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Heterogeneous Convergence

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  • Matthew J. Higgins
  • Daniel Levy
  • Andrew T. Young

Abstract

We use U.S. county-level data containing 3,058 cross-sectional observations and 41 conditioning variables to study economic growth and explore possible heterogeneity in growth determination across 32 individual states. Using a 3SLS-IV estimation method, we find that the convergence rates for 32 individual states are above 2 percent, with an average of 8.1 percent. For 7 states the convergence rate can be rejected as identical to at least one other state's convergence rate with 95 percent confidence. Convergence rates are negatively correlated with initial income. The size of government at all levels of decentralization is either unproductive or negatively correlated with growth. Educational attainment has a non-linear relationship with growth. The size of the finance, insurance and real estate, and entertainment industries are positively correlated with growth, while the size of the education industry is negatively correlated with growth. Heterogeneity in the effects of balanced growth path determinants across individual states is harder to detect than in convergence rates.

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Paper provided by Department of Economics, Emory University (Atlanta) in its series Emory Economics with number 0615.

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Date of creation: Nov 2006
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Handle: RePEc:emo:wp2003:0615

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Cited by:
  1. 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).
  2. Andrew Young & Matthew Higgins & Daniel Levy, 2005. "Sigma-Convergence Versus Beta-Convergence: Evidence from U.S. County-Level Data," Macroeconomics 0505008, EconWPA.
  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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