United States environmental agencies monitor ambient fine particulate matter (i.e., PM2.5). These activities are limited by sparse network coverage and no indoor monitoring. This leaves the public without full knowledge of exposures. Emergent nonregulatory air quality monitoring networks (NAQMNs) comprised of low-cost PM2.5 sensors can address uncertain exposures and facilitate health-protective decision-making. My dissertation assesses social disparities in Salt Lake County (SLCo), Utah’s NAQMN and sensor use among families impacted by asthma and is oriented by an environmental justice (EJ) perspective emphasizing the disproportionate environmental burdens experienced by disadvantaged groups. Chapter 2 investigates how social inequalities in access to sensors in SLCo census tracts vary based on the purchaser (i.e., university versus private). Results show that higher-income and more polluted tracts have increased sensors per resident. Findings related to income attenuate when predicting university-purchased sensors versus privately-purchased sensors per capita. Tracts with greater Hispanic/Latino/a immigrant populations have increased access to university-purchased sensors. Tracts with greater Asian composition are underserved by the NAQMN regardless of purchaser. Then, I deployed PM2.5 sensors to families impacted by asthma to examine how participatory sensing influenced their exposure experiences. Chapter 3 results reveal ecosocial histories, senses, and health effects shaped parents’ outdoor PM2.5 perceptions and engagement with sensors. Indoors, parents uncovered seemingly invisible PM2.5 while cooking but remained confused about exposure-related health impacts. Further, parents deemed the indoor sensor an effective tool while observing outdoor sensor readings less frequently. Income was not associated with identifying PM2.5, but lower-income parents preferred the indoor sensor, while higher-income parents were more likely to observe patterns in outdoor sensor readings. Chapter 4 results indicate lower-income households were exposed to greater PM2.5 than higher-income households. Income was associated with parents’ ability to engage in responsive actions (to mitigate exposures and protect health). Lower-income families had less engagement with indoor and outdoor responsive actions than higherincome households. Checking sensor readings elicited emotional reactions among parents. The results of this dissertation have EJ implications related to an uneven distribution of NAQMN sensors, potentially overlooked exposures to ambient PM2.5 pollution, and a cumulative burden on lower-income households regarding exposures and responsive actions.

The COVID-19 pandemic spurred major, and possibly enduring, changes in paid work. In this chapter, we explore the continuity and change in several work day dimensions, including where it is performed, the amount of time spent working, the length of the work day, and who people are with when they work, as well as variation across population subgroups. We use nationally representative data from the American Time Use Survey (ATUS) to analyze change across the 2019 to 2021 period. While the shift to working primarily at home in 2020 is dramatic and continuing into 2021, working primarily at the workplace remains the modal experience for Americans. We find differences by gender, education, parental status, and age in which workers perform their jobs at home, and we find much more continuity in how much people work and when they work.

I investigate the systemic problem of economic externalities from multiple angles with the goal of improving the way that we formulate, quantify, evaluate, and advance economic welfare and environmental sustainability.Externalities are costs (or benefits) that result from economic activities and transactions which are not paid (received)1 by those directly involved. Some aspect of the cost or harm is external to the direct parties, which means that the market price is lower than it would otherwise be, with some part being ‘paid’ by others, usually in the form of some harm suffered. An example is air or water pollution caused by a factory: the firm has direct costs (materials, equipment, infrastructure, labour etc) which it, and potentially its customers, pay, but downwind and downstream communities suffer negative health and quality of life impacts that are not part of the costs paid by the producer or the consumer.Externalities undermine the theoretical optimum and welfare maximizing function of competitive markets, fundamentally skewing outcomes and causing major harm as a result of economic activity. Without accounting for externalities, the profit maximising and cost minimising impetus of markets guarantees harm, because it is always cheaper to undertake activities wherein some of the costs are not paid by the firm, while the revenues are realised directly. Issues of sustainability can be understood as negative externalities that impact the welfare of people in the future (Brundtland 1987).In my investigations, I generate novel analyses and tools for explaining, quantifying, and evaluating externalities. I complete assessments and analyses of the Genuine Progress Indicator (GPI) for California and the United States, and suggest improvements to its methodologies. The GPI is a macroeconomic indicator that incorporates assessments of a number of significant externalities in order to construct a more comprehensive measure of welfare. I produce a cross-sectional analysis of the Ecological Footprint (EF) efficiency in national welfare provision. EF measures the anthropogenic draw on renewable biological resources, the externality of unsustainable impact on natural resources. Finally, as a foundation for ongoing work examining externalities and related policy questions, I build an open source and free software package, MPSGE.jl, that facilitates easier Computer General Equilibrium (CGE) modelling. The equilibrium framework of CGE models lends itself to applications accounting for externalities, such as the imposition of Pigouvian taxes2.1 While there are both negative and positive externalities, in general I will default to the negative case for discussion throughout for readability, unless explicitly described otherwise. 2 Pigouvian taxes and subsidies (Pigou 1920) imposed and provided by the government, can adjust market prices to incorporate the externality cost, to more fully reflect and optimise social welfare.My GPI work, presented in Chapters 1 and 2, includes calculating and analysing the GPI of California and the United States in order to measure truer social welfare over time, while I also analyse the indicator and its strengths and weaknesses.In Chapter 1, we estimate the GPI for California for a five-year period, 2010-2014. Within this relatively short time period, which includes the recovery from the Great Recession, we examine how inequality, nonmarket activities, and environmental degradation, affects the GPI of California. We also evaluate our estimation of the California GPI (CA-GPI) in two specific ways. First, we compare California’s GPI to an alternative indicator of social welfare, the Human Development Index (HDI) for California. Our comparison points to the GPI as a more holistic measure of sustainable economic well-being, although the HDI is useful in evaluating educational attainment, life expectancy, or earnings across regions or demographic groups in the state. Second, we compare our estimation of CA-GPI to the California results from a GPI estimation for all fifty states for 2011, and evaluate how different methodological decisions and data selection affect the results. Comparison of the two GPI assessments shows how the use of region-specific data compared to scaled national data increases the accuracy of estimates. However, using data and methods that prioritizes standardization is essential for comparing the GPI across regions, though the trade-off is diminished regional accuracy. The chapter concludes with a discussion of the uses of the GPI to evaluate policies, and suggests fruitful steps forward. Chapter 2 argues that important improvements in the Genuine Progress Indicator can be made by directly calculating the loss of natural resources, the benefits of leisure, and adjusting for inequality using a global norm, rather than using local, historical benchmarks. Local benchmarking is an obstacle to the standardisation and comparability of the GPI. We provide alternative methods for the five components that have used benchmarking in the standard GPI. We present new empirical estimates for the GPI of the United States and California over the period 1995 through 2017, calculated with and without the alternative methods. Using the alternative methods, we show that some differences between the GPI of the U.S. and CA are artefacts of the benchmark methods. Implementing the alternative methods narrows the gap between the U.S. and CA GPI, as it reduces the U.S. environmental costs, and removes the artificial differential between the U.S. and CA in the cost of inequality. We find that the GPI provides insight into net welfare not reflected in GDP, both with and without the benchmarking methods. Overall, we suggest that the GPI can be significantly improved with these high priority revisions without changing the fundamental approach or theoretical framework.In Chapter 3, I present a novel data analysis and visualization that combines indicators of different of national welfare in conjunction with each country’s associated Ecological Footprint, generating a measure of Ecological Footprint Efficiency, that is, the efficiency in providing economic services while minimizing the externality of ecological impact. The Ecological Footprint (EF) measures humanity’s draw on renewable biological resources. I use a specific set of data from a model which tracks the EF through the global supply chain to seven categories of final consumption. Using that EF data enables a direct association with selected data from the Sustainable Development Goals Indicator (SDGI) tracking the quality of the welfare benefits, under each of the seven categories.In Chapter 4, I detail my research contribution in developing MPSGE.jl, a novel, open-source software platform to facilitate simpler, error-reducing, fast, and free Computable General Equilibrium (CGE) modelling. The package is an evolution of the Mathematical Programming System for General Equilibrium analysis (MPSGE, Rutherford 1987) in the open-source Julia programming language. MPSGE.jl provides free and open-source access to the succinct-form model-construction functionality of its predecessor, and provides additional features such as an algebraic print of the model equations and easy integration with the growing ecosystem of other packages in the Julia programming language. I describe the package’s structure and use, and illustrate its benefits as part of a general-use and increasingly popular scientific programming language with an application. I use Monte Carlo methods to perform sensitivity analyses on a variety of parameters within a national model of the United States, and generate visualisations of the results with a standard plotting package.

We examine how the availability of prescription opioids affects labor market activity and household economic well-being. While greater access to opioids may lead people to substance use disorders and negative economic consequences, appropriate pain medication may allow some individuals to effectively participate in the labor market. We study prescription drug monitoring programs (PDMPs), which were designed to curb inappropriate opioid prescribing and assess how these policies affected labor force attachment and credit outcomes. We use variation across states in the timing of implementation of PDMPs and recent methods developed for difference-in-difference event study designs with multiple time periods. In line with previous work, we find that PDMPs lead to a decline in opioid prescribing rates. Although we find that these reductions in opioid supply have no clear effect on measures of labor force activity in our pooled sample, we see some suggestive evidence of negative effects on labor force attachment in states where there is less scope for substitution to illicit drugs. We also show that PDMPs lead to a decline in credit scores and increases in the number and amount of third-party debt collections, and that these effects are more pronounced in states lacking an illicit market. These findings suggest that some individuals are likely negatively affected by the lack of access to pain medication due to the PDMP laws.

The U.S. technological and economic boom of the 1990s generally resulted in decreased poverty yet left some areas of the country behind. Since then, policymakers have sought to eliminate concentrated poverty nationwide. The latest attempt to eradicate spatial poverty in the U.S. – tax incentives for private investment – was adopted in 2018. While research into this new program is sparse, other place-based policy research aimed at eradicating poverty is mixed. This study seeks to expand on existing research into this program by using a unique data source and model specification. Using six five-year estimates for 42,160 census tracts between 2012 and 2021, this study employs a fixed effects approach, including a difference-in-differences supplement, to estimate the association between a census tract being designated as an Opportunity Zone and various economic indicators. It finds statistically modest but substantively mixed associations between Opportunity Zone designation and economic indicators that ultimately support arguments for and against place-based policies.

This paper examines the impact of the large structural shocks-automation and import competition-on voter turnout during US federal elections from 2000 to 2016. Although the negative income effect of both shocks is comparable, we find that political participation decreases significantly in counties more exposed to industrial robots. In contrast, the exposure to rising import competition does not reduce voter turnout. A survey experiment reveals that divergent beliefs about the effectiveness of government intervention drive this contrast. Our study highlights the role of beliefs in the political economy of technological change.

Parks serve an essential role in city life as many residents enjoy visiting and interacting with the outdoors on a regular basis. The open space, greenery, quietness, and lack of crowds can provide a wonderful contrast to the hustle and bustle of city life. To maximize the benefits that parks bring, public officials and stakeholders need to understand how park visitors interact with park elements as well as perceived accessibility and safety to manage and regulate city parks with best practices. This study helps explore how park preferences of residents of Columbia, Missouri correlate with the geographic accessibility of parks. Additionally, this study evaluates which park features that residents of Columbia, Missouri value the most and how preferences enhance or detract from park usage. To accomplish this, a mixed-methods approach utilizing a public survey and GIS software was employed to analyze how city residents perceive and interact with park features. The findings reveal key insights into how park features can elevate the usage of parks and better support public officials and stakeholders in ongoing efforts to overcome barriers of distance and accessibility for all residents of Columbia, Missouri.

This chapter takes advantage of new digitized information in order to deal with an old Bolivian historiographic debate: the effects of education reforms in Bolivia during the first half of the twentieth century. It does by offering new information on education outputs at the departmental and provincial level. The new quantitative evidence shows that literacy improvements were very heterogeneous from a regional, ethnic and gender perspective. After the liberal reforms enforced during the first years of the twentieth century, educational indicators improved significantly in the departments of La Paz and Oruro and among non-indigenous (both men and women) and Aymara men. By contrast, education changes in departments such as Chuquisaca and among Quechuas (both men and women) did not show a significant dynamism until the 1930s. The opposite trajectories of Aymaras and Quechuas (the two most important indigenous groups in Bolivia) calls for further research in order to identify the mediating factors between ethnic diversity and public goods provision.

While the effect of credit on having a financial crisis is well-studied, its impact on recovering from the crisis is unresolved. This paper establishes the causal effect of loan supply shocks on the real economy using newly-collected archival data and a novel empirical strategy. The Bank of America was only bank large and geographically diversified enough to weather the Great Depression without shutting lending down completely did not select into better performing cities before the Depression. I find that cities with access to more stable lending from 1929 to 1933 had smaller contractions in economic activity in the same period. While cities with relatively little credit access during the 1930's did not recover to 1929 levels until 1940, Bank of America branched-cities grew during the Depression. Confirming the city-level results, there is a credit availability wage premium in individual-level data, even when controlling for workers' pre-crisis characteristics. These increases in wages are driven by a reallocation towards nontradable employment at the expense of the agricultural sector.

This paper provides evidence that air-pollution-related health conditions change how households evaluate clean air and, as a result, incentivize them to relocate to locations with better air quality. The evidence implies that naive estimations of the adverse effect of air pollution on health are biased, as people sort on air quality differently depending on their health. I employ a spatial-equilibrium model in which households choose a county to live in based on county-level characteristics including air pollution. Using National Longitudinal Survey of Youth data, I create a panel tracking respondents’ respiratory health shocks and county-level location for over three decades. The estimates from a multinomial mixed logit model support the hypothesis that households move to cleaner-air locations after an adult is diagnosed with asthma. I find that households react more strongly to an asthma diagnosis for an adult than to a child's diagnosis. The estimated median increase in marginal willingness to pay for a one-unit reduction in Air Quality Index after a diagnosis of adult-onset asthma is $157–$830 (in constant 1982–84 dollars).

Women make up a disproportionate number of part-time workers. Compared to full-time work, part-time work is associated with lower wages, fewer benefits, fewer opportunities for job advancement, and less work consistency and reliability. Women cite a number of reasons for working part-time, including lack of access to affordable child care. However, there is little research on whether child care affordability has a relationship with a woman’s decision to work part- or full-time. My study addresses this gap in the literature using Child Care and Development Fund (CCDF) expenditure data from the U.S. Department of Health and Human Services and individual-level employment data from the U.S. Census Bureau’s Current Population Survey Annual Social and Economic Supplement for years 2015-2019. I estimate the relationship between governmental child care subsidies and the probability that a low-incomeemployed-single-mother works part- or full-time. I find no statistically significant association between the CCDF subsidy and the probability of full-time vs. part-time work. This finding is consistent across sensitivity analyses controlling for an individual’s race, age, education, family size, children’s age, disability and health status, as well as a state’s economic characteristics. It is also consistent among sensitivity analyses focused on women below 100% and 200% of the Federal Poverty Line and that define full-time work as at least 35 hours and at least 21 hours per week. Future research is needed to conclusively decide whether child care subsidies are an important tool for connecting women with the robust wages and benefits of full-time work.

Why does inequality vary across societies? We advance the hypothesis that in a market economy, where earning differentials reflect variations in productive traits among individuals, a significant component of the differences in inequality across societies can be attributed to variation in societal interpersonal diversity, shaped by the prehistorical out-of-Africa migration. Exploring the roots of inequality within the US population, we find supporting evidence for our hypothesis: variation in the inequality across groups of individuals originating from different ancestral backgrounds can be traced to the degree of diversity of their ancestral populations. This effect is sizable: a move from the lowest to the highest level of diversity in the sample is associated with an increase in the Gini index from the median to the 75th percentile of the inequality distribution.

Introduction Although structural racism is strongly related to racial health disparities, we are not aware of any composite, multidimensional measure of structural racism at the city level in the United States. However, many of the policies, programs, and institutions that create and maintain structural racism are located at the city level. To expand upon previous research, this paper uses a novel measure to measure structural racism at the city level for the non-Hispanic Black population. Methods We used confrmatory factor analysis to model the latent construct of structural racism for 776 U.S. cities. The model included six indicators across fve dimensions: racial segregation, incarceration, educational attainment, employment, and economic status. We generated factor scores that weighted the indicators in order to produce the best model ft. The resulting factor scores represented the level of structural racism in each city. We demonstrated the utility of this measure by demonstrating its strong correlation with Black-White disparities in frearm homicide rates. Results There were profound diferences in the magnitude of structural racism across cities. There were also striking diferences in the magnitude of the racial disparity in frearm homicide across cities. Structural racism was a signifcant predictor of the magnitude of these racial disparities in frearm homicide. Each one standard deviation increase in the structural racism factor score increased the frearm homicide rate ratio by a factor of approximately 1.2 (95% confdence interval, 1.1-1.3). Conclusions These new measures can be utilized by researchers to relate structural racism to racial health disparities at the city level.

One of the economic development objectives of tax increment financing (TIF) is to increase business entries and decrease exits in designated areas. The authors use data on sales and use tax permit registrations in Iowa for two of the largest counties, Johnson and Polk, during the period 1990 through 2017 to estimate the effects of TIF on business establishments, entries, and exits. Using an event-study design, the analysis of pooled data suggests that TIF has no significant effect on total establishments or business entries, and significantly reduces business exits. TIF seems to increase establishments in Johnson County and to reduce business exits in Polk County. Of the industries examined, retail stands to benefit the most from TIF. The authors also find limited evidence of spatial spillover effects of TIF.

This paper investigates the short-run impact of the U.S. trade wars of 2018-19 on socioeconomic outcomes in the United States. Using monthly data from 2016 to 2019, we exploit the variation in the agricultural and manufacturing production levels of counties, and present evidence that counties that were exposed to higher levels of agricultural production in the pre-trade war shock period, exhibit higher levels of crimes, especially property crimes. Thus, we provide linkages between economic shocks and socioeconomic outcomes and show that trade shocks have such indirect distributional impacts even in the short-run.

Recent advances in sociological appreciation of risk have culminated in the concept of riskscapes, which describe how the social, political, biophysical, and technological drivers of risk are embedded within different spaces in ways that can reinforce systemic inequities. The U.S. military has long been recognized as an important structural and institutional contributor to environmental problems and therefore potentially riskscapes. However, the regional environmental injustice consequences of military presence have received little attention. To address this need, here we construct a regionalized military riskscapes modeling strategy that focuses on understanding environmental riskscapes across regional contexts. Using multilevel models with random intercepts, our exploratory analysis reveals differences in racial and ethnic environmental health exposure associated with proximity to military facilities across the 10 administrative regions used by the United States Environmental Protection Agency. Furthermore, we find that the relative contributions to local air pollution profiles arising from military and non-military sources likely differ by region, as do consequent environmental justice concerns. For example, in the Midwest, Central Mountain, and West/Southwest regions neighborhoods with more Latinx residents experience intensified air pollution inequalities associated with proximity to military installations. Neighborhoods with more Black residents in the Midwest reported greater environmental health risk from air toxics associated with nearby military facilities. These results underscore the usefulness of viewing the environmental consequences of domestic military facilities and their activities as regionally specific and spatially contingent. We further suggest that scholars studying environmental inequalities relating to military and other sources of pollution should consider how regional processes contextualize the existence and persistence of environmental injustice.

Hispanics in the United States tend to have lower household income, education, and health insurance coverage when compared to non-Hispanic Whites. Despite these economic disadvantages, paradoxically, Hispanics have displayed an equality with or even advantages over other minority groups and non-Hispanic Whites across a wide range of health outcomes. For example, in 2019, the Hispanic population had a life expectancy advantage of 3.0 years over the non-Hispanic White population and 7.1 years relative to the non-Hispanic Black population, despite having real household income that was 26 percent lower than non-Hispanic White households (Wilson 2020). Hispanic immigrants have also shown lower infant mortality rates and prevalence of mental illnesses. These stylized facts are collectively known as the “Hispanic health paradox.” This essay will provide an overview of the Hispanic health paradox literature. We will document different instances of the Hispanic health paradox across various measures: life expectancy at birth, infant mortality rate, death rates, causes of death, and morbidity. We will discuss the leading explanations of the Hispanic health paradox and possible ways for economists to contribute to this discussion. The origin of the Hispanic health paradox is often traced to the seminal paper by Markides and Hazuda (1980), in which the outperformance of Hispanics was deemed an “epidemiological paradox.” The authors found that Mexican Americans in southwest Texas had a lower infant mortality rate relative to other groups, including non-Hispanic Whites. Markides and Coreil (1986) reported the same phenomenon for life expectancy, mortality, disease-related health outcomes, and mental and functional health. In fact, the first Hispanic health advantage reported was observed for mental health among Mexican Americans (Karno and Edgerton 1969). Markides and Eschbach (2005) renamed these advantages the Hispanic paradox. In their discussion, they highlight the role of immigration in explaining the paradox, with the initial assumption that immigrants need to be healthy enough to endure the cost associated with immigration: travel, adaptation to new customs, new laws, and potentially with few resources or support available. The Hispanic health paradox is closely tied to the “healthy immigrant effect” (also known as the “healthy immigrant paradox”). The healthy immigrant effect is an observed time path in which the health of immigrants just after the migration is substantially better than that of comparable native-born people, but worsens with additional years in the new country. Stephen et al. (1994) were the first to identify this effect using the 1989 National Health Interview Survey, because this was the first time the survey incorporated the number of years lived in the country. Since then, various authors have identified this effect across numerous health outcomes (Ali 2002; Goel et al. 2004; Kennedy et al. 2015; McDonald and Kennedy 2004; Puyat 2013; Wu and Schimmele 2005; Jasso et al. 2005; Roger et al. 2011; Constant et al. 2018). A vast majority of the Hispanic health paradox literature has treated Hispanics in the United States as a monolithic group.1 Leading explanations of the Hispanic health paradox can be different due to backgrounds and characteristics. To that end, whenever possible, we disaggregate our findings by nativity and ancestry.

We document large differences among regions of the United States in the trends of the black/white earnings gap among full-time workers from 1976 to 2017. Outside the South, the earnings of black workers grew more slowly than those of non-Hispanic white workers. These relative decreases were much larger for women than for men. However, in the South, the racial earnings gap shrank for men, and changed little for women. Thus, we find a substantial convergence across regions in the black/white earnings gap. The most important explanations of the racial earnings gaps are persistent racial differences in educational attainment and persistent occupational segregation. However, differences in observables leave much of the racial earnings gaps unexplained. The regional convergence in the racial earnings gap is evident in both explained and unexplained gaps for both women and men.

At least half of the world population is bilingual, but lifetime financial gains from early exposure to multiple languages are largely unknown. In this study, we analyze individual earnings of bilinguals in the US using 15 years of Census data and an augmented wage model, accounting for cognitive, manual, and interpersonal skills derived from O*NET job task descriptors via sparse principal component method. Using unconditional quantile regression, we find evidence that language skills mostly benefit individuals at the lower end of the earnings distribution. While our analysis does not establish causality, it underscores the potential of early language acquisition to mitigate income inequality by enhancing the employment prospects of low-income individuals. We also highlight the favorable cost-benefit ratio of language acquisition in childhood, when learners face no monetary opportunity costs and can achieve greater levels of fluency.

This dissertation contains three essays on the topics of job search and labor markets. The first essay studies effects of occupational credentials on unemployment duration. Using a random search model we theorize that occupational credentials in the form of licenses and certificates reduce unemployment duration through improvements in human capital, provision of better signalling, or both. Whichever credential has the stronger effect remains an empirical question. Since the questions about occupational credentials have recently been added to large population surveys in the US, the topic is relatively nascent; and we find that certificates issued by businesses as well as licenses decrease unemployment duration while the former has the stronger effect that the latter. The second and third essays study effects of immigration and linguistic assimilation on growth in native employment. The second essay studies those effects in the context of five European countries whereas the third essay studies those effects in the US case. The second essay derives a search and matching model to demonstrate that immigrants having higher search costs than natives, join the host country economy and boost native employment, accepting lower wages and driving firms’ costs down. The second essay also develops a novel index to measure linguistically assimilated and linguistically unassimilated areas using Google Trends search data whereas the third essay relies on self-reported data on linguistically isolated households. Findings from both essays are similar: inflows of new immigrants into linguistically assimilated areas increase growth in native employment. However, the second essay, with the exception of France, demonstrates that inflows into linguistically unassimilated areas do not show evidence of the effects in contrast to the case of the US. However, further applications of the index derived in the second essay to the case of the US will shed some light on the comparability of the results.