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Gender and Child Mortality in Pakistan


  • Gangadharan, L.
  • Maitra, P.


In this paper we use child level data from Pakistan to estimate the probability of the child dying and the number of days the child was alive before dying. We find that overall girls have a higher probability of surviving and when we look at disaggregated data we find that relative to boys, girls have a significantly lower probability of dying in the age group 0-1 but have a significantly higher probability of dying in the age group 1-5. Education of the mother has a significant and negative effect on child mortality and there is a threshold level of education that the mother has to attain before education starts affecting child mortality. However the effect of education is not as strong as what the literature has suggested. Additionally we find that increased duration between the births significantly reduces child mortality. Children born to older parents have a lower probability of dying and the age of the mother at the time of birth has a significant effect on child mortality though the age of mother effect on child mortality differs across age groups of the child. We argue that the higher mortality of girls in the age group 1-5 is indicative of discrimination against girls in the form of lower health and other resource inputs.

Suggested Citation

  • Gangadharan, L. & Maitra, P., 2000. "Gender and Child Mortality in Pakistan," Department of Economics - Working Papers Series 763, The University of Melbourne.
  • Handle: RePEc:mlb:wpaper:763

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    References listed on IDEAS

    1. Bohm, Peter, 1972. "Estimating demand for public goods: An experiment," European Economic Review, Elsevier, vol. 3(2), pages 111-130.
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    5. Andreoni, James, 1995. "Cooperation in Public-Goods Experiments: Kindness or Confusion?," American Economic Review, American Economic Association, vol. 85(4), pages 891-904, September.
    6. Burks, Stephen V. & Carpenter, Jeffrey P. & Verhoogen, Eric, 2003. "Playing both roles in the trust game," Journal of Economic Behavior & Organization, Elsevier, vol. 51(2), pages 195-216, June.
    7. Palfrey, Thomas R & Prisbrey, Jeffrey E, 1997. "Anomalous Behavior in Public Goods Experiments: How Much and Why?," American Economic Review, American Economic Association, vol. 87(5), pages 829-846, December.
    8. Offerman, Theo & Sonnemans, Joep & Schram, Arthur, 1996. "Value Orientations, Expectations and Voluntary Contributions in Public Goods," Economic Journal, Royal Economic Society, vol. 106(437), pages 817-845, July.
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    JEL classification:

    • J1 - Labor and Demographic Economics - - Demographic Economics
    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions


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