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Heterogeneous Convergence

  • Andrew T. Young

    ()

    (College of Business and Economics, West Virginia University)

  • Matthew J. Higgins

    (College of Management, Georgia Institute of Technology)

  • Daniel Levy

    (Department of Economics, Bar-Ilan University; Department of Economics, Emory University; RCEA)

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 all statistically significant 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 The Rimini Centre for Economic Analysis in its series Working Paper Series with number 18_11.

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Date of creation: Mar 2011
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Handle: RePEc:rim:rimwps:18_11
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