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Influence functions for distributional statistics

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  • B. Essama-Nssah

    (World Bank Group)

  • Peter J. Lambert

    ()
    (University of Oregon)

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    Abstract

    Social evaluation functions used in policy impact analysis can be viewed as real-valued functionals of the underlying outcome distributions. Influence functions may be used to identify the sources of variation in social outcomes in terms of individual or household characteristics. This paper sets forth in clear terms the definition of the influence function and recentered influence function, and catalogs these functions for a wide range of distributional statistics, including measures of central tendency, inequality and poverty and also measures of the degree of pro-poorness of a shock- or policy-induced change in income levels.

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    File URL: http://www.ecineq.org/milano/WP/ECINEQ2011-236.pdf
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    Bibliographic Info

    Paper provided by ECINEQ, Society for the Study of Economic Inequality in its series Working Papers with number 236.

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    Length: 25 pages
    Date of creation: 2011
    Date of revision:
    Handle: RePEc:inq:inqwps:ecineq2011-236

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    Related research

    Keywords: Influence function; robust statistic; distributional statistic; inequality; poverty; social evaluation.;

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    1. Ravallion, Martin & Shaohua Chen, 2001. "Measuring pro-poor growth," Policy Research Working Paper Series 2666, The World Bank.
    2. Jenkins, Stephen P & Lambert, Peter J, 1997. "Three 'I's of Poverty Curves, with an Analysis of UK Poverty Trends," Oxford Economic Papers, Oxford University Press, vol. 49(3), pages 317-27, July.
    3. Victor Chernozhukov & Ivan Fernandez-Val & Blaise Melly, 2008. "Inference On Counterfactual Distributions," Boston University - Department of Economics - Working Papers Series, Boston University - Department of Economics wp2008-005, Boston University - Department of Economics.
    4. B. Essama-Nssah & Peter J. Lambert, 2009. "Measuring Pro-Poorness: A Unifying Approach With New Results," Review of Income and Wealth, International Association for Research in Income and Wealth, International Association for Research in Income and Wealth, vol. 55(3), pages 752-778, 09.
    5. Shorrocks, Anthony F, 1983. "Ranking Income Distributions," Economica, London School of Economics and Political Science, London School of Economics and Political Science, vol. 50(197), pages 3-17, February.
    6. Rothe, Christoph, 2011. "Partial Distributional Policy Effects," IZA Discussion Papers 6076, Institute for the Study of Labor (IZA).
    7. SErgio Firpo & Nicole M. Fortin & Thomas Lemieux, 2006. "Unconditional Quantile Regressions," Textos para discussão, Department of Economics PUC-Rio (Brazil) 533, Department of Economics PUC-Rio (Brazil).
    8. Atkinson, Anthony B., 1970. "On the measurement of inequality," Journal of Economic Theory, Elsevier, Elsevier, vol. 2(3), pages 244-263, September.
    9. Foster, James & Greer, Joel & Thorbecke, Erik, 1984. "A Class of Decomposable Poverty Measures," Econometrica, Econometric Society, Econometric Society, vol. 52(3), pages 761-66, May.
    10. Datt, Gaurav & Ravallion, Martin, 1992. "Growth and redistribution components of changes in poverty measures : A decomposition with applications to Brazil and India in the 1980s," Journal of Development Economics, Elsevier, Elsevier, vol. 38(2), pages 275-295, April.
    11. Rothe, Christoph, 2010. "Nonparametric estimation of distributional policy effects," Journal of Econometrics, Elsevier, Elsevier, vol. 155(1), pages 56-70, March.
    12. Frank A. Cowell & Maria-Pia Victoria-Feser, 2002. "Welfare Rankings in the Presence of Contaminated Data," Econometrica, Econometric Society, Econometric Society, vol. 70(3), pages 1221-1233, May.
    13. Frédéric CHANTREUIL & Alain TRANNOY, 2011. "Inequality Decomposition Values," Annales d'Economie et de Statistique, ENSAE, issue 101-102, pages 13-36.
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