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A Meta-Analytic Assessment of the Effects of Inequality on Growth

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  • Pedro Neves

    (CEF.UP and FEP, Universidade do Porto)

  • Sandra Silva

    (CEF.UP and FEP, Universidade do Porto)

  • Óscar Afonso

    (CEF.UP, OBEGEF, NIFIP, and FEP, Universidade do Porto)

Abstract

Over the last two decades there has been a growing interest in determining the impact of inequality on growth. The empirical literature has, however, produced controversial results regarding both the signal and the magnitude of such impact. This paper develops a meta-analysis on this literature on an attempt to systematize and explain the diversity in studies' results. We find that most of the heterogeneity is due to differences in studies' methodological characteristics, such as the structure of the data, the sample coverage, the type of distribution, the definition of income, and the estimation technique. These results suggest that there is not one but several underlying effects of inequality on growth, which are likely to differ in their nature and operate in opposing directions. We also find traces of publication bias, as, on the one hand, authors and journals are more willing to report and publish statistically significant results, and, on the other hand, studies' results tend to follow a predictable cycle of fashion and novelty over time.

Suggested Citation

  • Pedro Neves & Sandra Silva & Óscar Afonso, 2012. "A Meta-Analytic Assessment of the Effects of Inequality on Growth," CEF.UP Working Papers 1204, Universidade do Porto, Faculdade de Economia do Porto.
  • Handle: RePEc:por:cetedp:1204
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    Keywords

    meta-analysis; inequality; economic growth; publication bias.;
    All these keywords.

    JEL classification:

    • O4 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity
    • D3 - Microeconomics - - Distribution
    • H2 - Public Economics - - Taxation, Subsidies, and Revenue
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models

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