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A Reconsideration of Kuznets Curve across Countries: Evidence from the Co-summability Approach

Author

Listed:
  • Shinhye Chang

    () (Department of Economics, University of Pretoria, Pretoria, 0002, South Africa)

  • Matthew W. Clance

    () (Department of Economics, University of Pretoria, Pretoria, 0002, South Africa)

  • Giray Gozgor

    () (Faculty of Political Sciences, Istanbul Medeniyet University, Istanbul, 34720, Turkey)

  • Rangan Gupta

    () (Department of Economics, University of Pretoria, Pretoria, 0002, South Africa)

Abstract

This study re-examines the existence of an inverted U-shaped relationship between economic growth and income inequality using advanced time series techniques, which enable analyzing nonlinear long-run relationships among stochastic processes. Applying the concept of summability, balancedness, and co-summability on a sample of 55 countries from 1980 to 2010, we find no evidence in support of the nonlinear long-run relationship economic growth and income inequality.

Suggested Citation

  • Shinhye Chang & Matthew W. Clance & Giray Gozgor & Rangan Gupta, 2019. "A Reconsideration of Kuznets Curve across Countries: Evidence from the Co-summability Approach," Working Papers 201970, University of Pretoria, Department of Economics.
  • Handle: RePEc:pre:wpaper:201970
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    References listed on IDEAS

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    More about this item

    Keywords

    income distribution; economic development; summability; balancedness; co-summability; cross-country studies;

    JEL classification:

    • O47 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Empirical Studies of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence
    • O15 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Economic Development: Human Resources; Human Development; Income Distribution; Migration
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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