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

了解低收入家庭的食品购买行为如何随着价格或收入的冲击而变化，对于制定应对粮食不安全和营养不良的政策至关重要。对于有年幼子女的农村家庭来说，由于流行病、战争和气候变化导致收入和价格发生不可预测的变化，这些冲击变得越来越重要。这项研究建立在一项正在进行的实地实验的基础上，旨在研究有幼儿的妇女的食物偏好对价格和收入变化的反应，以及外界营养信息如何改变这些偏好。重点是了解在收入支持之外提供营养信息是否比单独提供收入支持能带来更好的营养选择。本研究的结果将改进社会保护计划的设计，如提供的一揽子服务和支持的最佳规模。除了帮助研究人员模拟不利冲击的经济影响外，研究结果还将有助于提高社会支持项目的效率，从而改善低收入人群的福祉，并减轻此类项目的财政负担。研究结果还有助于确立美国在社会支持项目方面的全球领导地位。估计低收入农村地区营养消费的无偏价格和收入弹性是困难的，尽管这些对有效设计社会支持计划至关重要。DDRIG利用正在进行的随机对照试验中支出的随机变化，随机分配有年幼子女的家庭接受不同数额的现金转移。项目设计还允许pi测试在收入支持之外提供营养信息是否比仅提供收入支持更能改善营养结果。在淡季家庭调查期间，pi通过一系列支付意愿实验来补充这种支出变化。在多个维度随机变化的情况下，PIs工具用于价格和收入，并估计一个几乎理想的需求系统，以获得家庭对食物和微量营养素偏好的完整图景。本研究的结果将改进社会保护计划的设计，如提供的一揽子服务，以及支持的最佳规模。除了阐明不利冲击的经济影响建模之外，本研究结果还将有助于提高社会支持计划的效率，从而改善低收入人群的福祉，并减轻此类计划的财政负担。研究结果还有助于确立美国在社会支持项目方面的全球领导地位。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

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.