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The Impact Of Education On Income Distribution

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  • Jan Tinbergen

Abstract

In this paper the author adds some further empirical tests of his theory of income distribution. This theory (cf. this Review, Series 16, Number 3, September 1970, p. 221 ff) sees income distribution as the distribution of prices of production factors, especially labour, of different quality and prices as the effect of demand and supply factors. The quality of labour is represented only by the number of years of schooling. Its supply is described by the actual numbers of people having each of the possible years of schooling; this frequency distribution can be characterized by its average and by some measure of its dispersion or by one of its deciles (in particular the highest) expressed in terms of its median. The demand for the various qualities of labour can be supposed to be reflected by (i) total demand for commodities, but (ii) more accurately by the percentage of third‐level educated people used in and weighted by the size of the four main sectors of production: agriculture, manufacturing, trade and transport, and other services. Extensive material collected and reworked by Professors B. R. Chiswick for the U.S.A. and Canada and T. P. Schultz and L. S. Burns with H. E. Frech III for the Netherlands is used in cross‐section tests to explain variations in income distribution in the states of the U.S.A. and the provinces of Canada and the Netherlands. The results can be found in the tables. While further increase and smaller dispersion in years of schooling, according to some of the findings presented, would only moderately reduce the degree of inequality in the U.S.A. and Canada, more result seems to be possible according to other findings, including those for the Netherlands. In the latter category the second demand index mentioned above has been used. This paper is one of several devoted in various ways to the testing of the same theory.

Suggested Citation

  • Jan Tinbergen, 1972. "The Impact Of Education On Income Distribution," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 18(3), pages 255-265, September.
    • Handle: RePEc:bla:revinw:v:18:y:1972:i:3:p:255-265
    DOI: 10.1111/j.1475-4991.1972.tb00865.x
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    Cited by:

    1. Alessio Emanuele Biondo & Roberto Cellini & Tiziana Cuccia, 2020. "Choices on museum attendance: An agent‐based approach," Metroeconomica, Wiley Blackwell, vol. 71(4), pages 882-897, November.
    2. Javier Alejo & Leonardo Gasparini & Gabriel Montes-Rojas & Walter Sosa-Escudero, 2024. "A decomposition method to evaluate the ‘paradox of progress’, with evidence for Argentina," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 22(2), pages 453-472, June.
    3. Ghosh, sudeshna, 2017. "Education Attainment Forecasting and Economic Inequality United States," MPRA Paper 89712, University Library of Munich, Germany.
    4. Park, Kang H., 1996. "Educational expansion and educational inequality on income distribution," Economics of Education Review, Elsevier, vol. 15(1), pages 51-58, February.
    5. Ruikun An & Feng Wang & Jiro Sakurai & Hideki Kitagawa, 2024. "Willing or Not? Rural Residents’ Willingness to Pay for Ecosystem Conservation in Economically Underdeveloped Regions: A Case Study in China’s Qinling National Park," Sustainability, MDPI, vol. 16(6), pages 1-17, March.
    6. Dobdinga C. Fonchamnyo & Nubonyin Hilda Fokong, 2017. "Educational Gender Gap, Economic Growth and Income Distribution: An Empirical Study of the Interrelationship in Cameroon," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 9(3), pages 168-176, March.
    7. Moser, Mathias & Schnetzer, Matthias, 2014. "The Geography of Average Income and Inequality: Spatial Evidence from Austria," Department of Economics Working Paper Series 191, WU Vienna University of Economics and Business.
    8. Patrinos,Harry Anthony, 2020. "The Learning Challenge in the 21st Century," Policy Research Working Paper Series 9214, The World Bank.
    9. Andersen, Torben M, 2015. "Social background, education and inequality," CEPR Discussion Papers 10433, C.E.P.R. Discussion Papers.
    10. Biondo, Alessio Emanuele & Cellini, Roberto & Cuccia, Tiziana, 2022. "Cultural consumption in times of lock-down: An agent-based model of choice," Structural Change and Economic Dynamics, Elsevier, vol. 62(C), pages 430-440.
    11. Xiao, Han & Zheng, Xinye & Xie, Lunyu, 2022. "Promoting pro-poor growth through infrastructure investment: Evidence from the Targeted Poverty Alleviation program in China," China Economic Review, Elsevier, vol. 71(C).
    12. Campos-González, Jorge & Balcombe, Kelvin, 2024. "The race between education and technology in Chile and its impact on the skill premium," Economic Modelling, Elsevier, vol. 131(C).

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