Mixed evidence on the relationship between school closure and COVID-19 prevalence could reflect focus on large-scale levels of geography, limited ability to address endogeneity, and demographic variation. Using county-level Centers for Disease Control and Prevention (CDC) COVID-19 data through June 15, 2020, two matching strategies address potential heterogeneity: nearest geographic neighbor and propensity scores. Within nearest neighboring pairs in different states with different school closure timing, each additional day from a county’s first case until state-ordered school closure is related to 1.5 to 2.4 percent higher cumulative COVID-19 deaths per capita (1,227–1,972 deaths for a county with median population and deaths/capita). Results are consistent using propensity score matching, COVID-19 data from two alternative sources, and additional sensitivity analyses. School closure is more strongly related to COVID-19 deaths in counties with a high concentration of Black or poor residents, suggesting schools play an unequal role in transmission and earlier school closure is related to fewer lives lost in disadvantaged counties.

Background: Neighborhood-level characteristics, such as poverty, have been associated with risk factors for heart failure (HF), including hypertension and diabetes mellitus. However, the independent association between neighborhood poverty and incident HF remains understudied. Objective: To evaluate the association between neighborhood poverty and incident HF using a “real-world” clinical cohort. Design: Retrospective cohort study of electronic health records from a large healthcare network. Individuals’ residential addresses were geocoded at the census-tract level and categorized by poverty tertiles based on American Community Survey data (2007–2011). Participants: Patients from Northwestern Medicine who were 30–80 years, free of cardiovascular disease at index visit (January 1, 2005–December 1, 2013), and followed for at least 5 years. Main Measures: The association of neighborhood-level poverty tertile (low, intermediate, and high) and incident HF was analyzed using generalized linear mixed effect models adjusting for demographics (age, sex, race/ethnicity) and HF risk factors (body mass index, diabetes mellitus, hypertension, smoking status). Key Results: Of 28,858 patients included, 75% were non-Hispanic (NH) White, 43% were men, 15% lived in a high-poverty neighborhood, and 522 (1.8%) were diagnosed with incident HF. High-poverty neighborhoods were associated with a 1.80 (1.35, 2.39) times higher risk of incident HF compared with low-poverty neighborhoods after adjustment for demographics and HF risk factors. Conclusions: In a large healthcare network, incident HF was associated with neighborhood poverty independent of demographic and clinical risk factors. Neighborhood-level interventions may be needed to complement individual-level strategies to prevent and curb the growing burden of HF.

Objective This study examines whether—and if so how—gender composition of children matters for mothers' and fathers' well-being during parenting activities. Background Despite that parents interact with girls and boys differently and spend different amounts of time with them, scholars have paid little attention to how gender composition of children matters for parental well-being. Method The study assessed parental well-being during time spent with children, across four measures of subjective well-being (N = 16,140 activities, 8,621 parents), pooled across three survey waves (2010, 2012, and 2013) from the American Time Use Survey Well-being Module. Random intercept models were used to account for the multilevel structure of the data. Results For both mothers and fathers, gender composition of children was not associated with different levels of happiness or meaning while parenting. However, fathers reported greater stress parenting all girls and mixed-gender children (i.e., girl/s and boy/s at the same time) compared to parenting all boys. Mothers reported greater fatigue and stress parenting all girls, compared to parenting all boys. Controlling for activity type explained some of the stress patterns. Conclusion This study, which is contextualized in broader literature on gender stereotypes, interactional processes, and time-use, makes several contributions to research on gender, family, and health and identifies an important factor—gender composition of children—that helps shape mothers' and fathers' well-being while parenting.

The authors analyze the impact of a tax on sweetened beverages using a unique data set of prices, quantities sold, and nutritional information across several thousand taxed and untaxed beverages for a large set of stores in Philadelphia and its surrounding area. The tax is passed through at an average rate of 97%, leading to a 34% price increase. Demand in the taxed area decreases by 46% in response to the tax. Cross-shopping to stores outside of Philadelphia offsets more than half of the reduction in sales in the city and decreases the net reduction in sales of taxed beverages to only 22%. There is no significant substitution to bottled water and modest substitution to untaxed natural juices. The authors show that tax avoidance through cross-shopping severely constrains revenue generation and nutritional improvement, thus making geographic coverage an important policy decision.

This paper studies the labor market effects of both documented and undocumented immigration in a search model featuring non-random hiring. As immigrants accept lower wages, they are preferably chosen by firms and therefore have higher job finding rates than natives, consistent with evidence found in US data. Immigration leads to the creation of additional jobs but also raises competition for natives. Which effect dominates depends on the fall in wage costs, which is larger for undocumented than for legal immigration. The model predicts a dominating job creation effect for the former, reducing natives' unemployment rate, but not for the latter.

The COVID-19 pandemic has made clear the vital role women play in our economy and in the economic security of families, both nationally and in Florida. Now more than ever, lawmakers in Florida must do better to ensure all women and families have quality reproductive health care, safe workplaces, equal representation in government, and economic security. Women need policies that reflect their roles as providers and caregivers—roles that the COVID-19 pandemic has demonstrated are critical to the well-being of families, communities, and the economy. In Florida, mothers are the sole, primary, or co-breadwinners in 68.8 percent of families, and these numbers are higher for some mothers of color across the United States. The following policy recommendations can help support the economic security of women and families in Florida.

How much do administrative hassles matter for health insurance take-up, and what are the implications for who gets covered? Studying low-income health insurance enrollment in Massachusetts, we find that a modest hassle-a requirement to actively choose a health plan to get enrolled-leads to major reductions in take-up. An auto-enrollment policy that removes this hassle increases take-up by 30-50% and differentially enrolls young, healthy, low-cost individuals with lower socioeconomic status. Applying the evidence to a model of public program targeting, we argue that the classic measure of favorable targeting-whether an ordeal screens out people who need or value a program less-misses the fact that low-value types often incur much lower costs. Relative to subsidies, auto-enrollment has similar targeting properties but is 36-125% more cost-effective by avoiding new spending on inframarginal enrollees.

Between 2006 and 2015, approximately 16.2 million homes entered foreclosure, directly affecting nearly one in six American households (Hall et al., 2015). Yet, the consequences of foreclosure were not distributed evenly amongst all Americans. The foreclosure rate for Black Americans was 11%, compared to 6% for white people during the Great Recession (Hwang et al., 2015). Previous studies point to residential segregation as a driver of the disproportionate consequences of the crisis borne by minority communities. In Hennepin County, racial covenants were the first mechanized form of residential segregation. Written into property deeds, racial covenants prevented anyone who was not white from residing in or owning the home. By exploiting the exogenous shock of the 1948 Supreme Court ruling deeming racial covenants unenforceable, I employ a fuzzy regression discontinuity model to show that covenants impacted foreclosure outcomes during the financial crisis in the early 2000s. I find evidence that covenanted homes were 15% less likely to foreclose during the Great Recession.

Understanding the potential child care needs for parents who work early in the morning, evenings, nights, and weekends has become a growing concern for policymakers trying to make child care more accessible. Families working these nontraditional (NTH) schedules-defined here as anytime outside of 7:00 a.m. to 6:00 p.m. on weekdays-can face extra challenges finding child care, and the types of care they use are less supported by public funds (Adams et al. 2021a-c; Sandstrom 2018). Using data from the 2015-19 American Community Survey and 2016 Survey of Income and Program Participation, we estimated the potential demand for child care during these nontraditional hours (NTH). 1 Although parents of all types and income levels work NTH schedules, these schedules are much more common 2 among families who have faced structural barriers to employment, education, and good wages (Adams et al. 2021a-c). Research shows that people with lower incomes, who are Black and Latino, who have lower levels of education, and who are single parents face structural barriers to employment, education, and access to services. The pandemic has underscored these difficulties. It has deepened the child care crisis and heightened the nation's understanding of how race impacts families' risk and opportunities. In most states, children in families that have historically experienced these structural barriers are more likely to have NTH-working parents. Understanding which families are working NTH schedules allows policymakers to develop and implement policies that are equitable and meet different groups' needs.

This dissertation examines the relationship between financial resources and health outcomes. My first chapter estimates the impact of a conditional cash transfer program on the usage of health facilities during childbirth in Nepal. My second chapter explores the relationship between mother’s landownership and child health in Nepal. My third chapter analyzes the impact of housing wealth shocks on physical and mental wellbeing in the United States. In the first chapter, I examine the effects of the Safe Delivery Incentive Program in Nepal, a cash transfer program that reduced the costs of childbirth in a healthcare facility. Using a difference-in-differences design, I find that low-parity women in high Human Development Index (HDI) districts increased facility delivery by 8.6 percentage points. Despite larger cost reductions, low-parity women in low HDI districts did not increase facility delivery but increased delivery with skilled personnel by 5 percentage points. The impact in low HDI districts was driven by the program’s supply-side incentive, which paid health workers to deliver in facilities or homes. This program had no impact on high-parity women, who become eligible two years later. Pre-existing barriers such as poor infrastructure of roads and facilities, customs, liquidity constraints, and lack of program awareness limited the effectiveness of the program. In the second chapter, I provide empirical evidence on the relationship between mother’s land ownership and child health outcomes using data from Nepal iii Demographic and Health Survey 2001, 2011, and 2016. I employ a technique that uses selection on observable characteristics as a guide for selection on unobservable characteristics to estimate bounded treatment effects of land ownership. My results indicate that mother’s land ownership decreases the incidence of child underweight and stunted with estimates that are robust to selection on unobservables. I show that the improvements in child health driven by land ownership are concentrated in rural households and for women employed in agriculture. I also provide evidence that increases in women’s decision-making power upon access to land are significant drivers of the relationship between land ownership and child health. In the third chapter, we explore the causal relationship between wealth and health by using contemporaneous changes in housing prices. Employing data from Panel Study of Income Dynamics, we find that increases in housing prices have positive effects on the self-reported health of homeowners. We show that a $100,000 increase in housing price over four years increases the probability of being healthy by 1.3 percentage points and decreases the probability of being unhealthy by 0.3 percentage points. Housing wealth shocks also affect the incidence of more objective health measures, causing decreases in metabolic disorders and work-limiting disabilities. We show that market-level housing prices fluctuations drive these effects and that renters are unaffected by these changes. Heterogeneous analysis suggests that the estimated impacts of housing wealth shocks are larger for older adults in terms of work-limiting disabilities and self-reported poor health.

This Article empirically illustrates that red flag laws--laws which permit removal of firearms from a person who presents a risk to themselves or others-- contribute to a statistically significant decrease in suicide rates, but do not influence homicide rates. I exploit state-level variation across time in the existence of red flag laws between 1990 and 2018 and find that the existence of a risk-based law reduces firearm-related suicides by 6.4% and overall suicides by 3.7%, with no substitution to non-firearm suicides. Red flag laws are not associated with a statistically significant change in homicides rates. Policymakers should consider red flag laws an effective tool to prevent firearm-related suicide, one of the most prevalent preventable causes of death in the United States. In light of this evidence, red flag laws should be more politically successful in the current partisan environment than other forms of gun control legislation because of their targeted nature and potential to balance the interests of gun owners against the negative externalities of gun violence.

Objective: This study examines the association between psychological distress and Alzheimer’s disease mortality among US adults aged ≥45. Methods: We analyzed the Kessler 6-item psychological distress scale as a risk factor for Alzheimer’s mortality using the pooled 1997–2014 National Health Interview Survey (NHIS)- National Death Index (NDI) database (N = 265,089). Cox regression was used to model mortality as a function of psychological distress and sociodemographic and behavioral covariates. Results: The Alzheimer’s mortality risk was 97% higher (HR = 1.97; 95% confidence interval [CI] = 1.37, 2.84) in adults with serious psychological distress compared with those without psychological distress, controlling for sociodemographic covariates. The relative mortality risk remained statistically significant (HR = 1.49; 95% CI = 1.04, 2.13) after additional adjustment for smoking, alcohol consumption, health status, activity limitation, and body mass index. Discussion: US adults had significantly higher risks of Alzheimer’s disease mortality at higher psychological distress levels. These findings underscore the significance of addressing psychological well-being as a strategy for reducing Alzheimer’s disease mortality.

Corruption has been shown to affect a variety of observed human capital inputs, such as health status, school enrollment, and student dropout rates. However, to the best of our knowledge, the question of how corruption affects unobserved skills has received little attention. This study investigates the effect of corruption on unobserved human capital, measured from the earnings of immigrants, using the U.S. census data for the period 1980–2000. In the human capital model built in the paper, corruption enters the budget constraint of an individual as a cost of the accumulation of unobservable skills. Using data on immigrants and the theoretical model motivating an empirical analysis, the study reveals how corruption impacts the stock of human capital across countries. According to the prediction deriving from the empirical analysis, corruption has a negative effect on the stocks of human capital. The counterfactual findings using the calibrated model suggest that the elimination of corruption increases aggregate output by 18–21% on average.

Those who are not employed during their 50s – and who may not be candidates for working into their 60s – are frequently invisible in the working longer discussion. We bring these individuals back into the conversation by examining who is and is not working in their 50s, the stability of individuals’ employment in their 50s, and their likelihood of working into their 60s. We find that those who lack stable employment during their 50s are disproportionately nonwhite, women, and those without college degrees. While disadvantaged groups start from a lower base, employment rates fall by about 20 percentage points for all groups between ages 50 and 60. We also find that continuous employment during one’s 50s appears to be a critical foundation for working longer, but about half of Americans do not have continuous employment during their 50s. Policies that improve the quality and consistency of employment in late middle age may increase rates of working longer.

A measure of the irregularity of the boundaries of Urbanized Areas is presented. This irregularity is related to the extent of scattered development and urban sprawl. For all 486 Urbanized Areas in 2010, the index, ranging from 0 to 100, had a mean of 79 (very irregular) with the majority of areas clustering near this value. The distribution was skewed to the left with a smaller number of areas having index values approaching and even going below 50. Larger areas tended to have somewhat higher levels of irregularity. Urbanized Areas in the Northeast and South had the highest average irregularity while those in the West were lowest. For some large urban areas, the largest Urbanized Area does not encompass the full extent of what should be considered the urban area. A set of 59 large urban areas consisting of 1 or more Urbanized Areas is the focus of further analysis. The same patterns emerged with high irregularity, the distribution skewed toward the less irregular areas, and higher irregularity for areas in the Northeast and lower for those in the West. Irregularity increased with the land area of the urban area and was lower for areas growing more rapidly and for areas subject to barriers to the expansion of urban development. Population density was lower in more irregular areas and in a simple model, the irregularity index and population accounted for 2/3 of the variation in density.

In this paper, we investigate if there is any ethnic discrimination towards Hispanics in the labor market for the US and how Donald Trump’s involvement has affected it. By comparing the income of Hispanics with White-Americans with data collected from IPUMS between the years 2010-2019. We investigated the period before and after 2016 when he got elected as the new president for the United States. We looked further into his different statements against the Hispanic population and how that might have affected the Hispanics overall. This paper result was obtained through the difference in difference model with the help of our linear probability model. From this model, a different coefficient and a dummy variable were created to get a result with accuracy for this study. The results showed that the logarithmic income for both ethnicities has decreased over time, but just slightly. Furthermore, our results indicated no increased ethnic discrimination in terms of income during our given time interval. However, we could see a difference in educational attainment. Those with higher education earned more after 2016 than previous years, which goes for Hispanics and White Americans. We interpret the results by seeing no significant change in the Hispanic’s income level, meaning that Trump did not affect their income. However, we can conclude that there was an income gap before Trump's presidency started and that his time as president did neither increase nor decrease the gap between the two ethnicities in our research.

This dissertation consists of three chapters. In the first chapter, I analyze credible intervals for quantiles constructed using Bayesian bootstrap techniques and show that credible intervals constructed using the “continuity-corrected” Bayesian bootstrap (Banks, 1988) have frequentist coverage probability error of only O(n −1 ). In addition, I show that these “continuity-corrected” Bayesian bootstrap credible intervals achieve the same frequentist coverage probability as the frequentist confidence intervals of Goldman and Kaplan (2017), up to some error term of magnitude O(n −1 ). Furthermore, I demonstrate that credible intervals constructed using the “continuitycorrected” Bayesian bootstrap have less frequentist coverage probability error than those constructed using the Bayesian bootstrap (Rubin, 1981). In the second chapter, I investigate three strikes laws, which mandate sharply increased sentences for criminals who commit a specific number of felonies. Specifically, I analyze the effect of these laws on violent crime rates using municipal-level data from the FBI. I compare violent crime rates of border municipalities in states with differing treatment statuses using a difference-in-differences specification with a sample matched on pre-treatment outcomes. I find no statistical evidence that three strikes laws reduce violent crime rates. I rule out reductions in violent crime rates greater than 1.3% and reject the hypothesis that three strikes laws reduce violent crime rates at the 5% significance level. Additional analyses and robustness checks support my main findings. vii

Using the panel feature of the Current Population Survey, we examine how the employment status of people who were self-employed business owners (working at least 15 hours per week in the business) in February 2020 changed over the following year, the first year of the coronavirus pandemic. We find that, in February 2021: 41 percent were no longer business owners working at least 15 hours per week, a higher percentage than during the corresponding months in 2018-2019. Business closures were greatest between February and April 2020, when the closure rate far exceeded that of February-April 2018.

Stay-at-home fathers (SAHFs) face negative social stereotypes, and experience social stigma surrounding their role. These stereotypes and stigma may be unique to SAHFs, and may further be linked to negative feelings during social contact. This study examines differences in social contact and time alone experienced by SAHFs compared to stay-at-home mothers and parents of other work/caregiving statuses. Additionally, we analyze SAHFs’ subjective well-being when with their children, spouse, non-spouse adults, and when alone to more accurately capture the positive and negative valences of their experiences across social contact. Using individual-level time-use diaries from the American Time Use Survey (N = 35,959), a nationally representative sample, we find that compared to fathers working full time, SAHFs spent more time alone, more time with only their children, and less time with adults. SAHFs reported that this alone time was meaningful, not negative. They reported more happiness when interacting exclusively with children. These findings refute some common stereotypes that primary caregiving fathers only stay home with their children as a last resort, and further support the new fatherhood ideal that many fathers desire to be more actively involved in childrearing than prior generations of fathers were. Unfortunately, SAHFs reported significantly more sadness, more stress, and less happiness while interacting in a variety of contexts with adults, including higher feelings of sadness when spending time with a spouse. Connecting our work with past research, we believe these findings are best explained by either exclusion of SAHFs or increased salience of social stigmas felt by SAHFs in social situations with adults. These indicators of emotional well-being during social contact have important implications for parent physical and mental health.

Objective: To contextualize experiences of activities during the day and investigate whether the contour of the day is correlated with well-being during activities. Methods: Drawing on American Time Use Surveys, we employ sequence and cluster analyses to create distinct typologies of daily life patterns, and bivariate analyses to describe whether well-being across activities varies by these typologies. Results: We identified four typologies characterized by different primary activity of the day: leisure (22.7%), TV (22.4%), housework (47.5%), and work (7.5%). Individuals in the work and leisure clusters tend to report more positive well-being and individuals in the housework and TV clusters tend to report more negative well-being in experiences of activities during the day. We also found that well-being experiences in the same activity differed across individuals in the different typologies. Conclusion: Understanding the daily life patterns of older adults may be important, given its correlation with well-being during activities.