Abstract

India hosts the highest number of malnourished children in the world. Tackling this challenge requires urgent implementation of targeted policies. However, the current research is not clear on which specific interventions the policymakers should undertake to yield the biggest improvement in child malnutrition in India. Hence, our study aims to contribute to the existing literature by using a novel regression decomposition technique, called the Shapley–Owen decomposition which can estimate the relative contribution of the factors influencing malnutrition. Using the NFHS-4 data, we classify the drivers of child undernutrition (besides age and gender) into different groups, such as infections and medicines, birth characteristics, food intake, child’s environment, mother’s anthropometry, her characteristics, environment, and socio-economic factors. The decomposition informs us that the child’s age and the mother’s anthropometry are the most important determinants of child height and weight outcomes (respectively). This means that access to adequate nutritional provision during the early years of the child’s life is critical to reducing the burden of malnutrition in India. Further, targeting young girls as the beneficiaries of the welfare schemes will improve their anthropometry, which will ensure healthier children in the future. Given the rising challenge of malnutrition in India, there has been a push to enhance investment in a combination of interventions that ensure optimal food intake, its absorption, adequate sanitation, betterment of maternal nutrition as well as education and access to social safety nets. It is in this context that our study is among the first to provide rigorous econometric analysis to determine which among these is the most important. Hence, this guides policymakers to the specific sectors they could target to improve the nutritional well-being of children in India. JEL Codes: C01, D69, I15, I30, O20, P46

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