Unmanaged stormwater flows can threaten life, property, and the natural environment. Already damaging and deadly, flooding will only worsen as seas rise. Local governments are critical players in the inter-governmental effort to manage flooding and sea level rise. To adapt, local governments must invest in their infrastructure systems based on the complex risks and uncertainties underlying both flooding and sea level rise. This dissertation studies local governments’ budgetary decision-making at the macro and micro scales through three empirical studies. The first study assesses local governments macro-budgeting decisions by modeling flood control investment based on the demand of the median voter. The first study tests if local governments invest in flood control infrastructure systems in response to either experienced damages, new information on their flood risks, or if they fail to invest in response to their risk at all. Results indicate that local governments decide to pursue flood control infrastructure in response to damages which they develop in response to new scientific information. The second study turns to the micro-level and investigates how local governments’ public works directors would prioritize assets at risk of failure if seas were to rise through a decision-making experiment. Applying cumulative prospect theory, the second study argued that public works directors should be decreasingly sensitive to increases in assets’ criticality and to changes in assets’ probability of failure as the probability of failure departs from impossibility or certainty. However, the results show that works directors tended to exhibit risk aversion because they were decreasingly sensitive to both increases in assets’ importance and probability of failure across the full range of failure probabilities. Finally, turning back to the macro-level, the third study developed cost-functions to test if systematic capital budgeting practices could improve local governments’ cost-efficiency by improving the decisions surrounding stormwater investments. However, the third study indicates that while environmental and scale factors drive costs, neither master plans nor asset inventories improve cost-efficiency. Overall, investing in flood control, stormwater management, and sea level rise resiliency can improve public safety and water quality but requires the commitment of public and elected officials.

Objectives We aimed to measure both stated and experimentally “revealed” abortion provision preferences among US people with capacity for pregnancy. Study design In July 2022, we recruited US residents assigned female sex at birth and aged 18 to 55 years using Prolific, an online survey hosting platform. We asked participants what first-trimester abortion method and delivery model they would prefer. We also assessed abortion care preferences with a discrete choice experiment, which examined the relative importance of the following care attributes: method, distance, wait time for appointment, delivery model (telehealth vs in-clinic), and cost. Results More than half of the 887 respondents (59%) self-reported a slight (22%) or strong (37%) preference for medication compared to aspiration abortion; 11% stated no preference. Our discrete choice experiment found that cost and wait time had a greater effect on hypothetical decision-making than did method and delivery model (discrete choice experiment average importances = 44.3 and 23.2, respectively, compared to 15.9 and 8.2, respectively). Simulations indicated that holding other attributes constant, respondents preferred medication to aspiration abortion and telehealth to in-clinic care. Conclusions This study, the first to examine abortion preferences in the United States, using a discrete choice experiment, demonstrates the importance of wait time and cost in abortion care decision-making. Our work indicates that for this population, factors related to health care financing and organization may matter more than clinical aspects of care. Implications Although people in this study preferred medication to aspiration abortion and telehealth to in-clinic care, wait time and cost of care played a greater role in care decision-making. Focusing solely on clinical aspects of care (i.e., method, delivery model) may ignore other attributes of care that are particularly important for potential patients.

This work examines power dynamics at play in the early child-saving movement as illuminated in the case records and annual reports of the Pennsylvania Society to Protect Children from Cruelty (SPCC) from 1878 to 1881 and triangulated with other historical records. 1 We draw on ecological systems theory and urban ecology to examine social and spatial relationships between child-saving institutions, communities, and individuals and families. The paper adapts template analysis for archival research as a replicable approach for studying historical power dynamics embedded in social welfare institutions. This approach highlights the changing role of community members in identifying and responding to neglect and abuse and uncovers common themes that continue to impact the modern child welfare system.

A dataset with the numbers of housing units for the 56 largest urban areas in 2020, going back to 1950, is used to examine the changes in their sizes. While all of the areas more than doubled in size, the growth of some was astounding, adding over 99 percent of their 2020 housing units since 1950. The differences in rates of growth produced significant changes to the list of the largest 15 areas, with six new areas added compared only one change in the previous four decades. The areas in the South grew most rapidly. In 1950, the large urban areas in that region accounted for by far the smallest share of all of the housing units in the large urban areas but had the largest share in 2020. In the final decade, nearly half of all growth in housing units for the large urban areas was in the South. The distribution of the sizes of urban areas is often thought to conform to Zipf’s law, postulating that the size and rank are related by a power law with an exponent of one. In 1950 the exponent was slightly greater than one. The exponent dropped by 2020 such that the the smaller urban areas were larger than expected.

This piece discusses the growing empirical evidence that the communities where American children spend their formative years—not just the households they are raised in but where those households are located—matter for their prospects of success in subsequent stages of their lives. The authors explore the various community characteristics—including social capital, family structure, school quality, and income—associated with educational attainment, health, teen pregnancy, social mobility, violence, crime victimization, and more

We examine transitions into and out of car ownership among low-income households. We use a novel online survey of U.S. residents to investigate why households lose access to a car, how long they are without a car, why they regain a car, and how these transitions affect their quality of life. We find that car ownership transitions are primarily motivated by economic security and insecurity. The median length of a car-less episode is 1.7 years, while black and Hispanic respondents experienced longer car-less episodes. Despite their precarious grasp on car ownership, respondents felt that owning a car was worth it.

This dissertation consists of three chapters in labor economics. A theme throughout these chapters is using empirical analysis to examine how local labor markets, firms, and workers respond to policy and structural economic changes in the US. Chapter 1 documents the persistent effect of deindustrialization on local economies and their residents, from the decline of the New England textile industry in the 1920s. By comparing workers in towns with more and less initial exposure to the textile industry, I document that workers in textile-heavy towns were less likely to out-migrate. The fixed cost of moving and increased family support may have played a role in the decreased migration. Workers switched to the agricultural sector and faced lower earnings on average. Young workers increased their educational attainment, but the increased schooling did not translate to better labor market outcomes nor increased migration likelihood. In Chapter 2, Ilyana Kuziemko, Ebonya Washington, Gavin Wright, and I explore the local employment and political effect of NAFTA. We show NAFTA hurt employment in areas exposed to Mexican import competition. While NAFTA-exposed counties were more Democratic during the 1980s up to the early 1990s, they became increasingly Republican after the policy. In the areas most exposed to NAFTA, workers significantly opposed NAFTA, and a significant number of voters with protectionist views moved toward the Republican party between 1992 and 1994. In Chapter 3, Leah Boustan, David Clingingsmith, and I investigate the effect of computer numerical control (CNC) on employment and labor productivity in the US, which are thought to have replaced semi-skilled manufacturing workers in metal manufacturing starting the 1970s. We build a novel measure of exposure to this automation shock, and we find that industries more exposed to CNC experienced higher labor productivity, while reducing production employment. The relative demand for college-educated workers and abstract tasks rose. Workers in more exposed labor markets adjusted by shifting from metal manu3 facturing to other manufacturing industries. Some workers in exposed industries returned to school. Union members were shielded from job loss.

Racial and ethnic residential diversity in urban areas is measured using an index of exposure diversity, which is the mean of diversity within census tracts, and an index of evenness diversity relative to the diversity of the urban area. These indexes are used to examine neighborhood diversity among whites, blacks, Latinos, and Asians in 56 large urban areas in the United States from 1980 to 2020. Mean diversity across the urban areas increased dramatically. But substantial differences exist between exposure diversity and evenness diversity. An area with very low exposure diversity can have very high evenness diversity when the overall diversity of the urban area is also low. Diversity tends to be lower in urban areas in the Northeast and Midwest, highest in the West. Lower percent population white and decreases in the white population in the prior decade are associated with higher levels of exposure diversity with just the opposite for blacks, Latinos, and Asians. Average levels of the two measures of diversity increased in both the urban core and suburban periphery, but exposure diversity was higher in the core while evenness diversity was higher in the suburbs.

Employment rates fell dramatically between March and April 2020 as the initial shock of the COVID-19 pandemic reverberated through the US labor market. This paper uses data from the CPS Basic Monthly Files to document that the employment decline was particularly severe for immigrants. Historically, immigrant men are more likely to work than native men. The pandemic-related labor market shock eliminated the immigrant employment advantage. After this initial precipitous drop, however, the employment recovery through June 2021 was much stronger for immigrants, and particularly for undocumented immigrants. The steep drop in immigrant employment at the start of the pandemic occurred partly because immigrants were less likely to work in jobs that could be performed remotely and suffered disproportionate employment losses as only workers with remotable skills were able to continue working from home. The stronger employment recovery of undocumented immigrants, relative to that experienced by natives or legal immigrants, is mostly explained by the fact that undocumented workers were not eligible for the generous unemployment insurance (UI) benefits offered to workers during the pandemic.

Family structure is considered a particularly important predictor of social and political development; historical differences in family size and other family characteristics cast a long shadow over societal development. This paper explores the effect of differences in historical family size on political behavior based on within-country variations in this characteristic in Russia. Unlike most papers on historical legacies, we trace the effect of family size over a century of Russian history with a focus on the first competitive and free elections in Russia—to the Constituent Assembly—held in 1917 and on the presidential elections in post-Soviet Russia in 1996 and 2000. Mean family size is measured based on the census data for 1897. We find a robust and significant association between smaller family size and a voting preference for parties that are economically liberal, which holds despite differences in the political, economic, and social environment between the 1910s and 1990s

HIV/AIDS has been one of the largest public health crises in recent history, and the US federal government has spent hundreds of billions of dollars fighting the disease. This study examines the impact of the large amounts of federal funding allocated to US cities to combat HIV/AIDS through the Ryan White CARE Act's first title. The findings indicate that the cost to avoid an HIV/AIDS death through the program is roughly $334,000, that the program has saved approximately 57,000 lives through 2018, and that funding disparities are responsible for the uneven progress in combating HIV/AIDS across the United States.

For many Afro-Latinxs, the simultaneity of phenotype, culture, parent’s birthplace, and language create a unique experience relegated to the margins of “Latinidad” and “Blackness.”1 The term Afro-Latinx most often refers to people of visible or self-proclaimed African descent from Latin America and the Caribbean, whether they currently live in the Caribbean, the Americas, or elsewhere. As Flores and Jiménez Román write, “[Afro-Latinxs] are the group that typically falls between the cracks of prevailing classifications, and yet at the same time stands to serve as the most significant bridge across a growing, and increasingly ominous, social divide.”2 Despite the unique situatedness of Afro-Latinxs and their substantial growth rate over the last decade,3 few studies have attempted to quantify4 and center their lived experiences using Census Bureau data.5 In this brief, we use the 2015-2019 5-year American Community Survey (ACS) microdata to analyze the U.S. Afro-Latinx population, including their unique trends in education, employment, and homeownership.

While considerable attention has been given to the ways that parents contribute to undergraduates’ success, far less attention has been given to what these students do for their families, variation in students’ provision of help, or the consequences of giving. Drawing on 61 interviews with Asian American college students from diverse ethnic and class backgrounds, this paper extends conventional understanding of families and college by analyzing the financial assistance and translation support Asian American undergraduates give their parents. Using a trichotomous model of class—comparing disadvantaged, advantaged, and ambiguous students—I show that class disadvantage motivated students’ helping, advantage deterred it, while the ambiguous fell in between. Culture (i.e., filial piety) and a broad view of family (i.e., siblings’ contributions) also influenced students’ help. Finally, based on interview data combined with partial support from analysis of participants' grade point averages data, I demonstrate that helping had positive and negative implications for students’ college experience.

An extensive social science literature has examined the effects of climate change on human migration. Prior studies have focused largely on the out-migration of working-age adults or entire households, with less attention to migration among younger and older individuals. In this study, we focus on the implications of climate variability for the movement of children by examining the association between climate exposures and the in- and out-fostering of children in sub-Saharan Africa. We link high-resolution temperature and precipitation records to data from the Demographic and Health Surveys for 26 sub-Saharan African countries. We fit a series of regression models to measure the overall associations between climate exposures and each outcome, and then evaluate whether these associations are moderated by socioeconomic status, the number of children in the household, and the prevalence of fostering in each country. We find that precipitation is positively associated with in-fostering overall, and that effects are especially strong among households who already have at least one child and in countries where child fostering is common. We find no overall relationship between either temperature or precipitation exposures and out-fostering, but we do detect significant effects among households with many children and those with more-educated heads. Overall, this study demonstrates that new attention to the links between climate variability, child fostering, and other understudied forms of spatial mobility is needed to fully understand the effects of climate change on human populations.

Background: The connection between healthy housing status and health is well established. The quality of housing plays a significant role in infectious and non-communicable as well as vector-borne diseases. The global burden of disease attributable to housing is considerable with millions of deaths arising from diarrheal and respiratory diseases annually. In sub-Saharan Africa (SSA), the quality of housing remains poor although improvements have been documented. There is a general dearth of comparative analysis across several countries in the sub-region. We assess in this study, the association between healthy housing and child morbidity across six countries in SSA. Methods: We use the Demographic and Health Survey (DHS) data for six countries where the most recent survey collected health outcome data on child diarrhoea, acute respiratory illness, and fever. The total sample size of 91,096 is used in the analysis (representing 15, 044 for Burkina Faso, 11, 732 for Cameroon, 5, 884 for Ghana, 20, 964 for Kenya, 33, 924 for Nigeria, and 3,548 for South Africa). The key exposure variable is healthy housing status. We control for various factors associated with the three childhood health outcomes. These include quality housing status, residency (rural/urban), age of the head of the household, mother’s education, mother’s BMI status, marital status, mother’s age, and religious status. Others include the child’s gender, age, whether the child is from multiple or single births, and breastfeeding status. Inferential analysis using survey-weighted logistic regression is employed. Results: Our findings indicate that housing is an important determinant of the three outcomes investigated. Compared to unhealthier housing, healthy housing status was found to be associated with reduced odds of diarrhoea in Cameroon [Healthiest: aOR = 0.48, 95% CI, (0.32,0.71), healthier: aOR = 0.50, 95% CI,(0.35,0.70), Healthy: aOR = 0.60, 95% CI, (0.44,0.83), Unhealthy: aOR = 0.60, 95% CI, (0.44,0.81)], Kenya [Healthiest: aOR = 0.68, 95% CI, (0.52,0.87), Healtheir: aOR = 0.79, 95% CI, (0.63,0.98), Healthy: aOR = 0.76, 95% CI, (0.62,0.91)], South Africa[Healthy: aOR = 0.41, 95% CI, (0.18, 0.97)], and Nigeria [Healthiest: aOR = 0.48, 95% CI,(0.37,0.62), Healthier: aOR = 0.61, 95% CI,(0.50,0.74), Healthy: aOR = 0.71, 95%CI, (0.59,0.86), Unhealthy: aOR = 0.78, 95% CI, (0.67,0.91)], and reduced odds of Acute Respiratory Infection in Cameroon [Healthy: aOR = 0.72, 95% CI,(0.54,0.96)], Kenya [Healthiest: aOR = 0.66, 95% CI, (0.54,0.81), Healthier: aOR = 0.81, 95% CI, (0.69,0.95)], and Nigeria [Healthiest: aOR = 0.69, 95% CI, (0.56,0.85), Healthier: aOR = 0.72, 95% CI, (0.60,0.87), Healthy: aOR = 0.78, 95% CI, (0.66,0.92), Unhealthy: aOR = 0.80, 95% CI, (0.69,0.93)] while it was associated with increased odds in Burkina Faso [Healthiest: aOR = 2.45, 95% CI, (1.39,4.34), Healthy: aOR = 1.55, 95% CI, (1.09,2.20)] and South Africa [Healthy: aOR = 2.36 95% CI, (1.31, 4.25)]. In addition, healthy housing was significantly associated with reduced odds of fever among children in all countries except South Africa [Healthiest: aOR = 2.09, 95% CI, (1.02, 4.29)] where children living in the healthiest homes had more than double the odds of having fever. In addition, household-level factors such as the age of the household head, and place of residence were associated with the outcomes. Child-level factors such as breastfeeding status, age, and sex, and maternal-level factors such as education, age, marital status, body mass index (BMI), and religion were also associated with the outcomes. Conclusions: The dissimilarity of findings across similar covariates and the multiple relations between healthy housing and under 5 morbidity patterns show unequivocally the heterogeneity that exists across African countries and the need to account for different contexts in efforts to seek an understanding of the role of healthy housing in child morbidity and general health outcomes.

Agritourism is a growing sector that can provide opportunities for rural entrepreneurs and boost rural development in the US. Online presence is crucial for agritourism operators because they cater to consumers. In this study, we employ count data regression models to investigate the relationship between broadband adoption and the number of agritourism operations. Our analysis shows that access to fast broadband internet in 2012 significantly increased the number of agritourism operations in 2017, underscoring the pivotal role of broadband connectivity in facilitating farmer-consumer interactions.

Evaluating insurance coverage at the individual level abstracts away from the family-level decision making behind healthcare utilization. While traditional private insurance tends to be offered to either adult individuals or whole families, public insurance eligibility is determined person-by-person. Income eligibility thresholds for public coverage can differ for parents and children, and even among children in different age groups. Having different insurance sources, or a mix of insured and uninsured members of a family, may be disruptive to consistent medical care. In this paper we investigate how changes in eligibility thresholds for adults and children are associated with mismatched patterns of insurance coverage. Using the Current Population Survey and the Survey of Income and Program Participation, we document the patterns of insurance mismatch over time and their relationship to Medicaid and State Children's Health Insurance Program income eligibility thresholds. We find that expansions of parent thresholds can promote uniform insurance coverage for families. These results are driven by families led by single mothers, who are more likely to be affected by Medicaid expansions for parents. Treating a family as the main unit of observation provides important insights and details potential unintended consequences of individual-level public insurance policy.

Heavy-duty vehicles (HDVs) disproportionately contribute to the creation of air pollutants and emission of greenhouse gases—with marginalized populations unequally burdened by the impacts of each. Shifting to non-emitting technologies, such as electric HDVs (eHDVs), is underway; however, the associated air quality and health implications have not been resolved at equity-relevant scales. Here we use a neighbourhood-scale (~1 km) air quality model to evaluate air pollution, public health and equity implications of a 30% transition of predominantly diesel HDVs to eHDVs over the region surrounding North America’s largest freight hub, Chicago, IL. We find decreases in nitrogen dioxide (NO2) and fine particulate matter (PM2.5) concentrations but ozone (O3) increases, particularly in urban settings. Over our simulation domain NO2 and PM2.5 reductions translate to ~590 (95% confidence interval (CI) 150–900) and ~70 (95% CI 20–110) avoided premature deaths per year, respectively, while O3 increases add ~50 (95% CI 30–110) deaths per year. The largest pollutant and health benefits simulated are within communities with higher proportions of Black and Hispanic/Latino residents, highlighting the potential for eHDVs to reduce disproportionate and unjust air pollution and associated air-pollution attributable health burdens within historically marginalized populations.

Close-kin marriage, by sustaining tightly knit family structures, may impede development. We find support for this hypothesis using U.S. state bans on cousin marriage. Our measure of cousin marriage comes from the excess frequency of same-surname marriages, a method borrowed from population genetics that we apply to millions of marriage records from the eighteenth to the twentieth century. Using census data, we first show that married cousins are more rural and have lower-paying occupations. We then turn to an event study analysis to understand how cousin marriage bans affected outcomes for treated birth cohorts. We find that these bans led individuals from families with high rates of cousin marriage to migrate off farms and into urban areas. They also gradually shift to higher-paying occupations. We observe increased dispersion, with individuals from these families living in a wider range of locations and adopting more diverse occupations. Our findings suggest that these changes were driven by the social and cultural effects of dispersed family ties rather than genetics. Notably, the bans also caused more people to live in institutional settings for the elderly, infirm, or destitute, suggesting weaker support from kin.

In the last decade, significant infrastructure changes occurred in the U.S. electricity sector. Between 2010-2018, 546 coal-fired power units retired, while natural gas and renewable developments grew. These infrastructure changes allow for a natural experiment examining the impact of power-plant emissions on population health, and thus can be used to study the health impacts of coal emissions on respiratory diseases. Using survey data from the National Center for Health Statistics, this paper proposes a study design to examine health benefits and estimate changes in health disparities from the closure of U.S. coal power plants. Respondent data from the National Health Interview Survey on respiratory health outcomes can be merged with the location of power plants and climatic wind direction. We provide a method to merge restricted access data and estimate a statistical model of health outcomes that allows data to remain deidentified while comparing across disparity dimensions (e.g. income, race), wind direction, and coal power plant closures. The findings contribute to the fields of environmental health economics, and energy economics by quantifying the benefit of improved health from coal plant closures across racial and income subgroups.