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Fast methods for jackknifing inequality indices

  • Karoly, Lynn
  • Schröder, Carsten

The jackknife is a resampling method that uses subsets of the original database by leaving out one observation at a time from the sample. The paper outlines a procedure to obtain jackknife estimates for several inequality indices with only a few passes through the data. The number of passes is independent of the number of observations. Hence, the method provides an efficient way to obtain standard errors of the estimators even if sample size is large. We apply our method using micro data on individual incomes for Germany and the US.

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Paper provided by Christian-Albrechts-University of Kiel, Department of Economics in its series Economics Working Papers with number 2013-04.

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Date of creation: 2013
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Handle: RePEc:zbw:cauewp:201304
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  1. Russell Davidson, 2007. "Reliable Inference For The Gini Index," Working Papers halshs-00353856, HAL.
  2. Reza Modarres & Joseph L. Gastwirth, 2006. "A Cautionary Note on Estimating the Standard Error of the Gini Index of Inequality," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 68(3), pages 385-390, 06.
  3. Timm Bönke & Carsten Schröder, 2010. "Country Inequality Rankings and Conversion Schemes," Discussion Papers of DIW Berlin 1068, DIW Berlin, German Institute for Economic Research.
  4. David E. A. Giles, 2002. "Calculating a Standard Error for the Gini Coefficient: Some Further Results," Econometrics Working Papers 0202, Department of Economics, University of Victoria.
  5. Yitzhaki, Shlomo, 1991. "Calculating Jackknife Variance Estimators for Parameters of the Gini Method," Journal of Business & Economic Statistics, American Statistical Association, vol. 9(2), pages 235-39, April.
  6. Biewen, Martin, 2002. "Bootstrap inference for inequality, mobility and poverty measurement," Journal of Econometrics, Elsevier, vol. 108(2), pages 317-342, June.
  7. Jonathan Morduch & Terry Sicular, 2002. "Rethinking Inequality Decomposition, With Evidence from Rural China," Economic Journal, Royal Economic Society, vol. 112(476), pages 93-106, January.
  8. Lynn A. Karoly & Carsten Schröder, 2014. "Fast Methods for Jackknifing Inequality Indices," SOEPpapers on Multidisciplinary Panel Data Research 643, DIW Berlin, The German Socio-Economic Panel (SOEP).
  9. Heshmati, Almas, 2004. "A Review of Decomposition of Income Inequality," IZA Discussion Papers 1221, Institute for the Study of Labor (IZA).
  10. Karoly, Lynn A, 1992. "Changes in the Distribution of Individual Earnings in the United States: 1967-1986," The Review of Economics and Statistics, MIT Press, vol. 74(1), pages 107-15, February.
  11. Bhattacharya, Debopam, 2007. "Inference on inequality from household survey data," Journal of Econometrics, Elsevier, vol. 137(2), pages 674-707, April.
  12. Fields, Gary S & Yoo, Gyeongjoon, 2000. "Falling Labor Income Inequality in Korea's Economic Growth: Patterns and Underlying Causes," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 46(2), pages 139-59, June.
  13. Cowell, Frank A., 1989. "Sampling variance and decomposable inequality measures," Journal of Econometrics, Elsevier, vol. 42(1), pages 27-41, September.
  14. Ogwang, Tomson, 2000. " A Convenient Method of Computing the Gini Index and Its Standard Error," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 62(1), pages 123-29, February.
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