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An Integrated Approach for Top-Corrected Ginis

Listed author(s):
  • Bartels, Charlotte

    ()

    (DIW Berlin)

  • Metzing, Maria

    (DIW Berlin)

Household survey data provide a rich information set on income, household context and demographic variables, but tend to under report incomes at the very top of the distribution. Administrative data like tax records offer more precise information on top incomes, but at the expense of household context details and incomes of non-filers at the bottom of the distribution. We combine the benefits of the two data sources and develop an integrated approach for top-corrected Gini coefficients where we impute top incomes in survey data using information on top income distribution from tax data. We apply our approach to European EU-SILC survey data which in some countries include administrative data. We find higher inequality in those European countries that exclusively rely (Germany, UK) or have relied (Spain) on interviews for the provision of EU-SILC survey data as compared to countries that use administrative data.

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Paper provided by Institute for the Study of Labor (IZA) in its series IZA Discussion Papers with number 10573.

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Length: 38 pages
Date of creation: Feb 2017
Handle: RePEc:iza:izadps:dp10573
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  1. 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.
  2. Roine, Jesper & Waldenström, Daniel, 2014. "Long run trends in the distribution of income and wealth," Working Paper Series, Center for Fiscal Studies 2014:5, Uppsala University, Department of Economics.
  3. Thomas Piketty & Emmanuel Saez, 2003. "Income Inequality in the United States, 1913–1998," The Quarterly Journal of Economics, Oxford University Press, vol. 118(1), pages 1-41.
  4. Richard V. Burkhauser & Nicolas Hérault & Stephen P. Jenkins & Roger Wilkins, 2016. "What has Been Happening to UK Income Inequality Since the Mid-1990s? Answers from Reconciled and Combined Household Survey and Tax Return Data," NBER Working Papers 21991, National Bureau of Economic Research, Inc.
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  6. Roine, Jesper & Vlachos, Jonas & Waldenström, Daniel, 2009. "The long-run determinants of inequality: What can we learn from top income data?," Journal of Public Economics, Elsevier, vol. 93(7-8), pages 974-988, August.
  7. Feldstein, Martin S, 1969. "The Effects on Taxation on Risk Taking," Journal of Political Economy, University of Chicago Press, vol. 77(5), pages 755-764, Sept./Oct.
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  10. Bricker, Jesse & Henriques, Alice M. & Krimmel, Jacob & Sabelhaus, John, 2015. "Measuring Income and Wealth at the Top Using Administrative and Survey Data," Finance and Economics Discussion Series 2015-30, Board of Governors of the Federal Reserve System (U.S.).
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  14. Bartels, Charlotte & Jenderny, Katharina, 2014. "The role of capital income for top incomes shares in Germany," Discussion Papers 2014/32, Free University Berlin, School of Business & Economics.
  15. Richard V. Burkhauser & Shuaizhang Feng & Stephen P. Jenkins & Jeff Larrimore, 2012. "Recent Trends in Top Income Shares in the United States: Reconciling Estimates from March CPS and IRS Tax Return Data," The Review of Economics and Statistics, MIT Press, vol. 94(2), pages 371-388, May.
  16. Alvaredo, Facundo, 2011. "A note on the relationship between top income shares and the Gini coefficient," Economics Letters, Elsevier, vol. 110(3), pages 274-277, March.
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  18. Thomas Piketty, 2003. "Income Inequality in France, 1901-1998," Journal of Political Economy, University of Chicago Press, vol. 111(5), pages 1004-1042, October.
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