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Statistical Inference for Welfare under Complete and Incomplete Information

Author

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  • Frank A Cowell
  • Maria-Pia Victoria-Feser

Abstract

We show how a collection of results in the literature on the empirical estimation of welfare indicators from sample data can be unified. We also demonstrate how some of these ideas can be extended to empirically important cases where the data have been trimmed or censored.

Suggested Citation

  • Frank A Cowell & Maria-Pia Victoria-Feser, 1999. "Statistical Inference for Welfare under Complete and Incomplete Information," STICERD - Distributional Analysis Research Programme Papers 47, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    • Handle: RePEc:cep:stidar:47
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    File URL: https://sticerd.lse.ac.uk/dps/darp/DARP47.pdf
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    Cited by:

    1. Frank A Cowell & Maria-Pia Victoria-Feser, 2001. "Distributional Dominance with Dirty Data," STICERD - Distributional Analysis Research Programme Papers 51, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    2. Frank A Cowell & Maria-Pia Victoria-Feser, 2001. "Robust Lorenz Curves: A Semiparametric Approach," STICERD - Distributional Analysis Research Programme Papers 50, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    3. Susan Harkness, 2004. "Social and Political Indicators of Human Well-being," WIDER Working Paper Series RP2004-33, World Institute for Development Economic Research (UNU-WIDER).

    More about this item

    Keywords

    Inequality measurement; Income distribution; Lorenz curve; influence function; sampling variance; censoring; trimming;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • D63 - Microeconomics - - Welfare Economics - - - Equity, Justice, Inequality, and Other Normative Criteria and Measurement

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