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Testing for Son Preference in South Africa

Author

Listed:
  • Lata Gangadharan

    (University of Melbourne)

  • Pushkar Maitra

    (University of Sydney)

Abstract

Evidence from most developing countries suggest that parents have a preference for sons over daughters. This is know as son preference. This paper uses individual level unit record data to test the son preference hypothesis in South Africa. We use an accelerated hazard model to estimate the duration between successive births and our results indicate that son preference exists only for the Indian community in South Africa. Indian households prefer to have a higher duration between children following the birth of a son, irrespective of the number of children they already have. For the rest of the population, there is either no son preference or in some cases a weak preference for daughters. Our results appear to refute the usual arguments for son preference (including support for elderly parents and contribution to household income) and instead suggest the importance of religious beliefs and social customs (dowry system, lineage, familial and kinship ties etc.) in directing parental preferences.

Suggested Citation

  • Lata Gangadharan & Pushkar Maitra, 2000. "Testing for Son Preference in South Africa," Econometric Society World Congress 2000 Contributed Papers 0072, Econometric Society.
  • Handle: RePEc:ecm:wc2000:0072
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    Citations

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    Cited by:

    1. Aparna Lhila & Kosali Simon, 2008. "Prenatal health investment decisions: Does the child’s sex matter?," Demography, Springer;Population Association of America (PAA), vol. 45(4), pages 885-905, November.
    2. Lambert, Sylvie & Rossi, Pauline, 2016. "Sons as widowhood insurance: Evidence from Senegal," Journal of Development Economics, Elsevier, vol. 120(C), pages 113-127.
    3. Pauline Rossi & Léa Rouanet, 2015. "Gender Preferences in Africa: A Comparative Analysis of Fertility Choices," Working Papers halshs-01074934, HAL.
    4. Tarun Jain, 2014. "Where There Is a Will: Fertility Behavior and Sex Bias in Large Families," Journal of Human Resources, University of Wisconsin Press, vol. 49(2), pages 393-423.
    5. Silvia Helena Barcellos & Leandro S. Carvalho & Adriana Lleras-Muney, 2014. "Child Gender and Parental Investments in India: Are Boys and Girls Treated Differently?," American Economic Journal: Applied Economics, American Economic Association, vol. 6(1), pages 157-189, January.
    6. repec:spr:jopoec:v:31:y:2018:i:2:d:10.1007_s00148-017-0668-6 is not listed on IDEAS
    7. Rossi, Pauline & Rouanet, Léa, 2015. "Gender Preferences in Africa: A Comparative Analysis of Fertility Choices," World Development, Elsevier, vol. 72(C), pages 326-345.
    8. Chew, Soo Hong & Yi, Junjian & Zhang, Junsen & Zhong, Songfa, 2017. "Risk Aversion and Son Preference: Experimental Evidence from Chinese Twin Parents," IZA Discussion Papers 10519, Institute for the Study of Labor (IZA).
    9. Lindskog, Annika, 2013. "The effect of siblings’ education on school-entry in the Ethiopian highlands," Economics of Education Review, Elsevier, vol. 34(C), pages 45-68.
    10. Margaret Irving, 2008. "Gender patterns in household health expenditure allocation: A study of South Africa," Economics Series Working Papers CSAE WPS/2008-32, University of Oxford, Department of Economics.
    11. Sylvie Lambert & Pauline Rossi, 2015. "Sons as Widowhood Insurance: Evidence from Senegal," Working Papers halshs-00948098, HAL.
    12. van der Stoep, Gabrielle, 2008. "Childbearing and labour force participation in South Africa: sibling composition as an identification strategy?," MPRA Paper 52908, University Library of Munich, Germany.

    More about this item

    JEL classification:

    • J16 - Labor and Demographic Economics - - Demographic Economics - - - Economics of Gender; Non-labor Discrimination
    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • C41 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Duration Analysis; Optimal Timing Strategies
    • C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models; Switching Regression Models; Threshold Regression Models

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