Doctoral Dissertation Research in Economics: Measuring the Elasticity of Nutrition Among Mothers of Young Children

Cornell University, Ithaca NY

Investigators

Abstract

Understanding how food purchasing behaviors by low-income households change in response to shocks in prices or income is crucial for the design of policy to counter food insecurity and malnutrition. For rural households with young children, these shocks are becoming increasingly important as incomes and prices change unpredictably due to pandemics, wars, and climates change. This research builds on an on-going field experiment to study how responsive food preferences are to changes in price and income among women with young children and how outside information on nutrition alters these preferences. The focus is on understanding whether providing nutritional information in addition to income support leads to better nutritional choices than providing income support alone. The results of this research will improve the design of social protection programs, such as the bundle of services to provide, and the optimal size of support. Besides helping researchers to model the economic impacts of adverse shocks, the results will also help improve the efficiency of social support programs, thus improving the wellbeing of low-income people as well reducing the fiscal burden of such programs. The results could also help establish the US as the global leader in social support programs. Estimating unbiased price and income elasticities of nutrient consumption in low-income rural settings is difficult, even though these are critical to the efficient design social support programs. This DDRIG exploits random variation in expenditure in an on-going RCT that randomly assigns households with younger children to receive cash transfers of various amounts. The project design allows the PIs to also test whether providing nutritional information in addition to income support improves nutritional outcomes relative to only income support. The PIs supplement this expenditure variation with a set of willingness-to-pay experiments during a lean-season household survey. With random variation in multiple dimensions, the PIs instrument for prices and income and estimate an Almost Ideal Demand System to obtain a complete picture of household preferences for foods and micronutrients. The results of this research will improve the design of social protection programs, such as the bundle of services to provide, as well as the optimal size of support. Besides illuminating the modelling of economic impacts of adverse shocks, the results of this research will also help improve the efficiency of social support programs, thus improving the wellbeing of low-income people as well reducing the fiscal burden of such programs. The results could also help establish the US as the global leader in social support programs. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.