Author: Shree Saha, Sudha Narayanan
Title: A simplified measure of nutritional empowerment Using machine learning to abbreviate the Women’s Empowerment in Nutrition Index (WENI)
Abstract: Measuring empowerment is both complicated and time consuming. A number of recent ef- forts 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, us- ing 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 indi- cators. 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 west- ern Indian state of Maharashtra. We find that the 20-indicator A-WENI is both capable of reproducing well the empowerment 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 51.2% of mothers of children under the age of 5 years are nutritionally empowered, whereas 86.1% of their spouses are nutritionally empowered. We also find that only 22.3% 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 contempo- rary 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 nutri- tional 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.
Keywords: Empowerment, nutrition, machine learning, LASSO, gender, India, South Asia
JEL Code: J16, D63, I00, C55
Weblink: http://www.igidr.ac.in/pdf/publication/WP-2020-031.pdf
