Three Essays on Money Input and Time Input in Food Poverty Measurement and Healthy Eating Index
| dc.contributor.author | Yang, Yanliang | en |
| dc.contributor.committeechair | Davis, George C. | en |
| dc.contributor.committeechair | You, Wen | en |
| dc.contributor.committeemember | Ge, Suqin | en |
| dc.contributor.committeemember | Sengupta, Srijan | en |
| dc.contributor.department | Agricultural and Applied Economics | en |
| dc.date.accessioned | 2019-07-19T08:01:26Z | en |
| dc.date.available | 2019-07-19T08:01:26Z | en |
| dc.date.issued | 2019-07-16 | en |
| dc.description.abstract | A healthy diet is related to a low risk of chronic diseases. A large body of research is devoted to improving social welfare by promoting healthy eating. This dissertation addresses the relation of food and health by analyzing the money and time inputs in food, the food poverty measurement, and a corresponding health outcome. The second chapter extends the current food poverty measure in headcount and proposes a set of Foster, Greer, and Thorbecke (FGT) indices, which is commonly used in development literature, in food poverty to allow for a more comprehensive understanding in food poverty evaluation. The counter-factual analysis on removing the American Recovery and Reinvestment Act (ARRA) component from the food expenditure shows that the original metrics underestimate the reduction to food expenditure poverty associated with ARRA, whereas the FGT indices indicate a slightly larger impact of ARRA in alleviating food poverty. The third chapter uses the same FGT indices in food poverty measurement but focuses on the sensitivity of these measurements to a different spatial and temporary food price. We use linear regression to estimate the local level of food poverty thresholds. The results show the spatial and temporal-specific thresholds are higher than the national threshold. The West region shows the most severe poverty situation, indicating the importance of considering spatial and temporal variations in measuring food expenditure poverty. The decompositions of food expenditures show that both the Supplemental Nutrition Assistance Program (SNAP) benefits and money spent on protein play an essential role in reducing food expenditure poverty. The fourth chapter combines the two datasets used in the previous two chapters to investigate the connection between the resources (money and time) devoted to food and a corresponding health outcome (Healthy Eating Index, HEI). Two-Sample-2-Stage-Least-Square (TS2SLS) model is used to account for the two different datasets in predicting the time spent on food-related activities. After obtaining the time input, a Three-Stage-Least-Square (3SLS) model shows the time input improves the HEI for Non-SNAP households, who are more constrained by time. The decomposition of the impact of education on the HEI shows the indirect impact account for 22% of the total impact. This analysis breaks down the impact of the characteristics on HEI through different channels, thus offers more comprehensive policy recommendations. | en |
| dc.description.abstractgeneral | A healthy diet is related to a low risk of chronic diseases. A large body of research is devoted to improving social welfare by promoting healthy eating. This dissertation is a series of studies on food and health regarding the money and time input on food, the food poverty measurement, and the corresponding health outcome. The second chapter extends the current food poverty measure in headcount and proposes a set of distributional metrics: depth and severity, which measures how far away households are away from the targeted threshold and how severe the food poverty is respectively. These distributional metrics allow for a more comprehensive understanding of food poverty evaluation. We also analyzed the change of the metrics when removing part of the food expenditure funding source. The analysis shows the original metrics tend to underestimate the reduction to food expenditure poverty and indicates a slightly larger impact of removed funding source in alleviating food poverty. The third chapter uses the same distributional food poverty metrics, but focuses on the sensitivity of these measurements to different spatial and temporal food prices. We use linear regression in estimating the local food poverty thresholds. The results show the spatial and temporal-specific thresholds are higher than the national threshold. The West region shows the most severe poverty situation, indicating the importance of considering spatial and temporal variations in measuring food expenditure poverty. The forth chapter combines the two datasets used in the previous two chapters to investigate the connection between the resources (money and time) spent on food and a corresponding health outcome. A special econometrics model is used to predict the time spent on food-related activities with two datasets. After obtaining the time input, a system of equations model shows the time input improves the healthy eating for households who are more constrained by time. The decomposition of the impact of education on healthy eating shows the indirect impact account for 22% of the total impact. This analysis breaks down the impact of the characteristics on HEI through different channels, thus offers more comprehensive policy recommendations. | en |
| dc.description.degree | Doctor of Philosophy | en |
| dc.format.medium | ETD | en |
| dc.identifier.other | vt_gsexam:19251 | en |
| dc.identifier.uri | http://hdl.handle.net/10919/91895 | en |
| dc.publisher | Virginia Tech | en |
| dc.rights | In Copyright | en |
| dc.rights.uri | http://rightsstatements.org/vocab/InC/1.0/ | en |
| dc.subject | Money Input | en |
| dc.subject | Time Input | en |
| dc.subject | Food Poverty Measurement | en |
| dc.subject | Healthy Eating Index | en |
| dc.title | Three Essays on Money Input and Time Input in Food Poverty Measurement and Healthy Eating Index | en |
| dc.type | Dissertation | en |
| thesis.degree.discipline | Economics, Agriculture and Life Sciences | en |
| thesis.degree.grantor | Virginia Polytechnic Institute and State University | en |
| thesis.degree.level | doctoral | en |
| thesis.degree.name | Doctor of Philosophy | en |
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