We examine the consequences of monetary policy on racial disparities, focusing on the role of bank lending to firms through collateral and selection channels. Leveraging comprehensive loan-level data from the U.S. credit register (Y-14Q) of the Federal Reserve, we show that firms in Black communities obtain business loans that are more expensive and have a shorter maturity. These firms are also more likely to experience adverse credit supply shocks, controlling for firm risk and investment opportunities, as well as geographic and cultural covariates. We also study the effects of monetary policy across racial groups and document that, following a monetary policy tightening, banks extend loans to firms in Black communities at disproportionately higher interest rates. Furthermore, banks pass a monetary tightening through to loan rates for borrowers who have no collateral, have prior defaults, and have a shorter banking relationship, but even more to loan rates for firms in Black communities. Our findings suggest that monetary policy has distributional consequences in the form of tightened selectivity for Black minorities through lending conditions. Our analysis calls for place-based policies that target certain minority groups.

How did institutionalized discriminatory lending policies implemented under the guidance of the Federal Housing Administration (FHA)’s mortgage risk maps impact neighborhood trajectories? Have these spatially restrictive credit designations influenced home value, homeownership, and racial segregation? Using the FHA mortgage risk map of Chicago, Illinois, for new loan guarantees as a case study, I measure outcomes between credit zones and compare these risk regions with the Home Owners’ Loan Corporation (HOLC) Residential Security Maps, which represent post hoc measures of mortgage risk and were likely not directly used in loan activities. For areas excluded from FHA loan guarantees, the results suggest a negative impact on home values and homeownership rates and weakly decreased segregation between 1940 and 1980. They also suggest an overcorrection of home values, an under-correction of homeownership, and an increase in racial segregation in excluded neighborhoods between 1980 and 2010 when these areas may have experienced capital reinvestment. In comparison with the HOLC map, the effects on tracts in Chicago rated worst by the FHA are clearer and suggest a more significant impact during the period of discriminatory mortgage lending.

The “broken windows” hypothesis has led to millions of citizen/police encounters through aggressive enforcement of minor infractions. Despite extensive research on the relationship between broken windows and crime, there is less research on whether police officers focus on areas with broken windows, and the few studies that exist have mixed findings. Another set of studies finds high levels of policing in gentrifying neighbourhoods. On the one hand, then, studies show there is more policing in neighbourhoods with visible signs of disorder as police departments that adhere to the tenets of broken windows policing would be likely to send officers to patrol areas with broken windows, litter, and unkempt lawns in an effort to prevent crime in these areas. On the other hand, as high-income people move into these neighbourhoods, the signs of disorder should dissipate. This raises the question: Is there more policing in neighborhoods with signs of physical disorder or in neighbourhoods with signs of reinvestment? We measure this using three data sources: 1) an original housing survey using Google Street View that evaluates the level of physical disorder; 2) geocoded data from the Washington, DC Metropolitan Police Department on stop and frisks; and 3) Census and ACS data on population characteristics. These data allow us to answer our research questions: Are residents more likely to be stopped and frisked in neighbourhoods with high levels of physical disorder? Or, conversely, are residents more likely to be stopped and frisked in neighbourhoods experiencing an in-migration of middle-class residents?

Until the late 19th century, families in some municipalities paid small user fees, called rate bills, for their children to attend public schools. Urban school districts gradually repealed these fees and funded public education through local taxes. States eventually abolished rate bills, forcing rural areas to provide public education without tuition requirements. Using United States Census data and a staggered adoption difference-in-differences approach, I show that state-level rate bill abolition increased rural primary school attendance by 7.2 percentage points. These results suggest that small costs can be an obstacle to school attendance and inhibit the diffusion of education.

There is a growing population of adolescent and young adult (AYA, ages 15–39 at diagnosis) cancer survivors at heightened risk of chronic conditions. Moderate to vigorous physical activity level (MVPA) is an important modifiable factor associated with improved cardiovascular health. Little is known about the association of sociodemographic factors with MVPA in AYA survivors. Self-reported data from the National Health Interview Survey (2009–2018) were used to identify AYA cancer survivors (at least 2 years post-diagnosis) and age- and sex-matched controls. MVPA level based on sociodemographic (sex, race and ethnicity, income, education), medical (heart disease, stroke, and diabetes), and cardiovascular risk factors (BMI and smoking) was determined within and between survivors and controls using multivariable linear regression models. A total of 4766 AYA cancer survivors and 47,660 controls were included. Less than half of survivors (41.9%) and controls (43.2%) met MVPA guideline recommendations, and one-third of survivors (33.4%) reported no MVPA. Black race was associated with reduced MVPA compared with White race (ratio: 0.58 (95% CI: 0.37–0.90). Household income < $50,000/year, education < high school, diagnoses of diabetes or heart disease, and current smoking were all significantly associated with reduced MVPA in AYA survivors. There were no differences in MVPA between survivors and controls by sociodemographic factors, medical history, and cardiovascular risk factors. We found disparities in MVPA in AYA cancer survivors by sociodemographic, medical, and cardiovascular risk factors. Understanding trajectories of MVPA among different sociodemographic populations is needed to identify opportunities for intervention.

The 2021 CPS-ASEC underreports unemployment insurance benefits by approximately $220 billion. Using newly available summary data on unemployment insurance benefits in IRS tax records from Larrimore, Mortenson, and Splinter (2022), I estimate the effects of this underreporting on income and poverty statistics. If the CPS-ASEC had properly captured unemployment insurance benefits, the official poverty rate for income-year 2021 would have been 1.5 percentage points lower. Additionally, the supplemental poverty rate would have been 1.2 percentage points lower than that originally reported by the Census Bureau.

This paper studies the impact of the First Great Migration on children. We use the complete count 1940 Census to estimate selection-corrected place effects on education for children of Black migrants. On average, Black children gained 0.8 years of schooling (12 percent) by moving from the South to the North. Many counties that had the strongest positive impacts on children during the 1940s offer relatively poor opportunities for Black youth today. Opportunities for Black children were greater in places with more schooling investment, stronger labor market opportunities for Black adults, more social capital, and less crime.

Although scholars have acknowledged that shrinking federal resources for low-income housing programs increase economic inequality across the U.S. society as a whole, the question of how the allocation of these resources affects inequality among the poor has received little attention. Using a mixed-methods approach, this study examines local administrative practices of distributing scarce housing resources and the potential redistributive effects of those choices. Analyses of administrative and qualitative data collected from local housing agencies suggest that local administrative practices of managing a waitlist disadvantage residentially unstable applicants. Juxtaposing this finding with results from the Survey of Income and Program Participation suggests that among those who are income-eligible for program participation, poorer individuals have a greater likelihood of experiencing residential instability, thus compounding their disadvantage in the competition for a housing voucher.

The papers in this dissertation empirically estimate the causal effect of our social environment on our beliefs, preferences, and well-being. I present clear evidence that our decisions are not made in isolation. Rather, our very beliefs and preferences are shaped by our neighbors. Even our happiness may depend on the circumstances of those around us. The first paper reports evidence that neighbors with strong preferences or beliefs around politics, religion, or race are likely to shape our beliefs and preferences. In fact, the migration of individuals with strong preferences appears to be a key determinant of geographic patterns in political outcomes in contemporary America. The second paper shows how social context shapes reports of psychological well-being commonly used in important longitudinal surveys. Individuals understate the symptoms of depression and overstate their happiness when reporting directly to another individual. The final papers tests the relative income hypothesis showing that we are less happy when our neighbors become relatively richer. However, we find no evidence that individuals are averse to increases in income inequality.

This paper analyzes the employment trajectories of engineering workers-both workers in occupations formally classified as engineering and workers in occupations not formally classified as engineering but where engineering knowledge is important-during the COVID-19 pandemic. We find that the employment rate of workers in engineering occupations fell by 6.6 percentage-points at the onset of the pandemic compared to a 13.1 percentage-point drop among workers in non-engineering jobs, and that workers in jobs where engineering knowledge is important were less likely to suffer employment loss during the pandemic, regardless of whether their occupation is formally classified as a STEM engineering occupation. This suggests that engineering knowledge is beneficial in reducing a worker's unemployment risk during recessions. We also find that industries with the highest share of engineers as workers tended to experience smaller percentage declines in employment during the pandemic compared to overall US employment, although employment in aerospace and motor vehicle manufacturing industries remained over 10% below pre-recession employment as of 2021Q4.

Background: Monitoring progress toward population health equity goals requires developing robust disparity indicators. However, surveillance data gaps that result in undercounting racial and ethnic minority groups might influence the observed disparity measures. Objective: This study aimed to assess the impact of missing race and ethnicity data in surveillance systems on disparity measures. Methods: We explored variations in missing race and ethnicity information in reported annual chlamydia and gonorrhea diagnoses in the United States from 2007 to 2018 by state, year, reported sex, and infection. For diagnoses with incomplete demographic information in 2018, we estimated disparity measures (relative rate ratio and rate difference) with 5 imputation scenarios compared with the base case (no adjustments). The 5 scenarios used the racial and ethnic distribution of chlamydia or gonorrhea diagnoses in the same state, chlamydia or gonorrhea diagnoses in neighboring states, chlamydia or gonorrhea diagnoses within the geographic region, HIV diagnoses, and syphilis diagnoses. Results: In 2018, a total of 31.93% (560,551/1,755,510) of chlamydia and 22.11% (128,790/582,475) of gonorrhea diagnoses had missing race and ethnicity information. Missingness differed by infection type but not by reported sex. Missing race and ethnicity information varied widely across states and times (range across state-years: from 0.0% to 96.2%). The rate ratio remained similar in the imputation scenarios, although the rate difference differed nationally and in some states. Conclusions: We found that missing race and ethnicity information affects measured disparities, which is important to consider when interpreting disparity metrics. Addressing missing information in surveillance systems requires system-level solutions, such as collecting more complete laboratory data, improving the linkage of data systems, and designing more efficient data collection procedures. As a short-term solution, local public health agencies can adapt these imputation scenarios to their aggregate data to adjust surveillance data for use in population indicators of health equity.

We examine how shootings at schools-an increasingly common form of gun violence in the United States-impact the educational and economic trajectories of students. Using linked schooling and labor market data in Texas from 1992 to 2018, we compare within-student and across-cohort changes in outcomes following a shooting to those experienced by students at matched control schools. We find that school shootings increase absenteeism and grade repetition; reduce high school graduation, college enrollment, and college completion; and reduce employment and earnings at ages 24-26. We further find school-level increases in the number of leadership staff and reductions in retention among teachers and teaching support staff in the years following a shooting. The adverse impacts of shootings span student characteristics, suggesting that the economic costs of school shootings are universal.

This study analyzed the access to plumbed water and the quality of the water in Native American communities in Nevada. Census microdata were used to assess trends in household water access along with data on household characteristics sourced from the Integrated Public Use Microdata Series. Water quality reports were downloaded from the Environmental Protection Agency's Enforcement and Compliance History Online website. Individual compliance reports were accessed to identify health-based violations and violations that were not reported or monitored. The nonparametric Spearman's rho test was used to estimate trends. The analysis of the number of Native American community members with no access to plumbing increased from 1990 to 2019 (rs = 0.56, p = 0.0081). The overall percentage of Native American homes without indoor plumbing in Nevada was 0.67, which is higher than the reported 0.4 for the United States. The population affected by a lack of access to either plumbing, hot water, a shower, or a toilet increased as the number of family members increased. A growing trend (rs = 0.71, p = 0.018) was observed in the number of Safe Drinking Water Act violations registered by the EPA in water facilities serving Native Americans. The health-based violations most often registered were volatile organic chemicals and Revised Total Coliform Rules. The significance of these findings is highlighted not only in terms of the quality of life of the household members, but other health determinants such as the correlation between the access to clean, safe water and dissemination of diseases.

This paper examines differences in the wage-offer functions between males and females in the insurance industry. The results of random forest regression (RFR) residual analysis and quantile regressions (QRs) by gender indicate considerable inequities for underwriters, sales agents, and claims adjusters. We find relatively modest wage inequities among actuaries. Underwriters’ and adjusters’ gender wage inequality lies between the actuaries and sales agents. Across the specifications (RFR, QR, and the OLS benchmark), males benefit more from experience than females except for actuaries. In addition, males generally have a greater return to education than females (except for actuaries). Sales agents’ jobs exhibit the greatest inequality, with extremely high values for the regression Gini index of inequality at the upper quantiles. Actuaries exhibit the least amount of gender inequality across the board, with demographic responses suggesting competitive pressures across states yielding the least wage-offer inequality across gender. In summary, taste-based discrimination, social employment networks, difficulties in assessing productivity in heterogeneous work situations, competitiveness in the labor market, and the flexibility of work hours help explain our findings for different occupations in the insurance industry.

Importance Children with medical complexity (CMC) have substantial health care needs and frequently experience poor health care quality. Understanding the population prevalence and associated health care needs can inform clinical and public health initiatives. Objective To estimate the prevalence of CMC using open-source pediatric algorithms, evaluate performance of these algorithms in predicting health care utilization and in-hospital mortality, and identify associations between medical complexity as defined by these algorithms and clinical outcomes. Design, Setting, and Participants This retrospective cohort study used all-payer claims data from Colorado, Massachusetts, and New Hampshire from 2012 through 2017. Children and adolescents younger than 18 years residing in these states were included if they had 12 months or longer of enrollment in a participating health care plan. Analyses were conducted from March 12, 2021, to January 7, 2022. Exposures The pediatric Complex Chronic Condition Classification System, Pediatric Medical Complexity Algorithm, and Children With Disabilities Algorithm were applied to 3 years of data to identify children with complex and disabling conditions, first in their original form and then using more conservative criteria that required multiple health care claims or involvement of 3 or more body systems. Main Outcomes and Measures Primary outcomes, examined over 2 years, included in-hospital mortality and a composite measure of health care services, including specialized therapies, specialized medical equipment, and inpatient care. Outcomes were modeled using logistic regression. Model performance was evaluated using C statistics, sensitivity, and specificity. Results Of 1 936 957 children, 48.4% were female, 87.8% resided in urban core areas, and 45.1% had government-sponsored insurance as their only primary payer. Depending on the algorithm and coding criteria applied, 0.67% to 11.44% were identified as CMC. All 3 algorithms had adequate discriminative ability, sensitivity, and specificity to predict in-hospital mortality and composite health care services (C statistic = 0.76 [95% CI, 0.73-0.80] to 0.81 [95% CI, 0.78-0.84] for mortality and 0.77 [95% CI, 0.76-0.77] to 0.80 [95% CI, 0.79-0.80] for composite health care services). Across algorithms, CMC had significantly greater odds of mortality (adjusted odds ratio [aOR], 9.97; 95% CI, 7.70-12.89; to aOR, 69.35; 95% CI, 52.52-91.57) and composite health care services (aOR, 4.59; 95% CI, 4.44-4.73; to aOR, 18.87; 95% CI, 17.87-19.93) than children not identified as CMC. Conclusions and Relevance In this study, open-source algorithms identified different cohorts of CMC in terms of prevalence and magnitude of risk, but all predicted increased health care utilization and in-hospital mortality. These results can inform research, programs, and policies for CMC.

Relying on data from the United States Census and the American Time Use Survey (2010–2017), we examine how residential segregation influences per capita discretionary time availability in Los Angeles, New York City and Miami. We find a sizable disadvantage of being Latinx for discretionary time availability. Non-Latinx Whites have 182 extra hours of per capita discretionary time per year than do Latinx individuals. Both within-neighbourhood and adjacent-neighbourhood influences matter. In most neighbourhoods, segregation is correlated with having more discretionary time. Individuals in highly segregated areas have approximately 80 more hours of discretionary time per year than those living in diverse areas. This suggests that in addition to socioeconomic, cultural and well-being benefits, ethnic enclaves may also impart temporal advantages. However, we find that there may be diminishing marginal returns with increasing segregation in surrounding areas. Sociodemographic characteristics explain over one-quarter of the variance between segregation and discretionary time availability.

Latinos in the U.S. are the least likely to have health insurance compared to other racial and ethnic groups. Mexican Americans, the largest subgroup of U.S. Latinos, have particularly great barriers to healthcare access, and experience disparities in care and in health outcomes. The Affordable Care Act (ACA), enacted in 2010 and mostly implemented by January 1st, 2014, was designed in part to improve health insurance access for uninsured groups, including an option for states to expand Medicaid. We assess the ACA’s effect on six health-related outcomes for Mexican American adults (18-64 years of age). We estimate a difference-in-differences models using the IPUMS National Health Interview Survey data; Mexican Americans living in the West are assigned as the treatment group (where ~97% of Mexican Americans live in states which expanded Medicaid) and the South as a control group (where ~4% of Mexican Americans live in states which expanded Medicaid). We designate 2010-2013 as the pre-treatment period and 2014-2018 as the post-treatment period. The results for the full sample suggest that Medicaid expansion increased Mexican Americans' probability of having: health insurance, a physician visit in the past year, and self-reported diabetes, chronic kidney disease, and hypertension; and decreased the probability of reporting self-assessed health of “very good” or “excellent.” Heterogeneity analyses suggest remarkably large gains for those who are men, foreign born, undocumented, with less than high school levels of education, with incomes less than 100% of the federal poverty line (FPL), and those who have lived more than 5 and less than 10 years in the U.S.

This paper uses newly digitized border crossing records from the early 20th century to study the destination choice of female and male French Canadian migrants to the United States. Immigrant sorting across destinations was strikingly different between women and men. Absolute returns to skill dominate in explaining sorting among men, while job search costs and access to ethnic networks were more important for single women. Married women were typically tied to a spouse whose labour market opportunities determined the joint destination, and were much less responsive to destination characteristics as a result.

This research utilises 648 monozygotic and 1016 dizygotic twins' socioeconomic outcomes observed in United States of America in 1995 to conduct a twin study on the intergenerational transmission of high-income status. The research is conducted as a unique method to address the prevalent debate of income inequality and intergenerational persistency of socioeconomic status in the United States of America. In recent history, there are increasing imparity of opportunities and income immobility in the US. Using the genoeconomical approach of a twin study, the variance of socioeconomic position is distributed into three factors: genetic factors, family/common environment, and unique environment. The findings of my study suggest that the variance in socioeconomic status cannot be solely contributed to genetic factors and rather unique environmental elements, yet there are portions of the tendency of high socioeconomic position that can be predominantly assigned to genetic factors. Furthermore, it can be concluded by accounting for different characteristics, such as gender, age, ethnicity, and educational level, that the intergenerational transfer of high-income status variates heavily depending on the subsegment examined, such that an African American female will experience significantly different mechanisms of the intergenerational transfer of socioeconomic status than a Caucasian male.