlates of County-Level Growth in the U.S," MPRA Paper 3088, University Library of Munich, Germany.
  3. Jamie Bologna & Donald J. Lacombe & Andrew T. Young, 2014. "A Spatial Analysis of Incomes and Institutional Quality : Evidence from US Metropolitan Areas," Working Papers 14-11, Department of Economics, West Virginia University.
  4. Matthew J. Higgins & Daniel Levy & Andrew T. Young, 2007. "Black Populations and Economic Growth: An Extreme Bounds Analysis of Mississippi County-level Data," Emory Economics 0701, Department of Economics, Emory University (Atlanta).

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