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Democracy, Education, and Equality

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  • Roemer,John E.

Abstract

Many believe that equality of opportunity will be achieved when the prospects of children no longer depend upon the wealth and education of their parents. The institution through which the link between child and parental prospects may be weakened is public education. Many also believe that democracy is the political institution that will bring about justice. This study, first published in 2006, asks whether democracy, modeled as competition between political parties that represent different interests in the polity, will result in educational funding policies that will, at least eventually, produce citizens who have equal capacities (human capital), thus breaking the link between family background and child prospects. In other words, will democracy engender, through the educational finance policies it produces, a state of equal opportunity in the long run?

Suggested Citation

  • Roemer,John E., 2006. "Democracy, Education, and Equality," Cambridge Books, Cambridge University Press, number 9780521846653, March.
  • Handle: RePEc:cup:cbooks:9780521846653
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    1. Eide, Eric & Showalter, Mark H., 1998. "The effect of school quality on student performance: A quantile regression approach," Economics Letters, Elsevier, vol. 58(3), pages 345-350, March.
    2. Omar Arias & Walter Sosa-Escudero & Kevin F. Hallock, 2001. "Individual heterogeneity in the returns to schooling: instrumental variables quantile regression using twins data," Empirical Economics, Springer, pages 7-40.
    3. Oaxaca, Ronald, 1973. "Male-Female Wage Differentials in Urban Labor Markets," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 14(3), pages 693-709, October.
    4. Manning, Willard G. & Blumberg, Linda & Moulton, Lawrence H., 1995. "The demand for alcohol: The differential response to price," Journal of Health Economics, Elsevier, vol. 14(2), pages 123-148, June.
    5. Jason Abrevaya, 2001. "The effects of demographics and maternal behavior on the distribution of birth outcomes," Empirical Economics, Springer, vol. 26(1), pages 247-257.
    6. Moshe Buchinsky, 1998. "The dynamics of changes in the female wage distribution in the USA: a quantile regression approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 13(1), pages 1-30.
    7. Amanda Gosling & Stephen Machin & Costas Meghir, 2000. "The Changing Distribution of Male Wages in the U.K," Review of Economic Studies, Oxford University Press, vol. 67(4), pages 635-666.
    8. James M. Poterba & Kim S. Rueben, 1994. "The Distribution of Public Sector Wage Premia: New Evidence Using Quantile Regression Methods," NBER Working Papers 4734, National Bureau of Economic Research, Inc.
    9. Čížek, Pavel, 1999. "Quantile regression," SFB 373 Discussion Papers 1999,78, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    10. Heckman, James, 2013. "Sample selection bias as a specification error," Applied Econometrics, Publishing House "SINERGIA PRESS", pages 129-137.
    11. Angel López-Nicolás & Jaume García & Pedro J. Hernández, 2001. "How wide is the gap? An investigation of gender wage differences using quantile regression," Empirical Economics, Springer, vol. 26(1), pages 149-167.
    12. Trede, Mark, 1998. "Making mobility visible: a graphical device," Economics Letters, Elsevier, vol. 59(1), pages 77-82, April.
    13. Alberto Abadie & Joshua D. Angrist & Guido W. Imbens, 1998. "Instrumental Variables Estimation of Quantile Treatment Effects," NBER Technical Working Papers 0229, National Bureau of Economic Research, Inc.
    14. José Mata & José A. F. Machado, 2005. "Counterfactual decomposition of changes in wage distributions using quantile regression," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(4), pages 445-465.
    15. Kahn, Lawrence M, 1998. "Collective Bargaining and the Interindustry Wage Structure: International Evidence," Economica, London School of Economics and Political Science, vol. 65(260), pages 507-534, November.
    16. Shih-Kang Chao & Wolfgang Karl Härdle & Weining Wang, 2012. "Quantile Regression in Risk Calibration," SFB 649 Discussion Papers SFB649DP2012-006, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
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    Cited by:

    1. Zhang, Yingqiang & Eriksson, Tor, 2010. "Inequality of opportunity and income inequality in nine Chinese provinces, 1989-2006," China Economic Review, Elsevier, pages 607-616.
    2. John Roemer, 2012. "The political economy of income taxation under asymmetric information: the two-type case," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 3(1), pages 181-199, March.
    3. Gordon Anderson & Teng Leo & Robert Muelhaupt, 2014. "Measuring Advances in Equality of Opportunity: The Changing Gender Gap in Educational Attainment in Canada in the Last Half Century," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 119(1), pages 73-99, October.
    4. Rehme, Günther, 2014. "Endogenous (re-)distributive policies and economic growth: A comparative static analysis," Economic Modelling, Elsevier, vol. 40(C), pages 355-366.

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