Objectives: Although influenza vaccinations are widely accessible, many people in the United States do not receive them as recommended by the Centers for Disease Control and Prevention. This study examined the relationship between income and receiving the influenza vaccination among US adults. Methods: We used 2014-2018 National Health Interview Survey data (N = 138 697). Adults self-reported whether they received a shot or nasal spray vaccine within the previous 12 months and their total family income. We used multivariable logistic regression to obtain odds ratios and 95% CIs. Results: Approximately 43% of adults reported receiving the influenza vaccine in the previous 12 months. After adjustment, adults in lower-income-level categories had decreased odds of influenza vaccine receipt compared with adults with a total family income ≥$100 000. Specifically, adults with a total family income <$35 000 had 21% decreased odds of receiving the influenza vaccine (adjusted odds ratio = 0.79; 95% CI, 0.75-0.83). Conclusions: In this population of US adults, lower income levels were associated with decreased odds of influenza vaccine receipt. The relationship between income and receipt of the influenza vaccine may have important implications for future influenza vaccination efforts. Increasing influenza vaccination coverage among lower-income adults should be considered a public health priority.

Both the share of women who have ever married and the share who have ever had a birth has declined (FP-22-19), while those who do marry and/or have a birth are increasingly delaying these events to later ages (FP-21-12, FP-20-06). The marital context in which women have births varies by educational attainment, race/ethnicity, and age (FP-22-13). This profile expands beyond marital status by including cohabitation (union status) and relies on recent data from the 2014 and 2020 June Fertility Supplement of the Current Population Survey (CPS) to identify recent trends in women’s union status at first birth. Using data from the 2020 supplement to focus just on first births occurring between 2018 and 2020, we further consider union status by educational attainment, race/ethnicity, and age at first birth. Only women who were aged 44 or younger at first birth are included in the analyses. In this profile, “single” refers to those who are not married nor living with a partner.

This paper argues that the public education policies, which affect schooling years and education quality, are important to understand sectoral employment and productivity. We build a general equilibrium multi-sector heterogeneous-agent life-cycle model, which features both education investment, in terms of schooling years and expenditure, and sectoral employment choices. Disciplining the stock of human capital using schooling years and return data, we perform counter-factual experiments and show that eliminating public education policies would increase agricultural employment by 46% while endowing the country with U.S. public education policies would reduce the agricultural employment by 13% even when assuming constant years of schooling.

Hurricane Katrina was a historic event, forever changing many lives as well as altering impacted communities in the short and long term. In the fifteen years since the storm, patterns of damage, recovery programs and dollars, and existing neighborhood change have altered demographics in coastal Mississippi. This thesis investigates how population, median age, race, and education demographics have changed at the census tract level in the fourteen years since Hurricane Katrina (2006-2019) compared to pre-Katrina trends (1990-2000). A moving average using American Community Survey data as well as interval changes measure how different neighborhoods have been altered since the storm. Local Moran’s I cluster and outlier analysis combined with a change concept test identified clusters of large and small change. Large changes were focused on the Gulf Coast and inland tracts where development has focused since the storm while small changes were less common and scattered throughout the tri-county study area. The subsequent case study on coastal Mississippi considered damage, FEMA assistance recipients, and the growth of impervious areas before reviewing reports on Katrina recovery, city and county development, and regional plans for the future. The case study found that housing development was focused away from the coast, with many people priced out of rebuilding homes directly on the coast or opting away from future risk. For the most part, economic development remained focused on the coast, including tourism and multiple ports, which have been repeatedly impacted after Hurricane Katrina, including the 2010 BP oil spill.

There is well-documented income sorting across neighborhoods within defined administrative boundaries like school districts. Using campus level finance and demographic data for 3,500 K-12 schools in Texas, I show that income heterogeneity across neighborhoods can be mapped to per-pupil spending variation across schools within a district. I define this function as the school spending curve, and argue that the shape of the curve is vital for predicting within-school spending responses to neighborhood income shifts over time. To test this hypothesis I exploit spatial heterogeneity in the income composition of neighborhoods receiving affordable housing, and plausibly exogenous timing of construction approval to construct school enrollment and income composition shocks. I find that policy changes determining the shape of the Texas spending curve over time are soley responsible for preventing sharp declines in per-pupil spending following the construction of new affordable housing. My counterfactual exercise illustrates that benefits from increasingly progressive education policy in Texas appears to be captured by upper-middle income schools receiving new affordable housing development.

By the time the Fed raised interest rates in March 2022, employment had bounced back for most groups, but, as Burcu Eyigungor finds, there were two notable exceptions.

This paper investigates the effects of the introduction of Medicaid during the 1960s on next generations' birth outcomes. A federal mandate that all states must widen the coverage to all cash welfare recipients generated cross-state variations in Medicaid eligibility, specifically among nonwhites who largely overrepresented the target population. I implement a reduced-form difference-indifferences strategy that compares the birth outcomes of mothers born in states with higher cash welfare recipiency versus low welfare recipiency and different years relative to the Medicaid implementation year. Using Natality data (1970-2004), I find that Medicaid significantly improves birth outcomes. The effects are considerably larger among nonwhites, specifically blacks. The effects do not appear to be driven by preexisting trends in birth outcomes, preexisting trends in households' socioeconomic characteristics, changes in other welfare expenditures, and selective fertility. A back-of-an-envelope calculation points to a minimum of 3.9% social externality of Medicaid through income rises due to next generations' improvements in birth outcomes.

This paper shows that the ancestry composition shaped by century-long immigration to the US can explain the current structure of global supply chain networks. Using an instrumental variable strategy, combined with a novel dataset that links firm-to-firm global supply chain information with a US establishment database and historical migration data, we find that co-ethnic networks formed by immigration have a positive causal impact on global supply chain relationships between foreign countries and US counties. Such a positive impact not only exists in conventional supplier-customer relationships but also extends to strategic partnerships and trade in services. Examining causal mechanisms, we find that the positive impact is stronger for counties in which more credit-constrained firms are located, and such a stronger effect becomes even more pronounced for foreign firms located in countries with weak contract enforcement. Collectively, the results suggest that co-ethnic networks serve as social collateral to overcome credit constraints and facilitate global supply chain formation.

This book explores the local environmental impact of sports stadiums, and how that impact can disproportionately affect communities of color. Offering a series of review articles and global case studies, it illustrates what happens when sport organizations and other public and private stakeholders fail to factor environmental justice into their planning and operations processes. It opens with an historical account of environmental justice research and of research into sport and the natural environment. It then offers a series of case studies from around the world, including the United States, Canada, Kenya, South Africa, and Taiwan. These case studies are organized around key elements of environmental justice such as water and air pollution, displacement and gentrification, soil contamination, and transportation accessibility. They illustrate how major sports stadiums have contributed positively or negatively (or both) to the environmental health of the compact neighborhoods that surround them, to citizens’ quality of life, and in particular to communities that have historically been subjected to unjust and inequitable environmental policy. Placing the issue of environmental justice front and center leads to a more complete understanding of the relationship between stadiums, the natural environment, and urban communities. Presenting new research with important implications for practice, this book is vital reading for anybody working in sport management, venue management, mega-event planning, environmental studies, sociology, geography, and urban and regional planning. The Open Access version of this book, available at www.taylorfrancis.com, has been made available under a Creative Commons Attribution-Non Commercial-No Derivatives 4.0 license.

In the Coachella Valley, issues of water access are spatial in nature. Residents of the Eastern Coachella Valley experience water insecurity, while residents and visitors of the Western Coachella Valley have access to water for both potable and non-potable purposes. My dissertation takes the spatial inequality of water access between the two regions as a foundation for inquiry. I ask: How did the Coachella Valley’s spatial inequality in water access develop, deepen, and become exacerbated? I answer this question using the extended case method with water access in the Coachella Valley as my case. I use spatial analysis to examine the geographic patterns of water access over time, situating them within the institutional and water source context of the Coachella Valley. I analyze policy and archival documents to understand three conjunctural eras of spatial inequality in water access. I start with early United States settler colonialism in the late 1800s in the Coachella Valley. I then examine regional government iii formation for water management from the early 1900s to mid-century. Finally, I analyze contemporary land and water use policies that currently exacerbate spatial inequality in water access. I find that United States settler colonial policies were used by early settlers to dispossess Coachella Valley Indigenous communities of land and water, developing spatial inequality in water access. This spatial inequality, first presented as a racialized checkerboard spatial pattern between Indian/public and non-Indian/private land, deepened with the 1918 formation of a regional government to manage water provision and distribution, the Coachella Valley Water District. The water district, designed to grow the agriculture industry, established a center/periphery pattern of water access based on use where access to agricultural water was found in the periphery and access to domestic water was built in the region’s urban core. Today, regional county land use and water district regulations exacerbate both spatial patterns. Their growth for growth policies (that require new private development to expand public infrastructure provision) pursue peri-urbanization through luxury tourist developments. In doing so, they increase socio-economic disparities and decrease geographic proximity between those who have access and those who lack access to water.

As you get older, it might start to feel like everyone is getting younger around you. At what point are you older than the majority? Based on data from the American Community Survey, the chart below shows the percentage and number of people who are older and younger than you, given an age and categorized by sex.

In the USA, military service has been proposed as a social mobility opportunity for individuals from socially marginalized backgrounds, specifically that military training and access to benefits aid their civilian socioeconomic status. We examined the association between demographic characteristics and the education level and income level of American Indian and Alaska Native (AIAN) and non-Hispanic white men between the ages of 22 and 83, and consider veteran status as a moderator of socioeconomic status. We used logistic regression on whether the individual holds a bachelor’s degree and OLS regression on logged total income for our analyses. Our research suggests that single-race AIAN active duty veterans for eras between 1975 and 2001 were associated with higher education than their non-veteran counterparts and those who did not serve in these specific active-duty eras. We also found that overall single-race AIAN active-duty veterans for eras between 1975 and 2001 have higher incomes than those AIAN men who did not. Yet, we found that the gains by AIAN veterans were insufficient to close the income gap between AIAN and white men. The study bolsters the literature that inequality continues to persist for AIAN men despite individual pursuits for socioeconomic advancement. Our findings suggest that future research should investigate mechanisms of social mobility for Indigenous Peoples and more fully understand that social and structural forces that limit individual efforts for socioeconomic advancement.

A major challenge in assessing the health risks of PM10-2.5 is the limited ground-level measurement data from which to estimate exposure. This is especially problematic for studying long-term PM10-2.5 health effects since PM10-2.5 is more spatially variable than PM2.5 or PM10, particularly in urban areas. Fortunately, Aerosol Optical Depth (AOD) data from satellites offer opportunities to assess PM10-2.5 more broadly. Our project leverages measurements from NASA's Terra satellite to estimate long-term PM10-2.5 concentrations in six US urban areas (Los Angeles, CA; Chicago, IL; St. Paul, MN; Baltimore, MD; New York, NY; Winston-Salem, NC) for 2000–2012. We calibrated AOD (1 km2 resolution) with EPA monitored PM10 and PM2.5 levels daily using an area-specific mixed-modeling approach with land-use regression. We then used spatial smoothing in generalized additive mixed-models to predict daily PM10 and PM2.5 when AOD was missing. PM10-2.5 was estimated after taking the difference of spatially matched PM10 and PM2.5 daily predictions. Model performance for our long-term average predictions was evaluated using leave-one-station-out cross-validation and compared to alternative, nearest-monitor and inverse distance weighting (IDW) approaches. Final long-term PM10-2.5 predictions were well correlated with measured levels estimated from collocated PM2.5 and PM10 sites in five of the six areas, with spatial CV R2 ranging from 0.50 to 0.97. Only in Winston-Salem did the model have very little predictive ability (R2: 0.34). All spatial predictions performed better than the nearest-monitor and IDW alternatives. In contrast, our final PM10-2.5 predictions had poor temporal performance, with mean monitor-level CV R2 ranging from 0.15 to 0.42. Given the superior performance of our spatial predictions compared to nearest-monitor and IDW alternatives and the high costs of field sampling, our results show the potential for combining AOD data with land-use regression to estimate long-term PM10-2.5 concentrations in localized areas.

This paper investigates the relative importance of various attributes, including varietal, brands, and geographic origin, in explaining retail wine prices for the United States market. We use a metric based on the Shapely value, from cooperative game theory, in the context of an empirical hedonic price equation estimated using a large sample of retail wine sales for home consumption over the period 2007–2019. We find that brands alone explain more than 70% of the variation in wine prices, but geographic origin and varietals retain additional explanatory power. Furthermore, information about the geographic origin appears to be a considerably more important attribute than varietals.

Introduction: Structural racism is strongly related to racial health disparities. However, surprisingly few studies have developed empirical tools to measure structural racism. In addition, the few measures that have been employed have only considered structural racism at the neighborhood level. To expand upon previous studies, this paper uses a novel measure to measure structural racism at the county level for the non-Hispanic Black population. Methods: We used confirmatory factor analysis to create a model to measure the latent construct of structural racism for 1181 US counties. The model included five indicators across five dimensions: racial segregation, incarceration, educational attainment, employment, and economic status/wealth. Structural equation modeling and factor analysis were used to generate factor scores that weighted the indicators in order to produce the best model fit. The resulting factor scores represented the level of structural racism in each county. We demonstrated the utility of this measure by demonstrating its strong correlation with Black-White disparities in firearm homicide rates. Results: Our calculations revealed striking geographic differences across counties in the magnitude of structural racism, with the highest values generally being observed in the Midwest and Northeast. Structural racism was significantly associated with higher Black firearm homicide rates, lower White homicide rates, and a higher Black-White racial disparity in firearm homicide. Conclusions: These new measures can be utilized by researchers to relate structural racism to racial health disparities at the county level.

Health disparities between different racial/ethnic groups in the United States are substantial. When reviewed across an extensive body of literature, these disparities have been demonstrated to persist even when socioeconomic status, geographic region, health conditions, treatment methods, and patient access-related variables are controlled for. This ultimately leads to higher mortality rates among minority patients, making disparities in health a highly prevalent issue. However, the literature suggests that while racial and ethnic disparities in health have been widely examined, research documenting the evolution of these changes over time is lacking. This motivates the research questions: (1) How has the impact of racial biases on disparities in health outcomes evolved over the past decade?; (2) To what extent do race and ethnicity impact variation in health outcomes?; and (3) To what extent are race and ethnicity correlated with the socioeconomic gradient in health?; Last, (4) How present were these disparities when looking at outcomes related to the COVID-19 Pandemic? This thesis aims to address these questions through a two-part empirical analysis using publicly available data from the National Health Interview Survey (NHIS) and the COVID-19 Case Surveillance Public Use Dataset from the Centers for Disease Control and Prevention (CDC).

The lagging racial and ethnic diversity of the public school teacher workforce is well documented. As of the 2014–2015 school year, students of color in U.S. public schools surpassed 50%, while the teacher workforce one year later consisted of slightly less than 20% teachers of color (McFarland et al., 2018; Snyder et al., 2018). Due to the myriad ways in which students of color benefit from having a diverse teacher workforce, the rapid growth in the share of nonwhite students has created an urgent need for recruiting and retaining teachers of color. For example, empirical evidence suggests that race match between teachers and students improves math and reading scores, especially for low-performing students (Egalite et al., 2015). Similarly, Black students are less likely than white students to be placed in gifted programs when taught by a non-Black teacher (Grissom & Redding, 2016), and Black boys are more likely to receive exclusionary discipline when taught by a non-Black teacher (Lindsay & Hart, 2017). More recent evidence showed that Black students who were exposed to a Black teacher during their early elementary grades are 7% more likely to graduate from high school and 13% more likely to enroll in college (Gershenson et al., 2018). Although there is scant evidence on the relationship between Hispanic teachers and Hispanic student outcomes, a recent study found that Hispanic students who were exposed to Hispanic math and science teachers in middle and high school were more likely to enroll in STEM courses during college (Sass, 2015). In short, the extant evidence suggests that low racial diversity among the teacher workforce has a number of adverse consequences for students of color (Goldhaber et al., 2019) and schools could better serve their students with a more representative teacher workforce

I examine the effects of the 2014 ACA Medicaid expansion on "job lock," defined as the reluctance to leave a job with employer-provided health insurance for a more desirable employment situation with no health insurance offer. Exploiting state-level spatial and temporal variation in implementation of the policy, I use a difference-in-difference estimation strategy to investigate the labor market effects of the policy for poor and near-poor individuals who are likely to have become newly eligible for Medicaid. I estimate that self-employment increased by 12.0 percentage points (p<0.001), private employment decreased by 13.1 percentage points (p=0.009), and labor force participation increased by 1.6 (p=0.010) to 2.6 (p=0.039) percentage points in expansion states relative to non-expansion states. I do not find evidence that overall employment rates were impacted by the expansion. Most of these labor market mobility increases accrued to white, male populations.

The economic analysis of racial discrimination in public accommodations is remarkably limited. To study this issue, we construct a national dataset of non discriminatory establishments from the Negro Motorist Green Books, a travel guide published from 1936 to 1966 to aid Black Americans in finding non-discriminatory retail and service establishments. We document patterns in the geographic spread and evolution of Green Book establishments, as well as the correlates of Green Book presence. We find economic and social measures, as well as state laws relating to racial discrimination and anti-discrimination, were correlated with the provision of non-discriminatory services. We then use the Green Book data to test whether market conditions and White consumer discrimination led businesses to bar Black customers prior to the Civil Rights Act of 1964. We use plausibly exogenous variation from White WWII casualties and Black migration patterns to isolate the effect of a change in the racial composition of consumers on the growth of non-discriminatory businesses. We find that the share of non-discriminatory establishments grew faster in locations with larger increases in the share of the Black population, but the magnitudes were small. These results highlight the importance of federal legislation in ending racial discrimination in public accommodations.

Background: Recent evidence has shown that fine particulate matter (PM2.5) may be an important environmental risk factor for chronic kidney disease (CKD), but few studies have examined this association for individual patients using fine spatial data. Objective: To investigate the association between PM2.5 and CKD (estimated glomerular filtration rate [eGFR]<45 ml/min/1.73 m2) in the Twin-Cities area in Minnesota using a large electronic health care database (2012–2019). Methods: We estimated the previous 1-year average PM2.5 from the first eGFR (measured with the CKD Epidemiology Collaboration equation using the first available creatinine measure during the baseline period [2012–2014]) using Environmental Protection Agency downscaler modeling data at the census tract level. We evaluated the spatial relative risk and clustering of CKD prevalence using a K-function test statistic. We assessed the prevalence ratio of the PM2.5 association with CKD incidence using a mixed effect Cox model, respectively. Results: Patients (n = 20,289) in the fourth (PM2.5 > 10.4), third (10.3 < PM2.5 < 10.8) and second quartile (9.9 < PM2.5 < 10.3) vs. the first quartile (<9.9 μg/m3) had a 2.52[2.21, 2.87], 2.18[1.95, 2.45], and 1.72[1.52, 1.97] hazard rate of developing CKD in the fully adjusted models, respectively. We identified spatial heterogeneities and evidence of CKD clustering across our study region, but this spatial variation was accounted for by air pollution and individual covariates. Significance: Exposure to higher PM2.5 is associated with a greater risk for incident CKD. Improvements in air quality, specifically at hotspots, may reduce CKD.