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The Estimation of Poverty and Inequality through Parametric Estimation of Lorenz Curves: An Evaluation

Author

Listed:
  • Camelia Minoiu

    (International Monetary Fund)

  • Sanjay G. Reddy

    (The New School for Social Research)

Abstract

Poverty and inequality are often estimated from grouped data as complete household surveys are neither always available to researchers nor easy to analyze. In this study we assess the performance of functional forms proposed by Kakwani (1980a) and Villasenor and Arnold(1989) to estimate the Lorenz curve from grouped data. The methods are implemented using the computational tools POVCAL and Sim-SIP, developed and distributed by the World Bank. To identify biases associated with these methods, we use unit data from several household surveys and theoretical distributions. We find that poverty and inequality are better estimated when the true distribution is unimodal than multimodal. For unimodal distributions, biases associated with poverty measures are rarely larger than one percentage point. For data from multi-peaked or heavily skewed distributions, the biases are likely to be higher and of unknown sign.

Suggested Citation

  • Camelia Minoiu & Sanjay G. Reddy, 2009. "The Estimation of Poverty and Inequality through Parametric Estimation of Lorenz Curves: An Evaluation," Journal of Income Distribution, Ad libros publications inc., vol. 18(2), pages 160-178, June.
    • Handle: RePEc:jid:journl:y:2009:v:18:i:2:p:160-178
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    Citations

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    Cited by:

    1. Rahul Lahoti & Arjun Jayadev & Sanjay G. Reddy, 2014. "The Global Consumption and Income Project (GCIP): An Introduction and Preliminary Findings," LIS Working papers 621, LIS Cross-National Data Center in Luxembourg.
    2. Sanjay Reddy & Rahul Lahoti & Arjun Jayadev, 2015. "The global consumption and income project: An introduction and preliminary findings," WIDER Working Paper Series 003, World Institute for Development Economic Research (UNU-WIDER).
    3. Lahoti Rahul & Jayadev Arjun & Reddy Sanjay, 2016. "The Global Consumption and Income Project (GCIP): An Overview," Journal of Globalization and Development, De Gruyter, vol. 7(1), pages 61-108, June.
    4. Calzadilla, Alvaro, 2010. "Global income distribution and poverty: Implications from the IPCC SRES scenarios," Kiel Working Papers 1664, Kiel Institute for the World Economy (IfW Kiel).
    5. Teresa Ghilarducci & Joelle Saad-Lessler, 2014. "How 401(k) Plans Make Recessions Worse," SCEPA working paper series. 2014-9, Schwartz Center for Economic Policy Analysis (SCEPA), The New School.
    6. Rahul Lahoti & Arjun Jayadev & Sanjay G. Reddy, 2015. "The global consumption and income project: An introduction and preliminary findings," WIDER Working Paper Series wp-2015-003, World Institute for Development Economic Research (UNU-WIDER).

    More about this item

    Keywords

    grouped data; Lorenz curve; poverty; inequality; income distribution; POVCAL; SimSIP;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C16 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Econometric and Statistical Methods; Specific Distributions
    • D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution
    • D63 - Microeconomics - - Welfare Economics - - - Equity, Justice, Inequality, and Other Normative Criteria and Measurement
    • I32 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Measurement and Analysis of Poverty

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