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Some are more equal than others: new estimates of global and regional inequality

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  • Zsolt Darvas

    (Institute of Economics, Centre for Economic and Regional Studies, Hungarian Academy of Sciences and Corvinus University Budapest and Bruegel)

Abstract

* We compare four methodologies to estimate the global distribution of income and find that many methods work well, but the method based on two-parameter distributions is more accurate than other methods. This method is simpler, easier to implement and relies on a more internationally-comparable dataset of national income distributions than other approaches used in the literature to calculate the global distribution of income. We suggest a simulation-based technique to estimate the standard error of the global Gini coefficient. * Global income inequality among the citizens of 128 countries gradually declined in 1989-2013, largely due to convergence of income per capita, which was offset by a small degree the increase in within-country inequalities. The standard error of the global Gini coefficient is very small. * After 1994, market income inequality in the EU28 was at a level similar to market inequality in other parts of the world, but net inequality (after taxes and transfers) is at a much lower level and it declined between 1994 and 2008, since when it remained relatively stable. * Regional income inequality is much higher in Asia, Africa, the Commonwealth of Independent states and Latin America than in the EU28. In Asia, regional inequality has increased recent years, while it declined in the other three non-European regions.

Suggested Citation

  • Zsolt Darvas, 2016. "Some are more equal than others: new estimates of global and regional inequality," CERS-IE WORKING PAPERS 1635, Institute of Economics, Centre for Economic and Regional Studies.
  • Handle: RePEc:has:discpr:1635
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    Cited by:

    1. Sugata Marjit & Manoj Pant & Sugandha Huria, 2020. "Unskilled immigration, technical progress, and wages—Role of the household sector," Review of International Economics, Wiley Blackwell, vol. 28(1), pages 235-251, February.
    2. Edwin Fourrier-Nicolaï & Michel Lubrano, 2021. "Bayesian Inference for Parametric Growth Incidence Curves," Research on Economic Inequality, in: Research on Economic Inequality: Poverty, Inequality and Shocks, volume 29, pages 31-55, Emerald Group Publishing Limited.
    3. Zsolt Darvas, 2019. "Why is it So Hard to Reach the EU’s Poverty Target?," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 141(3), pages 1081-1105, February.
    4. Andrea Brandolini & Alfonso Rosolia, 2019. "The Distribution of Well-Being among Europeans," SOEPpapers on Multidisciplinary Panel Data Research 1052, DIW Berlin, The German Socio-Economic Panel (SOEP).
    5. Paul S. F. Yip & Chenhong Peng & Ho Kit Wong & Bing Kwan So, 2020. "Social Welfare Transfers and Poverty Transitions in Hong Kong: Evidence from Two-Wave Panel Data," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 151(3), pages 841-864, October.
    6. Zoriana GONTAR & Vasyl MARCHUK & Olena DURMAN & Nataliia DENKOVYCH & Vasyl DUDKEVYCH, 2020. "Exploring the Experience of the World's Leading Countries in Inclusive Growth as Part of the Post-Industrial Economy: Challenges and Perspectives," Postmodern Openings, Editura Lumen, Department of Economics, vol. 11(2Sup1), pages 222-237, September.
    7. Alberto Díaz Dapena & Esteban Fernández Vázquez & Fernando Rubiera Morollón & Ana Viñuela, 2021. "Mapping poverty at the local level in Europe: A consistent spatial disaggregation of the AROPE indicator for France, Spain, Portugal and the United Kingdom," Regional Science Policy & Practice, Wiley Blackwell, vol. 13(1), pages 63-81, February.
    8. Michael Dauderstädt, 2020. "Einkommensungleichheit in der EU [Income Disparities in the European Union]," Wirtschaftsdienst, Springer;ZBW - Leibniz Information Centre for Economics, vol. 100(8), pages 628-632, August.
    9. Chenhong Peng & Paul S. F. Yip & Yik Wa Law, 2020. "What Factors Beyond Economic Poverty Lead People in High-income Societies to Feel Poor? Evidence from Hong Kong," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 152(3), pages 991-1027, December.
    10. Stefano Filauro, 2017. "European incomes, national advantages: EU-wide inequality and its decomposition by country and region," EERI Research Paper Series EERI RP 2017/05, Economics and Econometrics Research Institute (EERI), Brussels.
    11. Filauro, Stefano & Parolin, Zachary, 2018. "Income Inequality in the European Union & United States: A Comparative Decomposition," SocArXiv g4cd3, Center for Open Science.
    12. Alessia Damonte & Fedra Negri, 2019. "Gauging fiscal worlds: how the EU countries balanced equality and wealth between 2007 and 2016," Quality & Quantity: International Journal of Methodology, Springer, vol. 53(4), pages 1675-1692, July.
    13. Chenhong Peng & Yik-Wa Law, 2023. "How Do Consumption Patterns Influence the Discrepancy Between Economic and Subjective Poverty?," Journal of Happiness Studies, Springer, vol. 24(4), pages 1579-1604, April.

    More about this item

    Keywords

    global and regional distribution of income; Gini coefficient; income inequality; development; simulation modelling;
    All these keywords.

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution
    • D63 - Microeconomics - - Welfare Economics - - - Equity, Justice, Inequality, and Other Normative Criteria and Measurement
    • O15 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Economic Development: Human Resources; Human Development; Income Distribution; Migration

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