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The T-Statistic Approach to Inference for Inequality Indices: The Issue of Grouping Variability

Author

Listed:
  • Herault, Nicolas

    (University of Bordeaux)

  • Jenkins, Stephen P.

    (London School of Economics)

Abstract

Ibragimov, Kattuman, and Skrobotov (Econometric Reviews, 2025) propose a ‘t-statistic’ approach to inference for inequality indices building on results provided by Ibragimov and Müller (Journal of Business & Economic Statistics, 2010), and they and Midões and de Crombrugghe (Journal of Economic Inequality, 2023) evaluate its performance. We highlight a feature of the t-statistic approach – ‘grouping variability’ – that has been understudied to date, showing how this complicates inference for inequality indices.

Suggested Citation

  • Herault, Nicolas & Jenkins, Stephen P., 2025. "The T-Statistic Approach to Inference for Inequality Indices: The Issue of Grouping Variability," IZA Discussion Papers 17972, Institute of Labor Economics (IZA).
    • Handle: RePEc:iza:izadps:dp17972
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    More about this item

    Keywords

    asymptotic inference; t-statistic inference approach; inequality; grouping variability;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C46 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Specific Distributions
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution

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