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A simplified measure of nutritional empowerment: Using machine learning to abbreviate the Women’s Empowerment in Nutrition Index (WENI)

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  • Saha, Shree
  • Narayanan, Sudha
Abstract
Measuring empowerment is both complicated and time consuming. A number of recent efforts have focused on how to better measure this complex multidimensional concept such that it is easy to implement. In this paper, we use machine learning techniques, specifically LASSO, using survey data from five Indian states to abbreviate a recently developed measure of nutritional empowerment, the Women’s Empowerment in Nutrition Index (WENI) that has 33 distinct indicators. Our preferred Abridged Women’s Empowerment in Nutrition Index (A-WENI) consists of 20 indicators. We validate the A-WENI via a field survey from a new context, the western Indian state of Maharashtra. We find that the 20-indicator A-WENI is both capable of reproducing well the empowerment scores and status generated by the 33-indicator WENI and predicting nutritional outcomes such as BMI and dietary diversity. Using this index, we find that in our Maharashtra sample, on average, only 35.9% of mothers of children under the age of 5 years are nutritionally empowered, whereas 77.2% of their spouses are nutritionally empowered. We also find that only 14.6% of the elderly women are nutritionally empowered. These estimates are broadly consistent with those based on the 33-indicator WENI. The A-WENI will reduce the time burden on respondents and can be incorporated in any general purpose survey conducted in rural contexts. Many of the indicators in A-WENI are often collected routinely in contemporary household surveys. Hence, capturing nutritional empowerment does not entail significant additional burden. Developing A-WENI can thus aid in an expansion of efforts to measure nutritional empowerment; this is key to understanding better the barriers and challenges women face and help identify ways in which women can improve their nutritional well-being in meaningful ways.

Suggested Citation

  • Saha, Shree & Narayanan, Sudha, 2022. "A simplified measure of nutritional empowerment: Using machine learning to abbreviate the Women’s Empowerment in Nutrition Index (WENI)," World Development, Elsevier, vol. 154(C).
    • Handle: RePEc:eee:wdevel:v:154:y:2022:i:c:s0305750x2200050x
    DOI: 10.1016/j.worlddev.2022.105860
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    1. Achim Ahrens & Christian B. Hansen & Mark E. Schaffer, 2020. "lassopack: Model selection and prediction with regularized regression in Stata," Stata Journal, StataCorp LP, vol. 20(1), pages 176-235, March.
    2. Alkire, Sabina & Foster, James & Seth, Suman & Santos, Maria Emma & Roche, Jose Manuel & Ballon, Paola, 2015. "Multidimensional Poverty Measurement and Analysis," OUP Catalogue, Oxford University Press, number 9780199689491.
    3. Solava Ibrahim & Sabina Alkire, 2007. "Agency and Empowerment: A Proposal for Internationally Comparable Indicators," Oxford Development Studies, Taylor & Francis Journals, vol. 35(4), pages 379-403.
    4. Robin A. Richardson, 2018. "Measuring Women’s Empowerment: A Critical Review of Current Practices and Recommendations for Researchers," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 137(2), pages 539-557, June.
    5. Sabina Alkire, James E. Foster, Suman Seth, Maria Emma Santos, Jose M. Roche and Paola Ballon, 2015. "Multidimensional Poverty Measurement and Analysis: Chapter 9 - Distribution and Dynamics," OPHI Working Papers ophiwp090_ch9.pdf, Queen Elizabeth House, University of Oxford.
    6. Sabina Alkire, James E. Foster, Suman Seth, Maria Emma Santos, José M. Roche and Paola Ballon, 2015. "Multidimensional Poverty Measurement and Analysis: Chapter 7 - Data and Analysis," OPHI Working Papers ophiwp088_ch7.pdf, Queen Elizabeth House, University of Oxford.
    7. Saha, Shree & Narayanan, Sudha, 2022. "A simplified measure of nutritional empowerment: Using machine learning to abbreviate the Women’s Empowerment in Nutrition Index (WENI)," World Development, Elsevier, vol. 154(C).
    8. Jayachandran, Seema & Biradavolu, Monica & Cooper, Jan, 2021. "Using machine learning and qualitative interviews to design a five-question women's agency index," CEPR Discussion Papers 15961, C.E.P.R. Discussion Papers.
    9. Sabina Alkire & James E. Foster & Suman Seth & Maria Emma Santos & Jose M. Roche & Paola Ballon, 2015. "Multidimensional Poverty Measurement and Analysis: Chapter 2 - The Framework," OPHI Working Papers 83, Queen Elizabeth House, University of Oxford.
    10. Yount, Kathryn M. & Cheong, Yuk Fai & Maxwell, Lauren & Heckert, Jessica & Martinez, Elena M. & Seymour, Gregory, 2019. "Measurement properties of the Project-Level Women’s Empowerment in Agriculture Index," IFPRI discussion papers 1798, International Food Policy Research Institute (IFPRI).
    11. Esther Duflo, 2012. "Women Empowerment and Economic Development," Journal of Economic Literature, American Economic Association, vol. 50(4), pages 1051-1079, December.
    12. Lentz, E.C. & Michelson, H. & Baylis, K. & Zhou, Y., 2019. "A data-driven approach improves food insecurity crisis prediction," World Development, Elsevier, vol. 122(C), pages 399-409.
    13. Pratley, Pierre, 2016. "Associations between quantitative measures of women's empowerment and access to care and health status for mothers and their children: A systematic review of evidence from the developing world," Social Science & Medicine, Elsevier, vol. 169(C), pages 119-131.
    14. Sabina Alkire & James E. Foster & Suman Seth & Maria Emma Santos & Jose M. Roche & Paola Ballon, 2015. "Multidimensional Poverty Measurement and Analysis: Chapter 9 - Distribution and Dynamics," OPHI Working Papers 90, Queen Elizabeth House, University of Oxford.
    15. Sabina Alkire, James E. Foster, Suman Seth, Maria Emma Santos, José M. Roche and Paola Ballon, 2015. "Multidimensional Poverty Measurement and Analysis: Chapter 2 - The Framework," OPHI Working Papers ophiwp083_ch2.pdf, Queen Elizabeth House, University of Oxford.
    16. Sabina Alkire & James E. Foster & Suman Seth & Maria Emma Santos & Jose M. Roche & Paola Ballon, 2015. "Multidimensional Poverty Measurement and Analysis: Chapter 7 - Data and Analysis," OPHI Working Papers 88, Queen Elizabeth House, University of Oxford.
    17. Linden McBride & Austin Nichols, 2018. "Retooling Poverty Targeting Using Out-of-Sample Validation and Machine Learning," The World Bank Economic Review, World Bank, vol. 32(3), pages 531-550.
    18. Alsop, Ruth & Heinsohn, Nina, 2005. "Measuring empowerment in practice: structuring analysis and framing indicators," Policy Research Working Paper Series 3510, The World Bank.
    19. Narayanan, Sudha & Lentz, Erin & Fontana, Marzia & De, Anuradha & Kulkarni, Bharati, 2019. "Developing the Women's Empowerment in Nutrition Index in Two States of India," Food Policy, Elsevier, vol. 89(C).
    20. Naila Kabeer, 1999. "Resources, Agency, Achievements: Reflections on the Measurement of Women's Empowerment," Development and Change, International Institute of Social Studies, vol. 30(3), pages 435-464, July.
    21. Malapit, Hazel J. & Quisumbing, Agnes R. & Meinzen-Dick, Ruth Suseela & Seymour, Gregory & Martinez, Elena M. & Heckert, Jessica & Rubin, Deborah & Vaz, Ana & Yount, Kathryn M., 2019. "Development of the project-level Women’s Empowerment in Agriculture Index (pro-WEAI)," IFPRI discussion papers 1796, International Food Policy Research Institute (IFPRI).
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    Cited by:

    1. Saha, Shree & Narayanan, Sudha, 2022. "A simplified measure of nutritional empowerment: Using machine learning to abbreviate the Women’s Empowerment in Nutrition Index (WENI)," World Development, Elsevier, vol. 154(C).
    2. Galvin, Lauren & Verissimo, Cristiana K. & Ambikapathi, Ramya & Gunaratna, Nilupa S. & Rudnicka, Paula & Sunseri, Amy & Jeong, Joshua & O'Malley, Savannah Froese & Yousafzai, Aisha K. & Sando, Mary Mw, 2023. "Effects of engaging fathers and bundling nutrition and parenting interventions on household gender equality and women's empowerment in rural Tanzania: Results from EFFECTS, a five-arm cluster-randomiz," Social Science & Medicine, Elsevier, vol. 324(C).

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    More about this item

    Keywords

    Empowerment; Nutrition; Machine learning; LASSO; Gender; India; South Asia;
    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
    • I00 - Health, Education, and Welfare - - General - - - General
    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis

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