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Heterogeneous Convergence

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  • Andrew Young
  • Matthew Higgins
  • Daniel Levy

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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Paper provided by Department of Economics, Emory University (Atlanta) in its series Emory Economics with number 1302.

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Date of creation: Apr 2013
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Handle: RePEc:emo:wp2003:1302

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Cited by:
  1. Andrew T. Young & Matthew J. Higgins & Daniel Levy, 2003. "Sigma Convergence Versus Beta Convergence: Evidence from U.S. County-Level Data," Working Papers 2003-06, Department of Economics, Bar-Ilan University.
  2. 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).
  3. Matthew J. Higgins & Daniel Levy & Andrew T. Young, 2007. "Robust Correlates of County-level Growth in the U.S," Emory Economics 0708, Department of Economics, Emory University (Atlanta).
  4. 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.

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