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Asymptotic and bootstrap inference for top income shares

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  • Michał Brzeziński

    ()
    (Faculty of Economic Sciences, University of Warsaw)

Abstract

We analyse statistical inference for top income shares in finite samples. The asymptotic inference performs poorly even in large samples. The standard bootstrap tests give some improvement, but can be unreliable. Semi-parametric bootstrap approach is accurate in moderate and larger samples.

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File URL: http://www.wne.uw.edu.pl/inf/wyd/WP/WNE_WP86.pdf
File Function: First version, 2013
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Bibliographic Info

Paper provided by Faculty of Economic Sciences, University of Warsaw in its series Working Papers with number 2013-01.

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Length: 12 pages
Date of creation: 2013
Date of revision:
Handle: RePEc:war:wpaper:2013-01

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Keywords: top income shares; income distribution; inference; bootstrap; semi-parametric bootstrap;

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  1. Atkinson, A. B. & Piketty, Thomas (ed.), 2007. "Top Incomes Over the Twentieth Century: A Contrast Between Continental European and English-Speaking Countries," OUP Catalogue, Oxford University Press, number 9780199286881.
  2. Beach, Charles M & Davidson, Russell, 1983. "Distribution-Free Statistical Inference with Lorenz Curves and Income Shares," Review of Economic Studies, Wiley Blackwell, vol. 50(4), pages 723-35, October.
  3. Richard V. Burkhauser & Shuaizhang Feng & Stephen P. Jenkins & Jeff Larrimore, 2009. "Recent Trends in Top Income Shares in the USA: Reconciling Estimates from March CPS and IRS Tax Return Data," NBER Working Papers 15320, National Bureau of Economic Research, Inc.
  4. Cowell, Frank A. & Flachaire, Emmanuel, 2007. "Income distribution and inequality measurement: The problem of extreme values," Journal of Econometrics, Elsevier, vol. 141(2), pages 1044-1072, December.
  5. McDonald, James B, 1984. "Some Generalized Functions for the Size Distribution of Income," Econometrica, Econometric Society, vol. 52(3), pages 647-63, May.
  6. Russell Davidson & Emmanuel Flachaire, 2004. "Asymptotic and bootstrap inference for inequality and poverty measures," Cahiers de la Maison des Sciences Economiques v04100, Université Panthéon-Sorbonne (Paris 1).
  7. Leigh, Andrew & van der Eng, Pierre, 2009. "Inequality in Indonesia: What can we learn from top incomes?," Journal of Public Economics, Elsevier, vol. 93(1-2), pages 209-212, February.
  8. Samuel Dastrup & Rachel Hartshorn & James McDonald, 2007. "The impact of taxes and transfer payments on the distribution of income: A parametric comparison," Journal of Economic Inequality, Springer, vol. 5(3), pages 353-369, December.
  9. Butler, Richard J. & McDonald, James B., 1989. "Using incomplete moments to measure inequality," Journal of Econometrics, Elsevier, vol. 42(1), pages 109-119, September.
  10. Thomas Piketty & Nancy Qian, 2009. "Income Inequality and Progressive Income Taxation in China and India, 1986-2015," American Economic Journal: Applied Economics, American Economic Association, vol. 1(2), pages 53-63, April.
  11. Russell Davidson, 2012. "Statistical inference in the presence of heavy tails," Econometrics Journal, Royal Economic Society, vol. 15(1), pages C31-C53, 02.
  12. Anthony B. Atkinson & Thomas Piketty & Emmanuel Saez, 2011. "Top Incomes in the Long Run of History," Journal of Economic Literature, American Economic Association, vol. 49(1), pages 3-71, March.
  13. Christian Schluter, 2012. "On the problem of inference for inequality measures for heavy‐tailed distributions," Econometrics Journal, Royal Economic Society, vol. 15(1), pages 125-153, 02.
  14. Vijay Verma & Gianni Betti, 2011. "Taylor linearization sampling errors and design effects for poverty measures and other complex statistics," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(8), pages 1549-1576, August.
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