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Reconsidering Gender Bias in Intrahousehold Allocation in India

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  • Laura Zimmermann

Abstract

Finding evidence of gender discrimination among children in the intrahousehold allocation of goods has often proven to be difficult. This article uses data on education expenditures in India to test whether data aggregation, data reliability and the statistical method used help explain this pattern. Results suggest that discrimination against girls is increasing in age and robust to the statistical method and the expenditure measure at the all-India level, although state-level results are more sensitive. I find that data aggregation and statistical method are important factors in detecting gender bias, while data reliability does not seem to play a major role.

Suggested Citation

  • Laura Zimmermann, 2012. "Reconsidering Gender Bias in Intrahousehold Allocation in India," Journal of Development Studies, Taylor & Francis Journals, vol. 48(1), pages 151-163, September.
    • Handle: RePEc:taf:jdevst:v:48:y:2012:i:1:p:151-163
    DOI: 10.1080/00220388.2011.629652
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    Citations

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    Cited by:

    1. Heath, Rachel & Tan, Xu, 2018. "Worth fighting for: Daughters improve their mothers' autonomy in South Asia," Journal of Development Economics, Elsevier, vol. 135(C), pages 255-271.
    2. Jacob, Arun, 2016. "Gender Bias in Educational Attainment in India : The Role of Dowry Payments," MPRA Paper 76338, University Library of Munich, Germany.
    3. Masahiro Hori & Nahoko Mitsuyama & Satoshi Shimizutani, 2016. "New Evidence on Intra-Household Allocation of Resources in Japanese Households," The Japanese Economic Review, Japanese Economic Association, vol. 67(1), pages 77-95, March.
    4. Chayanika Mitra, 2024. "Gender Bias in Education Expenditure among Religious and Social Groups: A Case Study for Below Class 10 Level in West Bengal," Arthaniti: Journal of Economic Theory and Practice, , vol. 23(1), pages 101-117, June.
    5. Sutirtha Bandyopadhyay & Bipasha Maity, 2021. "Widowhood and Consumption of Private Assignable Goods: The Role of Socio-Economic Status, Rainfall Shocks and Historical Institutions," Working Papers 73, Ashoka University, Department of Economics.
    6. Santiago Acerenza & Néstor Gandelman, 2019. "Household Education Spending in Latin America and the Caribbean: Evidence from Income and Expenditure Surveys," Education Finance and Policy, MIT Press, vol. 14(1), pages 61-87, Winter.
    7. Kadam, Aditi & Dorfman, Jeffrey H., 2023. "Looking for boy-girl discrimination using time-use data," 2023 Annual Meeting, July 23-25, Washington D.C. 335745, Agricultural and Applied Economics Association.
    8. Arora, Puneet & Roy, Moumita, 2025. "Are students really biased against female professors? — Experimental evidence from India," Journal of Development Economics, Elsevier, vol. 172(C).
    9. Balakrishnan, Uttara & Tsaneva, Magda, 2021. "Air pollution and academic performance: Evidence from India," World Development, Elsevier, vol. 146(C).
    10. Trisha Mukhopadhyay & Dhiraj Singha & Anupam Yadav & Nemthianngai Guite & Sanghmitra S. Acharya, 2025. "Access to Healthcare services among the Elderly in India: Evidence from LASI 2017-18," Journal of Population Research, Springer, vol. 42(4), pages 1-21, December.
    11. Chen Lin & Yuxin Chen & Jeongwen Chiang & Yufei Zhang, 2021. "Do “Little Emperors” Get More Than “Little Empresses”? Boy-Girl Gender Discrimination as Evidenced by Consumption Behavior of Chinese Households," Marketing Science, INFORMS, vol. 40(6), pages 1123-1146, November.
    12. Martin Abel & Daniel Buchman, 2024. "The Effect of Manager Gender and Performance Feedback: Experimental Evidence from India," Economic Development and Cultural Change, University of Chicago Press, vol. 73(1), pages 307-338.
    13. Momoe Makino, 2018. "Birth Order and Sibling Sex Composition Effects Among Surviving Children in India: Enrollment Status and Test Scores," The Developing Economies, Institute of Developing Economies, vol. 56(3), pages 157-196, September.
    14. Amita Majumder & Chayanika Mitra, 2017. "Gender Bias in Education in West Bengal," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 15(1), pages 173-196, March.
    15. S. Gupta & J. Singh, 2024. "Exploring gender disparity and economic growth in India: An ARDL approach," Journal of Economic Policy and Management Issues, JEPMI, vol. 3(2), pages 1-13.
    16. Chandan Jain, 2019. "Analysing Changes in Gender Difference in Learning in Rural India over Time," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 17(4), pages 913-935, December.
    17. Madhulika Khanna & Milan Thomas, 2024. "Gendered time poverty in three developing countries: An intra‐household analysis of children's time use," Journal of International Development, John Wiley & Sons, Ltd., vol. 36(1), pages 316-342, January.
    18. repec:ags:aaea22:335745 is not listed on IDEAS
    19. Mancini, Giulia, 2020. "Breadwinner, bread maker. Gender division of labor and intrahousehold inequality in 1930s rural Italy," MPRA Paper 102142, University Library of Munich, Germany.
    20. Majilla, Tanmoy, 2025. "Shadow education, intra-household financial resource allocation, and educational achievements," Journal of Economic Behavior & Organization, Elsevier, vol. 233(C).
    21. Zimmermann, Laura V, 2012. "Remember When It Rained: The Elusiveness of Gender Discrimination in Indian School Enrollment," IZA Discussion Papers 6833, Institute of Labor Economics (IZA).
    22. Swati Dutta, 2015. "Identifying Single or Multiple Poverty Trap: An Application to Indian Household Panel Data," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 120(1), pages 157-179, January.
    23. Klaus Prettner & Holger Strulik, 2017. "Gender equity and the escape from poverty," Oxford Economic Papers, Oxford University Press, vol. 69(1), pages 55-74.
    24. Maldonado, Javier, 2019. "Detecting Gender Discrimination in Intrahousehold Resource Allocation," DES - Working Papers. Statistics and Econometrics. WS 28146, Universidad Carlos III de Madrid. Departamento de Estadística.

    More about this item

    JEL classification:

    • I24 - Health, Education, and Welfare - - Education - - - Education and Inequality
    • I25 - Health, Education, and Welfare - - Education - - - Education and Economic Development
    • J16 - Labor and Demographic Economics - - Demographic Economics - - - Economics of Gender; Non-labor Discrimination
    • O15 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Economic Development: Human Resources; Human Development; Income Distribution; Migration

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