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Shifting gendered social norms: Impact of a mass media campaign on child health in India

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  • Aparajita Dasgupta

    (Ashoka University)

  • Anisha Sharma

    (Ashoka University)

Abstract

Policy measures that seek to address son preference through restrictions on the tools of sex-selective abortions, without addressing the underlying causes, have been found to generate negative welfare consequences for unwanted surviving girls. Unlike these topdown supply-side measures, demand-side measures that focus on increasing the demand for girls by shifting social norms of son preference can mitigate these adverse welfare consequences. We study the impact of an intervention aimed at reducing discrimination against girls, which has both supply-side and demand-side elements. The intervention, implemented in India between 2015-18 included a mass media campaign designed to increase the perception of the value of a female child, while also tightening the policing of illegal sex-selective abortions. We exploit variation in the timing of exposure to the programme across Indian districts as well as quasi-exogenous variation in the sex of the firstborn child to identify the impact of the programme and find that it led to an increased proportion of female births as well as a reduction in the gender gap in mortality in intensively treated families. The main mechanism that explains our results is a relative increase in health investments in daughters, such as breastfeeding and vaccinations.

Suggested Citation

  • Aparajita Dasgupta & Anisha Sharma, 2022. "Shifting gendered social norms: Impact of a mass media campaign on child health in India," Working Papers 85, Ashoka University, Department of Economics.
    • Handle: RePEc:ash:wpaper:85
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    References listed on IDEAS

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    1. Goodman-Bacon, Andrew, 2021. "Difference-in-differences with variation in treatment timing," Journal of Econometrics, Elsevier, vol. 225(2), pages 254-277.
    2. Diva Dhar & Tarun Jain & Seema Jayachandran, 2022. "Reshaping Adolescents' Gender Attitudes: Evidence from a School-Based Experiment in India," American Economic Review, American Economic Association, vol. 112(3), pages 899-927, March.
    3. Callaway, Brantly & Sant’Anna, Pedro H.C., 2021. "Difference-in-Differences with multiple time periods," Journal of Econometrics, Elsevier, vol. 225(2), pages 200-230.
    4. Clément de Chaisemartin & Xavier D'Haultfœuille, 2020. "Two-Way Fixed Effects Estimators with Heterogeneous Treatment Effects," American Economic Review, American Economic Association, vol. 110(9), pages 2964-2996, September.
    5. Eliana La Ferrara & Alberto Chong & Suzanne Duryea, 2012. "Soap Operas and Fertility: Evidence from Brazil," American Economic Journal: Applied Economics, American Economic Association, vol. 4(4), pages 1-31, October.
    6. Sonia Bhalotra & Tom Cochrane, 2010. "Where have all the young girls gone? Identification of sex selection in India," The Centre for Market and Public Organisation 10/254, The Centre for Market and Public Organisation, University of Bristol, UK.
    7. S Anukriti & Sonia Bhalotra & Eddy H F Tam, 2022. "On the Quantity and Quality of Girls: Fertility, Parental Investments and Mortality," The Economic Journal, Royal Economic Society, vol. 132(641), pages 1-36.
    8. Aparajita Dasgupta & Anisha Sharma, 2021. "Can Legal Bans on Sex Detection Technology Reduce Gender Discrimination?," Working Papers 58, Ashoka University, Department of Economics.
    9. Seema Jayachandran & Rohini Pande, 2017. "Why Are Indian Children So Short? The Role of Birth Order and Son Preference," American Economic Review, American Economic Association, vol. 107(9), pages 2600-2629, September.
    10. Sun, Liyang & Abraham, Sarah, 2021. "Estimating dynamic treatment effects in event studies with heterogeneous treatment effects," Journal of Econometrics, Elsevier, vol. 225(2), pages 175-199.
    11. Goodman-Bacon, Andrew, 2021. "Difference-in-differences with variation in treatment timing," Journal of Econometrics, Elsevier, vol. 225(2), pages 254-277.
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