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Statistical Methods for Distributional Analysis

Author

Listed:
  • Frank A. Cowell

    (STICERD - LSE - London School of Economics and Political Science)

  • Emmanuel Flachaire

    (GREQAM - Groupement de Recherche en Économie Quantitative d'Aix-Marseille - EHESS - École des hautes études en sciences sociales - AMU - Aix Marseille Université - ECM - École Centrale de Marseille - CNRS - Centre National de la Recherche Scientifique)

Abstract

This Chapter is about the techniques, formal and informal, that are commonly used to give quantitative answers in the field of distributional analysis - covering subjects including inequality, poverty and the modelling of income distributions. It deals with parametric and non-parametric approaches and the way in which imperfections in data may be handled in practice.

Suggested Citation

  • Frank A. Cowell & Emmanuel Flachaire, 2014. "Statistical Methods for Distributional Analysis," Working Papers halshs-01115996, HAL.
    • Handle: RePEc:hal:wpaper:halshs-01115996
    Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-01115996
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    References listed on IDEAS

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    More about this item

    Keywords

    parametric modelling; non-parametric methods; goodness of fit; dominance criteria; poverty measure; hypothesis testing; welfare indices; inequality measure; bootstrap; influence function; confidence intervals;
    All these keywords.

    JEL classification:

    • D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution
    • D63 - Microeconomics - - Welfare Economics - - - Equity, Justice, Inequality, and Other Normative Criteria and Measurement
    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General

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