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A Flow Measure of Missing Women by Age and Disease

Author

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  • Stephan Klasen
  • Sebastian Vollmer

Abstract

The existing literature on 'missing women' has suggested that the problem is mostly concentrated in India and China, and mostly related to sex-selective abortions and post-birth neglect of female children. In a recent paper in the Review of Economic Studies, Anderson and Ray (AR) develop a new ‘flow’ measure of missing women in developing countries by comparing actual age-sex-specific mortality rates with 'expected' ones. Contrary to the existing literature on missing women, they, and the World Bank which subsequently followed this method, find that gender bias in mortality is much larger than previously found (4-5 million excess female deaths per year), is as severe among adults as it is among children in India, is larger in Sub-Saharan Africa than in China and India, and existed on a large scale in the US around 1900. We first show that the data for Sub-Saharan Africa used by AR are generated by simulations in ways that deliver the findings on Africa (and the US in 1900) essentially by construction. We also show that the findings are entirely dependent on a highly implausible reference standard for sex-specific mortality from rich countries that is inappropriately applied to settings in developing countries; the attempt to control for differences in the disease environment does not correct for this problem and leads to implausible results. When a more appropriate reference standard is used, most of the new findings of AR regarding the regional and age composition of missing women disappear.

Suggested Citation

  • Stephan Klasen & Sebastian Vollmer, 2018. "A Flow Measure of Missing Women by Age and Disease," Courant Research Centre: Poverty, Equity and Growth - Discussion Papers 254, Courant Research Centre PEG.
  • Handle: RePEc:got:gotcrc:254
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    References listed on IDEAS

    as
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    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Missing women; gender bias; mortality; disease; age; Sub-Saharan Africa; China; India;
    All these keywords.

    JEL classification:

    • J16 - Labor and Demographic Economics - - Demographic Economics - - - Economics of Gender; Non-labor Discrimination
    • D63 - Microeconomics - - Welfare Economics - - - Equity, Justice, Inequality, and Other Normative Criteria and Measurement
    • I10 - Health, Education, and Welfare - - Health - - - General

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