This issue examines the impact of COVID-19 on the construction industry over the past two years.

This paper documents how a one-time income shock can alter the household wealth distribution through local housing market channels. In 1936, the United States government unexpectedly gave World War I veterans a large income transfer. This payment, equivalent to 1936 per capita income, greatly improved recipients’ 1940 home values and homeownership rates compared to those of their 1930 neighbors. These home value gaps widened as the spatial intensity of the shock increased but only for likely home purchasers. Loan-level data suggest this combination of direct benefits and negative neighborhood spillovers derived from veterans crowding out other potential borrowers.

We examine the relationship between historical anti-miscegenation laws and contemporary racial classification within Black–White households in the United States using a multi-layered approach to conceptualizing that socio-historical context. We draw our sample of married Black–White households with children under the age of 18 from the 2012–2016 American Community Survey 5-Year estimates. Consistent with previous research, results suggest that households with connections to states that never had an anti-miscegenation law are less likely to adhere to the “one drop rule” than other households. However, these connections are not purely a reflection of the current state of residence; households comprised of two parents who were born in “no law” states – but currently live in states that had historical anti-miscegenation laws – display distinct racial classification patterns. This research contributes to our understanding of the link between place and race and highlights the power of migration in shaping ideas about race.

Background: This study examined the association between Medicaid expansions under the Affordable Care Act (ACA) and births among low-income women of reproductive age in the United States. Methods: We used data from the 2008 to 2019 American Community Survey to estimate the association between state adoption of Medicaid expansion under the ACA and the percent of low-income women of reproductive age with a birth in the past year using a difference-in-difference research design. Subgroup analysis was explored by race and ethnicity, age group, educational attainment, marital status, and number of children. Results: We found that Medicaid expansion was associated with a small reduction in births among low-income women of reproductive age by 0.45 percentage points (95% confidence interval: −0.84 to −0.05). In subgroup analyses, we found reductions in births among Hispanic women, American Indian or Alaska Native women, women 25–29 years of age, women 35–39 years of age, unmarried women, and women with more than three children. Conclusions: Reductions in births associated with Medicaid expansion could suggest that expanding Medicaid addressed previously unmet reproductive health care needs among low-income women of reproductive age. The reductions in births among low-income women that we observe were occurring among some groups with higher unintended pregnancy rates, including Hispanic women, American Indian or Alaska Native women, young women, and unmarried women. These findings underscore the importance of reproductive health care access through insurance coverage on empowering women to have control over their reproductive decision-making and timing.

We aimed to determine if long-term fine particulate matter (PM2.5) concentrations are associated with increased risk of testing positive for COVID-19 among pregnant individuals who were universally screened at delivery and if socioeconomic status (SES) modifies this relationship. We used obstetric data from Columbia University Irving Medical Center in New York City from March–December 2020, which included Medicaid use (low-SES surrogate) and coronavirus disease 2019 (COVID-19) test results. We linked 300m resolution estimated 2018-2019 PM2.5 concentrations and census tract-level population density, household size and income, and mobility estimates. Analyses included 3318 individuals; 5% tested positive for COVID-19 at delivery, 8% tested positive during pregnancy, 48% used Medicaid, and average long-term PM2.5 concentrations were 7.4 μg/m3 (SD = 0.8). In adjusted multilevel logistic regression models, we saw no association between PM2.5 and ever-testing positive for COVID-19; however, odds were elevated among those using Medicaid (odds ratio = 1.6, 95% CI 1.0, 2.5 per 1-μg/m3 increase). Further, while only 22% of those testing positive showed symptoms, 69% of symptomatic individuals used Medicaid. SES, including unmeasured occupational exposures or increased susceptibility to the virus due to co-social and environmental exposures, may explain the increased odds of testing positive for COVID-19 confined to vulnerable pregnant individuals using Medicaid.

Despite an overall decline in poverty rates the last 20 years, there persists major differences in poverty levels amongst minority racial and ethnic groups compared to the majority group. I study the poverty level of four different minority races and ethnicities and compare it to the poverty levels of white Americans. Additionally, I study the poverty level of individuals of poor health and compare it to those of fair, good, very good, or excellent health to determine whether such differences pertain to discrimination in both the labor and health care markets. To determine this, My sample is a cross-section from the IPUMS Health Surveys: National Health Interview Surveys (NHIS).

This paper analyzes the impact of skill-biased technological change (SBTC) on intergenerational education mobility. I set up an SBTC model with an overlapping generations framework, where heterogeneously-skilled households invest in their children’s education to make them skilled. Technology incentivizes these investments by creating both pecuniary (higher skill-premium) and non-pecuniary (improved life skills) benefits; it constrains investments among low-income households by increasing inequality. I show there is a critical technology range within which SBTC shocks can increase investments by both high-income and low-income households, improving absolute education mobility. Moreover, the relative increase in transfers can be larger for the low-income group who initially have lower investment levels, which can help their children catch-up. I test the predictions of the model using data from Chetty et al. (2014) which show how college attendance rates of children in U.S. commuting zones (CZs) are linked to the rank of their families in the national income distribution. A technology measure is constructed for each CZ using its share of STEM workers, which I instrument using a Bartik-type IV to deal with endogeneity concerns. From 2SLS estimations, I find that college attendance rates of children from households in the same income rank improve if households are located in higher technology CZs, with the improvement being larger among lower-ranked households. Thus, SBTC is found to improve both absolute and relative intergenerational education mobility.

Income inequality remains a deeply controversial and widely misunderstood socio-economic issue within the United States. This research investigated how much (if any) inequality existed among the various racial groups within US Metropolitan Areas between 1980 and 2010. Using over 32 million census records from the Integrated Public Use Microdata Series (IPUMS), variables for occupational diversity, educational attainment, income category, and income inequality (GINI) were constructed from the sample. Frequency distributions were calculated for each variable and the relationships between the variables were measured using Pearson correlations. Findings from this analysis provide strong empirical evidence that, although inequality increased in general over the sample period, the inequality gap between Whites and non-Whites is closing. The gap is closing not because non-Whites are “replacing” Whites but, more likely, because non-Whites are “replicating” successful economic strategies used by Whites.

This issue examines fatal and nonfatal electrical injuries in the construction industry, as well as OSHA citations and penalties resulting from violations of electrical standards.

This three-paper dissertation improves our understanding of how financial institutions and substance use impact local economies. It expands our understanding of economic resilience, with a focus on community banks, minority-owned banks, and opioid use. This dissertation demonstrates the importance of community-oriented financial institutions, community banks and minority-owned banks, in strengthening economic resilience. It also demonstrates how substance use, often viewed through the lenses of public health, can impact long-term economic development. Paper one estimates the impact of the community-bank market share on the timing and duration of the GFC in the US. This paper empirically demonstrates counties with higher community bank market shares are less likely to experience recession conditions. Paper two estimates the impact of the minority-owned bank market share on the severity of the Global Financial Crisis and the COVID Recession in the US. This paper empirically demonstrates counties with higher minority-owned bank market shares experience lower minority employment growth declines through the Global Financial Crisis, though not through the COVID Recession. Small business lending drives this effect; minority-owned banks continued lending through the Global Financial Crisis at higher rates relative to non-minority-owned banks. Paper three estimates the effect of region-level opioid use rates on net firm entry in the US. In this paper, I instrument for opioid use rates using pill mills, thus providing causal evidence that as core-based statistical area-level opioid use rates increase, net firm entry declines. Differential impacts are observed across firm sizes and industries; small firms and service-oriented firm are most impacted. Recent recessions in the US demonstrate the importance of economic resilience. Using a diverse set of econometric methods, this dissertation demonstrates the role of community-oriented financial institutions in strengthening economic resilience, as well as how public health conditions impact economic development.

Background Most US states and counties prioritized essential workers for early access to COVID-19 vaccines due to their heightened occupational risk. Racial/ethnic groups most impacted by COVID-19 are overrepresented among essential workers. This study estimates the effects of prioritizing essential workers on racial/ethnic equity in COVID-19 vaccination. Methods Survey data were collected from 5500 Los Angeles County adult residents in March and April 2021. Multivariate regression models were used to assess marginal changes in probabilities of vaccination attributable to essential worker status by race/ethnicity. These probabilities were multiplied by population proportions of essential workers in each racial/ethnic group to estimate the effects of prioritizing essential workers on vaccine equity in the population. Results While Latinos (24.9%), Blacks (22.4%), and Asians (21.4%) were more likely to be prioritized essential workers than Whites (14.3%), their marginal gains in vaccine uptake due to their essential worker status did not significantly differ from that of Whites. At the population-level, prioritizing vaccines for essential workers increased the probabilities of vaccination by small and similar amounts among Asians (5.3%; 95% confidence interval [CI]: 3.3%, 7.5%), Blacks (4.0%; 95% CI: 1.7%, 6.5%), Latinos (3.7%; 95% CI: 2.3%, 5.1%), and Whites (2.9%; 95% CI :1.9%, 3.9%). Conclusions Prioritizing essential workers did not provide proportionally greater early vaccine uptake benefits to racial/ethnic groups that were disproportionately affected by COVID-19. Early prioritization of essential workers during vaccine campaigns is an important but insufficient strategy for reducing racial/ethnic disparities in early vaccine uptake. Additional strategies addressing access and trust are needed to achieve greater equity in vaccine distribution.

Open data sharing democratizes science by making data more equitably available throughout the world. Furthermore, open data sharing improves the reproducibility and quality of research and enables new collaborations powered by the freely available data. Open data are defined as data that can be freely used, reused, and redistributed by anyone. For an interdisciplinary field like biological anthropology, data sharing is critical since one person cannot easily collect data across the domains relevant to our field. The goal of this paper is to encourage broader data sharing in our discipline by exploring the state of data sharing in the field of biological anthropology. Our paper is divided into four parts: the first section describes the benefits, challenges, and emerging solutions to open data sharing; the second section presents the results of our data archiving and sharing survey that was completed by over 700 researchers; the third section presents personal experiences of data sharing by the authors; and the fourth section discusses the strengths of different types of data repositories and provides a list of recommended data repositories.

Background: A variety of approaches to defining sepsis using administrative datasets have been previously reported. We aimed to compare estimates, demographics, treatment factors, outcomes and longitudinal trends of patients identified with sepsis in United States emergency departments (EDs) using differing sets of sepsis criteria. Methods: We performed a cross-sectional study using the National Healthcare Ambulatory Medical Care Survey, a complex survey of nonfederal US ED encounters between 2002 to 2018. We obtained survey-weighted population-adjusted encounters of sepsis using the following criteria: explicit sepsis, severe sepsis, and quick Sequential Organ Failure Assessment (qSOFA) score combined with the presence of infection. Results: Age-adjusted for US adults, 18.6, 16.1 and 8.9 encounters per 10 000 population were identified when using the explicit, severe sepsis and qSOFA definitions, respectively. A higher proportion of the explicit cohort was hospitalized and had blood cultures performed, compared to cohorts ascertained using severe sepsis and qSOFA criteria, though confidence intervals overlapped. Antibiotic use was highest in encounters meeting qSOFA criteria. When inspecting unweighted encounters meeting each set of criteria, there was minimal overlap, with only 3% meeting all three. Encounters meeting the explicit and severe sepsis criteria were increasing over time. Conclusion: The explicit, severe sepsis and qSOFA criteria generated similar annual rates of presentation when applied to US ED encounters, with some evidence of the explicit sepsis cohort being higher acuity. There was minimal overlap of cases and instability in estimates when assessed longitudinally. Our findings inform research efforts to accurately identify sepsis among ED encounters using administrative data.

Pharmaceutical and personal care products (PPCPs) are chemical compounds used by humans to improve health and well-being. Once these compounds have served their purpose, the remaining waste material often makes its way into the environment (Petrie et al 2015). Because of their widespread use and potential impacts, PPCPs have been a growing concern as environmental pollutants. Although PPCPs are usually found in the environment at the nanogram to microgram per liter scale, even at these low concentrations some PPCPs have been identified to cause detrimental environmental impacts (Korekar et al 2020, Havens et al 2020, Vo et al 2019). A comprehensive monitoring program for PPCPs remains a difficult prospect due to the approximately 3000 known pharmaceutical substances, with new substances constantly in development (Rodriguez-Narvaez et al. 2017). Compounding this issue is the effort required to monitor low concentration substances utilizing highly technical and expensive equipment, and the lack of historic data on these substances across the environment due to the relatively recent environmental concern over their pollution (Rodriguez-Narvaez et al. 2017). Questions have been raised regarding the ecosystem and anthropogenic variables that influence the distribution of PPCPs in aquatic environments, but the specific impact of human population size and density has been often overlooked. This thesis sought to identify generalized patterns in these anthropogenic variables affecting PPCP distribution.

The co-occurrence of and synergistic interactions between substance abuse, violence, and HIV, known as the “SAVA syndemic,” is thought to be a driver of women’s elevated risk for HIV in sub-Saharan Africa. This study uses data from the 2016 South African Demographic and Health Survey (DHS) and the 2016 South African Census to examine geospatial associations between alcohol use, intimate partner violence (IPV), unprotected sex, and HIV status among a population-based sample of 8528 South African women (age 15–49). Results support the geographic clustering of alcohol use, unprotected sex, and IPV, but not HIV, and geospatial clustering of HIV alone. This study highlights the need for geographically-tailored interventions to address syndemics through integrated interventions, such as those simultaneously focused on alcohol, IPV, and sexual risk reduction, and points to the need for more targeted research to link these factors to HIV from a place-based risk perspective.

Black-Latina/o and White-Latina/o bachelor’s degree gaps persist despite substantial increases in Latina/o educational attainment since the late 1950s. The Latina/o population has grown rapidly in recent decades and currently comprises over 20% of the United States population. However, barriers to citizenship have grown in tandem, and these barriers have limited access to higher education. Using data from the U.S. Census (1950-2010) and the ACS (2015-2017), we examine trends in Black-Latina/o and White-Latina/o college completion gaps and factors that may explain them. We find that college enrollment differences explain the majority of the bachelor’s degree gaps. We then decompose enrollment gaps by differences in enrollment by citizenship. We find that if Latina/os had the same citizenship rates as the White and Black populations, the Black-Latina/o enrollment gaps would effectively disappear, and the White-Latina/os enrollment gaps would be reduced by up to 75%. Our findings indicate that the Latina/o population's relatively low college completion rates can partially be explained by restricted access to citizenship. The high proportion of Latina/o non-citizens has also masked the considerable educational progress Latina/o citizens have made in recent decades.

Problem, research strategy, and findings New transportation options like ride-hail can expand accessibility without the costs of car ownership. Ride-hail’s potential is particularly salient for lower-income and zero-car households. We used interviews and a national (U.S.) survey to examine how and why lower-income travelers in the United States use ride-hail. Survey and interview responses provided a temporal snapshot and thus reflect, in part, travel challenges specific to COVID-19. Findings suggest that lower-income travelers, particularly those without personal cars, use ride-hail in ways distinct from those typically reported in broader travel surveys. Individuals without cars are more likely to use ride-hail, and use it more often, compared with people with cars, particularly to fill spatial and temporal gaps in public transit service and to access medical care and groceries. Costs and price unpredictability remain significant barriers limiting travelers’ use of ride-hail services. Takeaway for practice This research demonstrates a latent need for car access among lower-income travelers. Substantial gaps in alternative modes pose challenges for travelers seeking reliable and timely transportation. Planners should invest in transit, biking, and walking to provide robust alternatives to car ownership. Such investments, however, take time. In the meantime, cities and agencies should consider subsidizing ride-hail trips to bridge existing gaps in the transportation network.

Data from the early 2000s indicated worse overall health and larger socioeconomic (SES) health inequalities in the U.S. than in Canada. Yet, sociopolitical contexts, health levels, and SES-health inequalities have changed in both countries during the intervening two decades. Drawing on new data, we update the comparison of health levels and SES-health gradients between the two countries. Analyses, focused on self-rated health, are based on two complementary sets of data sources: Resilience and Recovery (RR) data, a harmonized U.S.-Canada survey of social conditions collected in 2020 (N = 3743); and a pair of leading nationally representative health data sources from each country: the National Health Interview Surveys (NHIS, N = 104,027) and the Canadian Community Health Survey (CCHS, N = 97,605), both collected in 2017–2018. Health levels and disparities, net of demographic and socioeconomic covariates, were estimated using modified Poisson models for relative comparisons; descriptives and predicted levels of fair/poor health show the comparisons from absolute perspective. Both data sources show that U.S. adults continue to have significantly worse health than Canadians; the disadvantage may be due to SES differences between the two populations. However, the two data sources yield conflicting findings on SES-health inequalities: the RR data indicate no difference between the two countries in socioeconomic health gradients, while the NHIS/CCHS data show a significantly steeper gradient in the U.S. than in Canada for both education and income. Canadian adults continue to report better health than their U.S. peers, but it is unclear whether health inequalities remain smaller as well. We discuss potential reasons for the conflicting findings and call for a large new cross-national data collection, which will enable scholars and policymakers to better understand health and wellbeing in the U.S. and Canadian contexts.

Background India launched the National Rural Health Mission (NRHM) in 2005 to strengthen its primary healthcare system in high-focus and northeast-focus states. One of the NRHM objectives was to reduce child undernutrition in India. Methods and findings We used data from 1992, 1998, 2005, and 2015 National Family Health Survey (NFHS) of India to evaluate trends in child undernutrition prevalence before and after NRHM and across different categories of focus states. Stunting, Wasting, and Comprehensive Index of Anthropometric Failure (CIAF) were assessed using the World Health Organization (WHO) growth curves to assess chronic, acute, and overall undernutrition. The study included 187,452 children aged 3 years or under. Survey-weighted and confounder-adjusted average annualized reduction rates (AARRs) and predicted probability ratios were used to assess trends and socioeconomic disparities for child undernutrition, respectively. Nationwide, the prevalence of all types of undernutrition decreased from 1992 to 2015. However, the trends varied before and after NRHM implementation and differentially by focus states. After NRHM, acute undernutrition declined more rapidly among high-focus states (AARR 1.0%) but increased in normal-focus states (AARR −1.9% per year; p-value for the difference <0.001). In contrast, the prevalence of chronic undernutrition declined more rapidly (AARR 1.6%) in the normal-focus states in comparison to high-focus states (0.3%; p-value for the difference = 0.01). Income and caste-based disparities in acute undernutrition decreased but did not disappear after the implementation of the NRHM. However, similar disparities in prevalence of chronic undernutrition appear to be exacerbated after the implementation of the NRHM. Major limitations of this study include the observational and cross-sectional design, which preclude our ability to draw causal inferences. Conclusions Our results suggests that NRHM implementation might be associated with improvement in wasting (acute) rather than stunting (chronic) forms of undernutrition. Strategies to combat undernutrition equitably, especially in high-focus states, are needed.

My dissertation studies labor market structure and evaluates effects of policies relating to transportation improvements and immigration enforcement in different countries including Germany, the Untied States, and China. Specifically, I examine the nature and extent of labor market frictions, explore the causes and consequences, as well as study the role in policy evaluations. In the first chapter, I investigate one potential source of labor market frictions from limited labor mobility by examining how integrating labor markets through improved transportation infrastructure affects both wages and the allocation of workers across establishments. I take advantage of the expansion of the High-Speed Rail in Germany, which connected medium-sized districts located on existing rail lines, providing a natural experiment to study the effects of labor market integration. Using administrative panel data on establishments and workers linked to their employers, I estimate difference-in-differences and event-study models that compare newly connected districts to matched controls that were never connected. In theory, policies that improve labor mobility might raise wages both by facilitating more productive matches of workers to firms and by reducing the monopsony power that employers have vis-`a-vis workers. I find evidence of increased labor mobility for workers in treated districts, especially those that are more likely to commute. Worker wages increase significantly and I find that both reduced monopsony power and better match quality are possible mechanisms. I also test for establishment adjustments including entry, exit, size, and wage that are predicted by each mechanism. This study shows evidence of reduced labor market frictions from improved transportation. It also sheds light on the importance of policies that enhance workers’ ability to switch employers. In the second chapter, I explore the effects of LAWA on labor markets based on evidence that LAWA has significantly reduced the population of Hispanic noncitizens in Arizona. Specifically, I focus on the composition of the labor force and industry heterogeneity. I first show that a synthetic control has similar concurrent economic trends with Arizona, and verify that changes in employee composition are due to the replacement of Hispanic noncitizen workers by other subgroups and not by a change in overall employment. In response to LAWA, firms tend to reduce both the new hire rate and the separation rate. Several robustness checks are conducted to test the accuracy of the estimates and several mechanisms are considered that may drive the results. In the third chapter, we study the structure of labor markets and the effects on wages in China. A growing literature has emphasized the existence of monopsony power stemming from employer concentration within local labor markets, which deviates from the conventional view of labor markets as perfectly competitive. We use firm-level data from the Chinese Annual Survey of Industrial Firms to analyze how employer concentration affects wage behavior. We first verify that local employment concentration measured by the Herfindahl-Hirschman Index of firm employment decreases between 1998 and 2013, in contrast to the increasing trend found in developed countries. Then with OLS and IV models, we show a negative relationship between labor market concentration and wages both the at the market level and at the firm level, indicating the existence of imperfect labor market competition in China.