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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
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    References listed on IDEAS

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    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, January.
    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.
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    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).

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    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

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