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Where has all the bias gone? Detecting gender-bias in the household allocation of educational expenditure

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  • Geeta G. Kingdon

Abstract

The reliability of the household consumption based (Engel curve) methodology in detecting gender bias has been called into question because it has generally failed to confirm bias even where it exists. This paper seeks to find explanations for this failure by exploiting a dataset that has educational expenditure information at the individual level and also, by aggregation, at the household level. We find that in the basic education age groups, the discriminatory mechanism in education is via differential enrolment rates for boys and girls. Education expenditure conditional on enrolment is equal for boys and girls. The Engel curve method fails for two reasons. Firstly, it models a single equation for the two stage process. Second, even when we make individual and household level expenditure equations as similar as possible, the household level equation still fails to ‘pick up’ gender bias in about one third of the cases where the individual-level equation shows significant bias. The paper concludes that only individual based data can accurately capture the full extent of gender bias.

Suggested Citation

  • Geeta G. Kingdon, 2003. "Where has all the bias gone? Detecting gender-bias in the household allocation of educational expenditure," CSAE Working Paper Series 2003-13, Centre for the Study of African Economies, University of Oxford.
  • Handle: RePEc:csa:wpaper:2003-13
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    Cited by:

    1. Rozana Himaz, 2008. "Intrahousehold Allocation of Education Expenditure and Returns to Education: The Case of Sri Lanka," Economics Series Working Papers 393, University of Oxford, Department of Economics.
    2. Holger Strulik, 2013. "School Attendance And Child Labor—A Model Of Collective Behavior," Journal of the European Economic Association, European Economic Association, vol. 11(2), pages 246-277, April.
    3. Rana Ejaz Ali Khan & Karamat Ali, 2005. "Bargaining Over Sons' and Daughters' Schooling-Probit Analysis of Household Behavior," HEW 0505002, University Library of Munich, Germany.
    4. Fafchamps, Marcel & Wahba, Jackline, 2006. "Child labor, urban proximity, and household composition," Journal of Development Economics, Elsevier, vol. 79(2), pages 374-397, April.

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    • O - Economic Development, Innovation, Technological Change, and Growth
    • P - Economic Systems

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