Browsing by Author "Chen, Susan Elizabeth"

Now showing 1 - 7 of 7
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    Essays On Health Economics
    Pilehvari, Asal (Virginia Tech, 2021-02-10)
    This dissertation consists of three essays in Health Economics relating to the recent challenges in the U.S. The first essay studies the impact of retirement on subsequent health and investigates the mediation effect of social network in the relationship between retirement and health. Findings reveal that retirement adversely impacts physical and mental health outcomes and a considerable portion of these effects are explained by social network changes post-retirement. In particular, shrinkage in the size of social network post-retirement deteriorates physical health and increases depression in retirees. In the second essay, we assess the differential effect of social distancing on the daily growth rate of COVID-19 infections in the US counties by considering the spatial pattern of COVID-19 spread. We also conduct a comparative analysis of the effect on urban versus rural counties, as well as low versus high socially vulnerable counties. Our analysis illustrates that a high level of social distancing compliance is needed in urban counties and in socially vulnerable areas to achieve the largest impact at curve flattening, whereas moderate-compliance is enough in reaching the peak marginal impact in rural regions and counties with low social vulnerability. In the third essay, by combining multiple data sources, we investigate how racial disparities in access to healthcare contribute to the disparity in COVID-19 infections and mortality in black versus white sub-groups. The multilevel analysis demonstrates that a higher probability of having health insurance significantly reduces disparity in COVID-19 mortality in black sub-group while it has no impact on the disparity in whites.
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    Essays on Price and Time in Trade and Household Production
    Yang, Jinyang (Virginia Tech, 2022-07-13)
    This dissertation consists of three chapters that estimate the elasticities regarding price and time in trade and household production. Chapters 1 and 2 estimate price elasticities. Chapter 1 estimates the one-factor-one-price elasticity of substitution (OOES)—or how the percentage change in the quantity of one good responds to the percentage change in the price (of itself or another good)—in an international trade context. Chapter 2 estimates the two-factor-one-price elasticity of substitution (TOES)—or the difference of percentage changes between two quantities with respect to the percentage change in the price of one good—in the context of household food production. Chapter 3 estimates the elasticity of export quantity and value with respect to delays in the time it takes to load or unload products at US ports. Chapter 1 estimates the price elasticities in agricultural trade. Armington elasticities, the elasticity of substitution between goods from different countries, are key parameters in agricultural trade policy evaluation and welfare calculation. We estimate Armington elasticities for a selected basket of 38 agricultural commodities in 5 categories by compiling a sample of 118 countries' production and trade flows. Following and extending Feenstra et al. (2018), we estimate both the micro-elasticity of substitution between foreign sources of imports and the macro-elasticity of substitution between home and imported products at the commodity level. The median of the micro- and macro-elasticities are 6.4 and 5.0, respectively. Meat products have the lowest micro- and macro-elasticities, with the micro-elasticities ranging from 4.2 (pork) to 5.0 (poultry) and the macro-elasticities ranging from 2.9 (pork) to 4.5 (beef). Crops products have the widest range of Armington elasticities, with micro-elasticities ranging from 2.5 (pigeon peas) to 90.3 (peanuts), and macro-elasticities ranging from 1.2 (pigeon peas) to 20.1 (peanuts). In line with the literature, we find that 75 percent of the agricultural commodities have numerically smaller macro-elasticities than micro-elasticities, even though only 6 of them (pork, poultry, corn, peanuts, apples, and peppers) are statistically smaller at the 5 percent level. We explore the robustness of our estimates by slicing the sample into separate periods and importing countries. Finally, we discuss the policy implications of our estimates on predicting trade due to tariff changes and understanding welfare gains from agricultural trade. Chapter 2 estimates the goods-time elasticity of substitution (EOS), the responsiveness of the difference between money and time in household production for change of opportunity cost of time (OCT). This chapter bridges the gap between literature that directly and indirectly estimates the goods-time EOS in household production. Inspired by the studies in environmental economics, we argue the opportunity cost of time in household production not only depends on wage but life-cycle dynamics and household demographics as well. We proceed with the estimation by two strategies: direct estimation of the household production, and the demand-supply approach borrowed from Feenstra's (1994) research on trade elasticities. Both strategies report the estimates are much larger than unit and closer to previous indirect estimates. We show our results are robust when applied to Aguiar and Hurst's (2007) sample, in which they employed the indirect estimation. The larger goods-time EOS indicates policies aiding households with money for groceries like the Supplemental Nutrition Assistance Program (SNAP) are more sufficient, since money for certain groceries can more easily substitute for time in making meals. Chapter 3 explores the elasticity of trade with respect to port congestion time. U.S. ports have struggled with significant supply chain congestion during the past two years. Anecdotal evidence shows the increasing port congestion brought substantial losses to U.S. exports, particularly agricultural shipments. However, previous studies are limited by the availability of explicit data on congestion times for unloading. This study first quantifies the association between port congestion days and U.S. agricultural exports, using monthly export data of top U.S. ports and their monthly average container and bulk shipments delays. We find one extra day delay of container shipments decreases U.S. agricultural monthly exports by 5 percent in quantity or 2 percent in value on average. That amounts to $63 million in monthly loss of export value on average, and Western U.S. ports are responsible for 69 percent of this total. The effect is most pronounced for the Western U.S. exports of bulk commodities, where congestion results in a 9 percent loss in quantity or 8 percent loss in value. For Eastern U.S., the most salient effect is on consumer commodities, with a loss of 3 percent in quantity and 3 percent in value. For the Gulf region, the largest effect is on bulk commodities, with a loss of 4 percent in quantity and 5 percent in value. The impacts of congestion on bulk shipments are both statistically and economically insignificant. However, we find some evidence that exporters substitute bulk cargoes with containers when bulk shipment delays at ports increase. The substitution of container shipments with bulk shipments, however, is unlikely.
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    Essays on Social Capital and Peer Effects
    Jiang, He (Virginia Tech, 2022-06-03)
    In Chapter 2, I employ the educational production function to identify the different effects of making a friend of the same gender and the opposite gender in a school network. Unlike other gender peer effects literature that only quantifies the causal effects of the proportion of girls in an aggregated level, such as other students in the same class, grade, or dorm, I study the gender of the five best friends nominated by the student. I address the endogeneity of friendship composition by employing a novel set of instrumental variables for the number of same-gender and opposite-gender friends. We find that having more friends, especially in the early accumulation stage, lowers the test scores. We also explore the mechanisms. In Chapter 3, I investigate the role of social learning in enrollment decisions for a public pension scheme. All else equal, if a qualified rural resident moves from a community where no other co- villagers participate in the new pension scheme to a community that is fully covered by the pension scheme, the probability of an individual enrolling by 0.541 percentage point. We use robustness checks to illustrate that the estimated peer effects are not driven by the common unobserved factors, but by social interactions. In Chapter 4, we use the survey data on Chinese middle students and the instrumental variables method to explore the different effects of making friends with the same gender and the opposite gender in a school network on mental health. The empirical results find that having a larger number of same-gender friends improves mental health but having a larger number of opposite-gender friends hurts mental health.
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    Human Capital in Appalachia: An Analysis of Vulnerability, Resilience, and Skills in Preparation of a Greener Economy
    Pierce, Timothy Samuel (Virginia Tech, 2022-09-08)
    This thesis constructs a novel resilience index and a comparative advantage measure of professional skills to enhance our understanding of economic resilience in Appalachian counties that are vulnerable to the transition to a greener economy. The index-based results indicate that resilience is clustered throughout the region and strongly related to local labor market demand for the skills required to complete non-routine cognitive tasks. Resilient labor markets hold a comparative advantage over their less resilient counterparts in twelve skills. These skills are highly prevalent in growing and emerging occupations and strongly related to resilience in the existing literature on regional economic shocks. This thesis also develops a database that enables future researchers, policymakers, and industry leaders to geospatially analyze skill prevalence at a county level and make informed and proactive decisions in the face of a changing economy.
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    Land Use on the Urban Fringe
    Rippley, Samantha (Virginia Tech, 2023-06-30)
    Due to their location on the urban fringe, many historically agricultural counties face development pressure from a spreading urban core. These local communities must contend with often conflicting objectives of providing economic development opportunities while at the same time protecting their county's natural resources. Land conservation policies incentivize landowners to keep land identified as critical environmental resources in their natural state. In this project, we analyze property-level administrative data to evaluate whether land conservation policies and neighbor land use patterns affect the probability of land parcel development. We find some evidence of the contagion effect and that the county's acknowledgment of Priority Conservation areas impacts development motivation.
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    Tasks, Skills, and Jobs in the Green Economy
    Cheng, Yang (Virginia Tech, 2024-05-29)
    The Inflation Reduction Act has allocated over $369 billion to expedite the transition from fossil fuels to renewable energy. Along with these incentives, the funds support job training initiatives, like the recently introduced American Climate Corps. The transition to new energy forms will result in structural changes in the labor market and the demand for new and emerging skills, tasks, and jobs. A challenge, however, is that there are no existing definitions of what constitutes green jobs and skills, and thus, no clear consensus on the training workers will need for these jobs. This dissertation employs a data-driven approach using the Occupational Information Network to define and characterize green tasks, skills, and jobs. Using Natural Language Processing, we develop a method to quantify the "greenness'' of tasks and occupations. Utilizing this index, we explore the significant role of green skills during economic transitions. Our findings offer a comprehensive roadmap for understanding the evolution of green jobs and skills over the next decade. This dissertation comprises three chapters analyzing the tasks, skills, and jobs in the green economy. The first chapter investigates what constitutes green jobs and their characteristics. We construct "Task Greenness Scores" and "Occupational Green Potential" indices using Natural Language Processing and machine learning techniques to assess the greenness of tasks and overall occupations. Clustering methods categorize occupations based on task attributes -- green potential, frequency, importance, and relevance, identifying five distinct groups. This classification reveals significant variability in job greenness; although many jobs incorporate green tasks, only 113 occupations are definitively categorized as green. These are further divided into "High Green Intensity-Task Focus" and "High Green Intensity-Use Focus" groups, with the latter typically requiring less formal education and emphasizing manual skills over analytical or interactive skills. Our analysis also indicates a modest overall unconditional green wage premium of 3% for 2019 and 2020. The second chapter delineates green skills and maps their prevalence across the U.S., focusing on coal-mining communities in Appalachia. We sort a variety of skills into categories reflecting task and skill differences between green and non-green occupations, identified through O*NET. Principal Component Analysis helps categorize these into broader green skill groups such as "Technical Skills", "Management Skills", "Science Knowledge", and "Integrated Knowledge". The prevalence of green skills is notable in production-related occupations, suggesting essential technical expertise for the green economy. Interestingly, sectors traditionally viewed as energy-intensive also show a foundation conducive to green practices. Our findings highlight the necessity of tailored training programs that cater to diverse educational backgrounds, particularly emphasizing the lack of green skills in Appalachian regions, which may exacerbate inequalities during the economic transition. The third chapter examines the mediating role of green skills in local labor markets amidst the transition to a sustainable and energy-efficient economy. This chapter informs policy debates on large-scale green fiscal plans of the 2009 American Recovery and Reinvestment Act. We discover that regions well-prepared for environmental regulations or new energy development benefit from a robust stock of green skills. However, our analysis suggests that green ARRA investments are negatively correlated with wages and job creation, contrasting with positive correlations found in non-green ARRA investments. This chapter concludes that green skills significantly influence labor market outcomes, particularly in the manufacturing sector, and highlights the spillover effects of green stimulus on neighboring labor markets.
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    Three Essays in Labor Economics
    Nurmukhametov, Azat (Virginia Tech, 2024-08-06)
    This dissertation comprises three autonomous essays on topics in labor economics. The first chapter investigates the impact of socio-cultural, technological, and other transformative factors on employees' labor market decisions over recent decades, focusing specifically on the mobility of young workers in terms of job and occupation transitions. Data from the National Longitudinal Surveys of Youth (NLSY79 and NLSY97) indicate a marked increase in job mobility among young participants across different cohorts. Analysis of these datasets demonstrates that the influence of age on the likelihood of changing jobs has become more negative for the second cohort. This shift is primarily driven by changes in the impact of age for specific socio-demographic groups of respondents. Additionally, there is a notable between-cohort rise in the relationship between both upward and downward job transitions and occupational mobility. The second essay explores the consequences of the rise in industrial robot installations on shifts in population size and employment within local labor markets, which may be substantially affected by the rapid advancement of robotics technology in recent decades. The cross-sectional study reveals discernible gender disparities in the impacts of robot adoption. The effect of robotization on the labor force participation rate is negative for men and unmarried women yet positive for married women. As industrial robots are predominantly programmed to perform routine tasks in manufacturing industries traditionally associated with heavy manual male-dominated labor, the anticipated impact of robot exposure on employment in the manufacturing sector is predictably negative for male workers. For women, this effect is conversely positive. It was also found that robot penetration leads to an increase in the share of family income attributed to females within married-couple households. The extended cross-sectional analysis in the third chapter indicates that the impact of robotization on local labor markets is more negative for younger people. Fixed-effects models using panel data analysis reveal that robot adoption unexpectedly reduces migration but enhances labor force participation, opposing recent scholarly findings. Employing an alternative robot adoption variable that is based on technology adoption within individual industries and, therefore, can only be utilized to analyze employment-related dependent variables yields more robust and statistically significant results, indicating a negative impact of robot exposure on employment. Nevertheless, panel data analysis does not support the previous chapter's findings regarding gender differences in the impact of robot penetration. These discrepancies may be attributed to differences in the structure, methodology, and nature of cross-sectional versus panel data and the methodological differences in measuring robotization.