IDEAS home Printed from https://ideas.repec.org/p/iza/izadps/dp11355.html
   My bibliography  Save this paper

Inequality among European Working Households, 1890-1960

Author

Listed:
  • Gazeley, Ian

    (University of Sussex)

  • Holmes, Rose

    (University of Sussex)

  • Newell, Andrew T.

    (University of Sussex)

  • Reynolds, Kevin

    (University of Brighton)

  • Gutierrez Rufrancos, Hector

    (University of Sussex)

Abstract

In this article we map, for the first time, the time-path of the size distribution of income among working class households in Western Europe, 1890-1960. To do this we exploit data extracted from a large number of newly digitised household expenditure surveys. Many are not representative of the population, or even of their target-subpopulation, as methods of social investigation were initially primitive, though rapidly evolving over this period. We overcome the consequent problem of comparability by exploiting our knowledge of the methods used by early social investigators to estimate of the scale of known biases. For some we have the original household data, but in most cases we have tables by income group. One by-product of this work is an evaluation of the range of estimation methods for distributional statistics from these historical tables of grouped data. Our central finding is that inequality among working households does not follow the general downward trend in inequality for the early part of the century found in labour share and top income studies. Contrary to Kuznets' prediction, our evidence suggests that on average income inequality among European working households remained stable for three generations from the late nineteenth century onwards.

Suggested Citation

  • Gazeley, Ian & Holmes, Rose & Newell, Andrew T. & Reynolds, Kevin & Gutierrez Rufrancos, Hector, 2018. "Inequality among European Working Households, 1890-1960," IZA Discussion Papers 11355, Institute of Labor Economics (IZA).
  • Handle: RePEc:iza:izadps:dp11355
    as

    Download full text from publisher

    File URL: https://docs.iza.org/dp11355.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    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. Gastwirth, Joseph L & Glauberman, Marcia, 1976. "The Interpolation of the Lorenz Curve and Gini Index from Grouped Data," Econometrica, Econometric Society, vol. 44(3), pages 479-483, May.
    3. Gazeley, Ian & Verdon, Nicola, 2014. "The first poverty line? Davies' and Eden's investigation of rural poverty in the late 18th-century England," Explorations in Economic History, Elsevier, vol. 51(C), pages 94-108.
    4. Gary Solon & Steven J. Haider & Jeffrey M. Wooldridge, 2015. "What Are We Weighting For?," Journal of Human Resources, University of Wisconsin Press, vol. 50(2), pages 301-316.
    5. Brenner,Y. S. & Kaelble,Hartmut & Thomas,Mark (ed.), 1991. "Income Distribution in Historical Perspective," Cambridge Books, Cambridge University Press, number 9780521356473, October.
    6. 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.
    7. Lerman, Robert I. & Yitzhaki, Shlomo, 1989. "Improving the accuracy of estimates of Gini coefficients," Journal of Econometrics, Elsevier, vol. 42(1), pages 43-47, September.
    8. Villasenor, JoseA. & Arnold, Barry C., 1989. "Elliptical Lorenz curves," Journal of Econometrics, Elsevier, vol. 40(2), pages 327-338, February.
    9. Horrell, Sara & Humphries, Jane, 1992. "Old Questions, New Data, and Alternative Perspectives: Families' Living Standards in the Industrial Revolution," The Journal of Economic History, Cambridge University Press, vol. 52(4), pages 849-880, December.
    10. Morrisson, Christian, 2000. "Historical perspectives on income distribution: The case of Europe," Handbook of Income Distribution, in: A.B. Atkinson & F. Bourguignon (ed.), Handbook of Income Distribution, edition 1, volume 1, chapter 4, pages 217-260, Elsevier.
    11. Graham Pyatt & Chau-nan Chen & John Fei, 1980. "The Distribution of Income by Factor Components," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 95(3), pages 451-473.
    12. Peter H. Lindert, 2000. "When did Inequality Rise in Britain and America?," Journal of Income Distribution, Ad libros publications inc., vol. 9(1), pages 2-2, June.
    13. Gazeley, Ian & Newell, Andrew T., 2009. "The End of Destitution," IZA Discussion Papers 4295, Institute of Labor Economics (IZA).
    14. Rossi, Nicola & Toniolo, Gianni & Vecchi, Giovanni, 2001. "Is The Kuznets Curve Still Alive? Evidence From Italian Household Budgets, 1881–1961," The Journal of Economic History, Cambridge University Press, vol. 61(4), pages 904-925, December.
    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. Gazeley, Ian & Holmes, Rose & Lanata Briones, Cecilia & Newell, Andrew T. & Reynolds, Kevin & Rufrancos, Hector Gutierrez, 2018. "Latin American Household Budget Surveys 1913-1970 and What They Tell Us about Economic Inequality among Households," IZA Discussion Papers 11430, Institute of Labor Economics (IZA).

    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. Nassim Nicholas Taleb, 2015. "How to (Not) Estimate Gini Coefficients for Fat Tailed Variables," Papers 1510.04841, arXiv.org.
    2. Salvatore Morelli & Timothy Smeeding & Jeffrey Thompson, 2014. "Post-1970 Trends in Within-Country Inequality and Poverty: Rich and Middle Income Countries," CSEF Working Papers 356, Centre for Studies in Economics and Finance (CSEF), University of Naples, Italy.
    3. Tom Van Ourti & Philip Clarke, 2008. "The Bias of the Gini Coefficient due to Grouping," Tinbergen Institute Discussion Papers 08-095/3, Tinbergen Institute.
    4. Wodon, Quentin & Yitzhaki, Shlomo, 2003. "The effect of using grouped data on the estimation of the Gini income elasticity," Economics Letters, Elsevier, vol. 78(2), pages 153-159, February.
    5. Juan Luis Londoño & Miguel Székely, 2000. "Persistent Poverty and Excess Inequality: Latin America, 1970-1995," Journal of Applied Economics, Universidad del CEMA, vol. 3, pages 93-134, May.
    6. Paul Makdissi & Myra Yazbeck, 2012. "On the Measurement of Indignation," Working Papers 1213E, University of Ottawa, Department of Economics.
    7. Pablo García S. & Camilo Pérez N., 2017. "Desigualdad, inflación, ciclos y crisis en Chile," Estudios de Economia, University of Chile, Department of Economics, vol. 44(2 Year 20), pages 185-221, December.
    8. Onrubia Fernández, Jorge & Picos, Fidel & Rodado, María del Carmen, 2019. "Shifting tax burden to top income earners: What is the best way to reduce inequality?," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 13, pages 1-31.
    9. Londoño, Juan Luis & Székely, Miguel, 1997. "Persistent Poverty and Excess Inequality: Latin America, 1970-1995," IDB Publications (Working Papers) 6092, Inter-American Development Bank.
    10. Mathias Silva, 2023. "Parametric models of income distributions integrating misreporting and non-response mechanisms," AMSE Working Papers 2311, Aix-Marseille School of Economics, France.
    11. 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.
    12. Walter Bossert & Conchita D’Ambrosio & Kohei Kamaga, 2021. "Extreme Values, Means, and Inequality Measurement," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 67(3), pages 564-590, September.
    13. 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.
    14. Frank Cowell & Emmanuel Flachaire, 2021. "Inequality Measurement: Methods and Data," Post-Print hal-03589066, HAL.
    15. Burkhauser, Richard V. & Herault, Nicolas & Jenkins, Stephen P. & Wilkins, Roger, 2016. "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 Papers 9718, Institute of Labor Economics (IZA).
    16. Channing Arndt & Kristi Mahrt, 2017. "Is inequality underestimated in Mozambique? Accounting for underreported consumption," WIDER Working Paper Series 153, World Institute for Development Economic Research (UNU-WIDER).
    17. 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).
    18. Berisha, Edmond & Meszaros, John & Olson, Eric, 2018. "Income inequality, equities, household debt, and interest rates: Evidence from a century of data," Journal of International Money and Finance, Elsevier, vol. 80(C), pages 1-14.
    19. Bengtsson, Erik & Waldenström, Daniel, 2018. "Capital Shares and Income Inequality: Evidence from the Long Run," The Journal of Economic History, Cambridge University Press, vol. 78(3), pages 712-743, September.
    20. Diego Winkelried & Bruno Escobar, 2022. "Declining inequality in Latin America? Robustness checks for Peru," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 20(1), pages 223-243, March.

    More about this item

    Keywords

    inequality; working households; Europe; 20th century;
    All these keywords.

    JEL classification:

    • N33 - Economic History - - Labor and Consumers, Demography, Education, Health, Welfare, Income, Wealth, Religion, and Philanthropy - - - Europe: Pre-1913
    • N34 - Economic History - - Labor and Consumers, Demography, Education, Health, Welfare, Income, Wealth, Religion, and Philanthropy - - - Europe: 1913-
    • O15 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Economic Development: Human Resources; Human Development; Income Distribution; Migration

    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:iza:izadps:dp11355. 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: Holger Hinte (email available below). General contact details of provider: https://edirc.repec.org/data/izaaade.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.