IDEAS home Printed from https://ideas.repec.org/p/sza/wpaper/wpapers377.html
   My bibliography  Save this paper

Estimating historical inequality from social tables: Towards Methodological Consistency

Author

Listed:
  • Dieter von Fintel

    (Department of Economics, Stellenbosch University)

  • Calumet Links

    (Department of Economics, Stellenbosch University)

  • Erik Green

Abstract

Research on long-term historical inequality has expanded to include previously neglected periods and societies, particularly in the global South. This is partly due to the resurgence of the social tables method in economic history, an approach which uses archival records to reconstruct income and wealth distributions in contexts where micro data is unavailable. This method can cause a downward bias in estimating inequality, but there is limited evidence of this bias in economic history. We collected a new data set of 108 historical social tables spanning over a 1000 years. We found that the compilers consistently made careful methodological choices that took data limitations into account. We found that the inequality estimates are not systematically related to the number of classes chosen or the size of the top class, but that choosing bottom classes that bundle together even small variations in income or wealth can introduce a downward bias to the inequality estimates. This drawback can be overcome by using methodological cohesion to mitigate the problem of limited information about the poorest classes in colonial archives.

Suggested Citation

  • Dieter von Fintel & Calumet Links & Erik Green, 2023. "Estimating historical inequality from social tables: Towards Methodological Consistency," Working Papers 01/2023, Stellenbosch University, Department of Economics.
    • Handle: RePEc:sza:wpaper:wpapers377
    as

    Download full text from publisher

    File URL: https://www.ekon.sun.ac.za/wpapers/2023/wp012023/wp012023.pdf
    File Function: First version, 2023
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Milanovic, Branko & Lindert, Peter & Williamson, Jeffrey, 2007. "Measuring Ancient Inequality," MPRA Paper 5388, University Library of Munich, Germany.
    2. Tom Van Ourti & Philip Clarke, 2011. "A Simple Correction to Remove the Bias of the Gini Coefficient due to Grouping," The Review of Economics and Statistics, MIT Press, vol. 93(3), pages 982-994, August.
    3. Stephen P. Jenkins, 2017. "Pareto Models, Top Incomes and Recent Trends in UK Income Inequality," Economica, London School of Economics and Political Science, vol. 84(334), pages 261-289, April.
    4. Valpy FitzGerald, 2008. "Economic development and fluctuations in earnings inequality in the very long run: The evidence from Latin America 1900-2000," Journal of International Development, John Wiley & Sons, Ltd., vol. 20(8), pages 1028-1048.
    5. Branko Milanovic, 2006. "An Estimate Of Average Income And Inequality In Byzantium Around Year 1000," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 52(3), pages 449-470, September.
    6. Michiel de Haas, 2022. "Reconstructing income inequality in a colonial cash crop economy: five social tables for Uganda, 1925–1965 [Long-term trends in income inequality: winners and losers of economic change in Ghana, 18," European Review of Economic History, European Historical Economics Society, vol. 26(2), pages 255-283.
    7. Alfani, Guido & Tadei, Federico, 2017. "Income Inequality In Colonial Africa: Building Social Tables For Pre-Independence Central African Republic, Ivory Coast And Senegal," African Economic History Working Paper 33/2017, African Economic History Network.
    8. Wojciech Kopczuk, 2015. "What Do We Know about the Evolution of Top Wealth Shares in the United States?," Journal of Economic Perspectives, American Economic Association, vol. 29(1), pages 47-66, Winter.
    9. 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.
    10. Kenneth L. Sokoloff & Stanley L. Engerman, 2000. "Institutions, Factor Endowments, and Paths of Development in the New World," Journal of Economic Perspectives, American Economic Association, vol. 14(3), pages 217-232, Summer.
    11. Thomas Piketty & Emmanuel Saez & Gabriel Zucman, 2022. "Twenty Years and Counting: Thoughts about Measuring the Upper Tail," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 20(1), pages 255-264, March.
    12. Emmanuel Saez & Gabriel Zucman, 2014. "Wealth Inequality in the United States since 1913: Evidence from Capitalized Income Tax Data," NBER Working Papers 20625, National Bureau of Economic Research, Inc.
    13. van Zanden, Jan Luiten & van Leeuwen, Bas, 2012. "Persistent but not consistent: The growth of national income in Holland 1347–1807," Explorations in Economic History, Elsevier, vol. 49(2), pages 119-130.
    14. Anthony F. Shorrocks & Guanghua Wan, 2008. "Ungrouping Income Distributions: Synthesising Samples for Inequality and Poverty Analysis," WIDER Working Paper Series RP2008-16, World Institute for Development Economic Research (UNU-WIDER).
    15. Dagum, Camilo, 1997. "A New Approach to the Decomposition of the Gini Income Inequality Ratio," Empirical Economics, Springer, vol. 22(4), pages 515-531.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Milanovic, Branko, 2024. "How rich were the rich? An empirically-based taxonomy of pre-industrial bases of wealth," Explorations in Economic History, Elsevier, vol. 93(C).
    2. Milanovic, Branko, 2024. "The three eras of global inequality, 1820–2020 with the focus on the past thirty years," World Development, Elsevier, vol. 177(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Nora Lustig & Andrea Vigorito, 2025. "Including the Rich in Income Inequality Measures: An Assessment of Correction Approaches," Working Papers 2503, Tulane University, Department of Economics.
    2. Modalsli, Jørgen, 2011. "Inequality and growth in the very long run: inferring inequality from data on social groups," Memorandum 11/2011, Oslo University, Department of Economics.
    3. Lustig, Nora, 2020. "The “Missing Rich” in Household Surveys: Causes and Correction Approaches," SocArXiv j23pn_v1, Center for Open Science.
    4. Nora Lustig, 2019. "The “Missing Rich” in Household Surveys: Causes and Correction Approaches," Commitment to Equity (CEQ) Working Paper Series 75, Tulane University, Department of Economics.
    5. Metzing, Maria & Bartels, Charlotte, 2016. "An integrated approach for top-corrected Ginis," VfS Annual Conference 2016 (Augsburg): Demographic Change 145818, Verein für Socialpolitik / German Economic Association.
    6. Pablo Astorga, 2015. "Functional Inequality in Latin America: News from the Twentieth Century," Oxford Economic and Social History Working Papers _135, University of Oxford, Department of Economics.
    7. Charlotte Bartels & Maria Metzing, 2019. "An integrated approach for a top-corrected income distribution," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 17(2), pages 125-143, June.
    8. Milanovic, Branko, 2024. "How rich were the rich? An empirically-based taxonomy of pre-industrial bases of wealth," Explorations in Economic History, Elsevier, vol. 93(C).
    9. Pablo Astorga, 2015. "Functional Inequality in Latin America: News from the Twentieth Century," Oxford University Economic and Social History Series _135, Economics Group, Nuffield College, University of Oxford.
    10. Nora Lustig, 2020. "The ``missing rich'' in household surveys: causes and correction approaches," Working Papers 520, ECINEQ, Society for the Study of Economic Inequality.
    11. Mathias Silva, 2023. "Parametric models of income distributions integrating misreporting and non-response mechanisms," AMSE Working Papers 2311, Aix-Marseille School of Economics, France.
    12. Elinder, Mikael & Erixson, Oscar & Waldenström, Daniel, 2018. "Inheritance and wealth inequality: Evidence from population registers," Journal of Public Economics, Elsevier, vol. 165(C), pages 17-30.
    13. Sean Higgins & Nora Lustig & Andrea Vigorito, 2018. "The Rich Underreport their Income: Assessing Bias in Inequality Estimates and Correction Methods using Linked Survey and Tax Data," Working Papers 1808, Tulane University, Department of Economics.
    14. Rodríguez Weber, Javier, 2015. "Estimación de desigualdad de ingreso y otras variables relacionadas para Chile entre 1860 y 1970. Metodología y resultados obtenidos [Income inequality estimates for Chile between 1860 and 1970. Me," MPRA Paper 68400, University Library of Munich, Germany.
    15. A. B. Atkinson & Stephen P. Jenkins, 2020. "A Different Perspective on the Evolution of UK Income Inequality," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 66(2), pages 253-266, June.
    16. Thomas Blanchet & Ignacio Flores & Marc Morgan, 2022. "The weight of the rich: improving surveys using tax data," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 20(1), pages 119-150, March.
    17. François Bourguignon, 2018. "Simple adjustments of observed distributions for missing income and missing people," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 16(2), pages 171-188, June.
    18. Pedro Fandiño, 2022. "The role of social conventions on wage inequality: the Brazilian trajectory and the missed “Great Leveling”," Review of Evolutionary Political Economy, Springer, vol. 3(2), pages 435-455, July.
    19. Frank Cowell & Emmanuel Flachaire, 2021. "Inequality Measurement: Methods and Data," Post-Print hal-03589066, HAL.
    20. Burdín, Gabriel & De Rosa, Mauricio & Vigorito, Andrea & Vilá, Joan, 2022. "Falling inequality and the growing capital income share: Reconciling divergent trends in survey and tax data," World Development, Elsevier, vol. 152(C).

    More about this item

    Keywords

    Social tables; Gini; inequality; pre-industrial; grouped data;
    All these keywords.

    JEL classification:

    • N30 - Economic History - - Labor and Consumers, Demography, Education, Health, Welfare, Income, Wealth, Religion, and Philanthropy - - - General, International, or Comparative
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sza:wpaper:wpapers377. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Melt van Schoor (email available below). General contact details of provider: https://edirc.repec.org/data/desunza.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.