The Journal of Economic Inequality

, Volume 17, Issue 2, pp 125–143 | Cite as

An integrated approach for a top-corrected income distribution

  • Charlotte BartelsEmail author
  • Maria Metzing


Household survey data provide a rich information set on income, household context and demographic variables, but tend to underreport 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 income distributions 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.


Gini coefficient Top income shares Survey data Tax record data Pareto distribution 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.



This paper has greatly benefited from the suggestions of the editor, two anonymous referees and Carsten Schröder. We thank Martin Biewen for valuable comments and participants of the 2016 conferences of the Society for Social Choice and Welfare (SSCW), the European Economic Association (EEA), the International Institute of Public Finance (IIPF) and the German Economic Association (Verein für Socialpolitik) as well as the 2017 meeting of the Society for the Study of Economic Inequality (ECINEQ) and Journées Louis-André Gérard-Varet (LAGV) for insightful discussions.

Supplementary material

10888_2018_9394_MOESM1_ESM.pdf (2.4 mb)
(PDF 2.39 MB)


  1. Aaberge, R., Atkinson, A.B.: Top incomes in Norway. In: Atkinson, A.B., Piketty, T. (eds.) Top Incomes: a Global Perspective, pp. 448–482. Oxford University Press (2010)Google Scholar
  2. Alvaredo, F.: A note on the relationship between top income shares and the Gini coefficient. Econ. Lett. 110, 274–277 (2011)CrossRefGoogle Scholar
  3. Armour, P., Burkhauser, R.V., Larrimore, J.: Deconstructing income and income inequality measures: a crosswalk from market income to comprehensive income. Am. Econ. Rev. Pap. Proc. 103(3), 173–177 (2013)CrossRefGoogle Scholar
  4. Atkinson, A.B.: Measuring top incomes: methodological issues. In: Atkinson, A.B., Piketty, T. (eds.) Incomes over the Twentieth Century: a Contrast Between Continental European and English-Speaking Countries, Chapter 2, pp. 18–42. Oxford University Press, Oxford (2007)Google Scholar
  5. Atkinson, A.B., Piketty, T., Saez, E.: Top incomes in the long run of history. J. Econ. Lit. 49(1), 3–71 (2011)CrossRefGoogle Scholar
  6. Bach, S., Beznoska, M., Steiner, V.: Who bears the tax burden in Germany? DIW Economic Bulletin No 51 and 52 (2016)Google Scholar
  7. Bach, S., Corneo, G., Steiner, V.: From bottom to top: the entire income distribution in Germany, 1992–2003. Rev. Income Wealth 2, 303–330 (2009)CrossRefGoogle Scholar
  8. Bartels, C., Jenderny, K.: The role of capital income for top income shares in Germany. World Top Incomes Database Working Paper Nr.1/2015 (2015)Google Scholar
  9. Benabou, R.: Tax and education policy in a heterogeneous-agent economy: what levels of redistribution maximize growth and efficiency? Econometrica 70(2), 481–517 (2002)CrossRefGoogle Scholar
  10. Biewen, M., Juhasz, A.: Understanding rising inequality in Germany, 1999/2000 - 2005/06. Rev. Income Wealth 58(4), 622–647 (2012)CrossRefGoogle Scholar
  11. Blundell, R., Pistaferri, L., Saporta-Eksten, I.: Consumption inequality and family labor supply. Am. Econ. Rev. 106(2), 387–435 (2016)CrossRefGoogle Scholar
  12. Bricker, J., Henriques, A., Krimmel, J., Sabelhaus, J.: Measuring income and wealth at the top using administrative and survey data. Brookings Papers on Economic Activity Spring 2016, 261–331 (2016)CrossRefGoogle Scholar
  13. Burkhauser, R., Feng, S., Jenkins, S.P., Larrimore, J.: Recent trends in top income shares in the united states: reconciling estimates from march CPS and IRS tax return data. Rev. Econ. Stat. 94(2), 371–388 (2012)CrossRefGoogle Scholar
  14. Burkhauser, R., Hérault, N., Jenkins, S.P., Wilkins, R.: What has been happening to UK income inequality since the mid-1990s? Answers from reconciled and combined household survey and tax return data. IZA Discussion Paper No. 9718 (2016)Google Scholar
  15. Clementi, F., Gallegati, M.: Pareto’s law of income distribrution: evidence for Germany, the United Kingdom, and the United States. In: Chakrabarti, S.Y.A., Chatterjee, B. (eds.) Econophysics of Wealth Distribution, pp. 3–14. Springer (2005a)Google Scholar
  16. Clementi, F., Gallegati, M.: Power law tails in the italian personal income distribution. Physica A: Statistical Mechanics and its Applications 350(2), 427–438 (2005b)CrossRefGoogle Scholar
  17. Dagum, C.: A new approach to the decomposition of the Gini income inequality ratio. Empir. Econ. 22, 515–531 (1997)CrossRefGoogle Scholar
  18. Feldstein, M.: The effects of taxation on risk taking. J. Polit. Econ. 77(5), 755–764 (1969)CrossRefGoogle Scholar
  19. Frick, J., Grabka, M., Krell, K.: Measuring the consistency of cross-sectional and longitudinal income information in EU-SILC. Rev. Income Wealth 63, 30–52 (2017)CrossRefGoogle Scholar
  20. Gerstorf, S., Schupp, J. (eds.): SOEP Wave Report 2015 DIW Berlin, (2016)Google Scholar
  21. Heathcote, J., Storesletten, K., Violante, G.L.: Optimal tax progressivity: an analytical framework. Q. J. Econ. 132(4), 1693–1754 (2017)CrossRefGoogle Scholar
  22. Jäntti, M., Törmälehto, V.-M., Marlier, E.: The Use of Registers in the Context of EU-SILC: Challenges and Opportunities. Publications Office of European Union, Luxembourg (2013)Google Scholar
  23. Jäntti, M., Törmälehto, V.-M., Marlier, E.: The Use of Registers in the Context of EU-SILC. In: Atkinson, A.B., Guio, A.-C., Marlier, E. (eds.) Monitoring Social Inclusion in Europe, pp. 499–508. Publications Office of European Union Luxembourg (2017)Google Scholar
  24. Jenkins, S.P.: Pareto models, top incomes, and recent trends in UK income inequality. Economica 84, 261–289 (2017)CrossRefGoogle Scholar
  25. Lakner, C., Milanovic, B.: Global income distribution: from the fall of the Berlin wall to the great recession. World Bank Econ. Rev. 30(2), 203–232 (2016)CrossRefGoogle Scholar
  26. Piketty, T.: Income inequality in France, 1901–1998. J. Polit. Econ. 111, 1004–1042 (2003)CrossRefGoogle Scholar
  27. Piketty, T., Saez, E.: Income inequality in the United States, 1913–1998. Q. J. Econ. 118(1), 1–41 (2003)CrossRefGoogle Scholar
  28. Roine, J., Vlachos, J., Waldenström, D.: The long-run determinants of inequality: what can we learn from top income data? J. Public Econ. 93(7-8), 974–988 (2009)CrossRefGoogle Scholar
  29. Törmälehto, V.-M.: High Incomes and Affluence: Evidence from the European Union Statistics on Income and Living Conditions. Publications Office of the European Union, Luxembourg (2017)Google Scholar
  30. Wagner, G.G., Frick, J.R., Schupp, J.: The German Socio-Economic Panel study (SOEP): scope, evolution and enhancements. Schmollers Jahr. 127(1), 139–169 (2007)Google Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.DIWBerlinGermany
  2. 2.IZABonnGermany
  3. 3.UCFSUppsalaSweden

Personalised recommendations