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Assessing inequality using percentile shares


  • Ben Jann


At least since Thomas Piketty's best-selling "Capital in the Twenty-First Century" (2014, Cambridge, MA: The Belknap Press), percentile shares have become a popular approach for analyzing distributional inequalities. In their work on the development of top incomes, Piketty and collaborators typically report top-percentage shares, using varying percentages as thresholds (top 10%, top 1%, top 0.1%, etc.). However, analysis of percentile shares at other positions in the distribution may also be of interest. In this paper I present a new Stata command called -pshare- that estimates percentile shares from individual-level data and displays the results using histograms or stacked bar charts. A shorter version of this paper has been published in The Stata Journal 16(2): 264-300 (see:

Suggested Citation

  • Ben Jann, 2015. "Assessing inequality using percentile shares," University of Bern Social Sciences Working Papers 13, University of Bern, Department of Social Sciences, revised 27 Oct 2016.
  • Handle: RePEc:bss:wpaper:13

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    References listed on IDEAS

    1. Stephen P. Jenkins, 1999. "Analysis of income distributions," Stata Technical Bulletin, StataCorp LP, vol. 8(48).
    2. Thomas Piketty, 2014. "Capital in the Twenty-First Century: a multidimensional approach to the history of capital and social classes," PSE-Ecole d'économie de Paris (Postprint) halshs-01157491, HAL.
    3. 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.
    4. Thomas Piketty & Emmanuel Saez, 2014. "Inequality in the long run," PSE - Labex "OSE-Ouvrir la Science Economique" halshs-01053609, HAL.
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    2. Anand, Ishan & Kumar, Rishabh, 2022. "The sky and the stratosphere: concentrated wealth in India during the ‘lost decade’," SocArXiv 726c8, Center for Open Science.
    3. James B. Davies & Nicole M. Fortin & Thomas Lemieux, 2017. "Wealth inequality: Theory, measurement and decomposition," Canadian Journal of Economics, Canadian Economics Association, vol. 50(5), pages 1224-1261, December.
    4. Anastasios Evgenidis & Apostolos Fasianos, 2021. "Unconventional Monetary Policy and Wealth Inequalities in Great Britain," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 83(1), pages 115-175, February.
    5. Mussa, Richard, 2017. "To Err is Human: Inconsistencies in Food Conversion Factors and Inequality in Malawi," MPRA Paper 75981, University Library of Munich, Germany.
    6. Bornmann, Lutz & Leydesdorff, Loet, 2017. "Skewness of citation impact data and covariates of citation distributions: A large-scale empirical analysis based on Web of Science data," Journal of Informetrics, Elsevier, vol. 11(1), pages 164-175.
    7. Gerson Pech & Catarina Delgado, 2020. "Percentile and stochastic-based approach to the comparison of the number of citations of articles indexed in different bibliographic databases," Scientometrics, Springer;Akadémiai Kiadó, vol. 123(1), pages 223-252, April.
    8. Oliver Hümbelin, 2016. "Ungleichheit und Umverteilung über das Steuersystem. Eine Analyse der Verteilungseffekte von direkten Steuern und steuerlichen Abzügen mit Steuerdaten des Kantons Aargau (2001-2011)," University of Bern Social Sciences Working Papers 23, University of Bern, Department of Social Sciences.

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    More about this item


    Stata; pshare; percentile shares; Lorenz curve; concentration curve; inequality; income distribution; wealth distribution; graphics;
    All these keywords.

    JEL classification:

    • C87 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Econometric Software
    • D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution
    • D63 - Microeconomics - - Welfare Economics - - - Equity, Justice, Inequality, and Other Normative Criteria and Measurement

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