Job quality is important for worker well-being (Congdon et al. 2020). However, all occupations are not equal in quality, and quality employment is distributed unevenly by race and gender. This study uses occupational crowding methodology to better understand how this occurs and who is impacted. We conducted a review of major definitions of job quality across multiple fields to develop an organizing framework of the main elements of job quality. The main categories we identified were pay, hours, scheduling, benefits, job security, working conditions, on-the-job training, advancement, and worker voice. We then identified these job quality indicators in 108 occupations and developed a combined job-quality score. The average job-quality score was 5.8 out of a total possible score of 11 across the occupations,the most frequent total scores were 7 or 8, and few occupations were very below average.

Background: Menstruation is a normal biological process experienced by more than 300 million women globally daily. Women need clean menstrual absorbents that can be changed as often as needed in a private and safe place with proper hygiene and disposal facilities. All these needs must be met throughout the duration of the menstrual cycle. Access to menstrual needs of women is important for their health, well-being, and human dignity. This study assessed the prevalence and factors associated with unmet need for menstrual hygiene management (MHM) in Ethiopia, Kenya, Uganda, Burkina Faso, Ghana, and Niger. Methods: We used data from the performance monitoring for action (PMA) surveys. We defined the unmet need for MHM as “lack of resources, facilities, and supplies for MHM.” Sample characteristics were summarized using frequencies and percentages while prevalence was summarized using proportions and their respective confidence intervals (CI). Factors associated with unmet need for MHM were assessed using a multilevel logistic regression model. Results: In the six countries, the majority of women were aged 20-34 years, were married or cohabiting, and had never given birth. The prevalence of unmet need for MHM was high among the uneducated and multiparous women, those who reused MHM materials, practiced open defecation, and lived in rural areas in all six countries. The prevalence of unmet need for MHM was highest in Burkina Faso (74.8%) and lowest in Ghana (34.2%). Age, education level, wealth status, and marital status were significantly associated with unmet need for MHM. Reuse of MHM materials and open defecation increased the odds of unmet need for MHM. Conclusion: More than half of women in five of the six countries have an unmet need for MHM with odds of unmet need significantly higher among younger women, those with low wealth status, the unmarried, and those with poor access to sanitary facilities. This study highlights the state of period poverty in Sub-Saharan Africa. Efforts to end period poverty should approach MHM needs as a unit as each need is insufficient on its own.

How did the adoption of reform-style government affect socioeconomic inequality in U.S. cities during the Progressive Era? The conventional wisdom describes the reforms of this time as reflecting racist and nativist impulses and primarily benefiting white business owners. However, political science work offers theoretical reasons to expect more nuanced redistributive effects of reform. We study the impact of reform lever-aging deanonymized census records, newly digitized municipal budgets, and reform adoption dates across 455 U.S. cities during 1900-1940. Using a two-way fixed effects design, we document the impact of Progressive municipal government on the relative socioeconomic well-being of black, immigrant, and working-class residents compared to whites, natives, and business elites. We find that inequality increased only modestly in reformed cities, with no significant differences in public spending. Our results challenge the dominant narrative that the reforms of this era produced large increases in socioeconomic inequality.

BACKGROUND Segmented assimilation theory asserts that children born to immigrants experience divergent paths of incorporation. While some exhibit substantial gains in well-being, others may fare worse than US-origin whites or their own parents. It is certainly true that contemporary immigrants find themselves living in a different context than those who arrived in the United States during the early 20th century. However, it remains an empirical question whether the incorporation process has suddenly become segmented. METHODS We select five of the top European sending regions to ask whether socioeconomic outcomes varied between immigrant-origin populations between 1910 and 1930. We use the Integrated Public Use Microdata Series Multigenerational Longitudinal Panel to link men over a 20-year period. Logistic regression is used to predict probabilities of school enrollment in 1910 among US- and immigrant-origin youths. We then rely on a series of OLS specifications to predict the socioeconomic standing of these men in 1930 as well as differences in father–son status. We also compare relative rates of occupational mobility across country of origin. RESULTS We find evidence of intergenerational mobility as well as convergence in economic success. Though some immigrant-origin groups fare better than others (e.g., the Irish and those from the United Kingdom versus Italians and Germans), our results largely align with classical theories of assimilation. To the extent that segmented assimilation occurs, it emerges in the especially low levels of attainment among German-origin youths. CONTRIBUTIONS Our findings raise important questions about studies that investigate segmented assimilation among immigrant-origin youths. We argue that more work is needed to determine whether downward assimilation is a sign of permanent disadvantage or a shortterm consequence from which youths can recover.

The COVID-19 pandemic has changed the way time is allocated towards market and non-market activities. This paper looks at the effect of the pandemic on a key category of non-market activity – leisure. We use micro-data from the American Time Use Survey to see how the pandemic affected leisure in the United States. A seemingly unrelated regression system is deployed to examine how the pandemic affects various leisure activities such as television viewing, socialising, reading/writing, active sports, games, and computer use. Apart from socialising, which was actively discouraged during the pandemic, all major leisure activities saw an increase, which resulted in overall leisure going up in the Covid year 2020 by 5%, compared to 2019. However, the impact is statistically significantly different for different types of leisure activities. Active leisure is being consumed less while passive leisure is being consumed more – pointing towards an increased sedentarization of lifestyles. Since previous studies have shown passive leisure to be negatively associated with health, our result has important implications for the health and well-being of Americans, and if the trend continues, policymakers should actively incentivise the consumption of active forms of leisure.

The declining presence of children in the nation’s dense urban areas has been a matter of concern for years, and this trend has only continued since the 2020 pandemic. In light of this pattern, this report assesses the family-friendliness of more than 200 metro areas across the U.S., using a wide variety of data sources, including the Census Bureau’s 2017–21 American Community Survey. It discusses which places have the most children, where families with children choose to move, and how metros fare on measures of well-being such as educational achievement, social mobility, social capital, and child poverty.An accompanying data tool that I created allows readers to see how well each of these variables correlates with all the others.1 Cost of living emerges as an overwhelming theme of these correlations: the metros that are home to the most children, as well as the metros attracting the most family migration, do not strongly tend to be the ones with, for example, high educational achievement, low child mortality and homicide rates, and strong upward mobility. Some of these correlations are even in the “wrong” direction. Rather, the metros that are objectively attractive to families are the ones with low cost of living, including affordable housing and child care.This report also offers suggestions as to how cities and other levels of government might make urban living more attractive to families with children. The single biggest suggestion is to bring down the cost of housing by increasing supply, which is currently held back by intense zoning regulations. Major metro areas cannot compete directly with the combination of advantages that smaller ones boast—cheaper housing plus more space—but they certainly can make housing more affordable, continue to offer their own cultural and economic advantages (areas where smaller cities cannot compete), and make public spaces more accessible and friendly to children.

Green spaces have gained increasing urgency due to the global and local challenges resulting from rapid urbanization and environmental issues. This study specifically focuses on the design, management, and crucial significance of urban green spaces in Uzbekistan within the framework of sustainable development. Through the integration of diverse theoretical perspectives and interdisciplinary approaches, the study seeks to enhance biodiversity, facilitate wildlife movement, and promote environmental sustainability within urban green spaces. The research methodology employed in this study is robust, encompassing comprehensive data analysis, which provides compelling evidence of the positive impacts of green spaces on both physical and mental well-being. Moreover, the study establishes a clear correlation between the concept of nature-based solutions and the imperative to leverage the potential of nature to effectively address environmental challenges and achieve socioeconomic advantages. In addition, the study explores the role of geography in effectively addressing the opportunities and challenges associated with urban green spaces in Uzbekistan. Policymakers, researchers, and practitioners engaged in promoting sustainable urban development can draw valuable insights from this study. The findings underscore the critical importance of adopting a multidimensional approach to urban planning to foster the development of sustainable and livable cities. By implementing the recommendations outlined in this study, Uzbekistan has the potential to enhance its green spaces and successfully tackle pressing environmental challenges. Consequently, this study fills a significant research gap by highlighting the pivotal role of geography in comprehending and addressing the importance of urban green spaces. The findings align with the concepts of nature-based solutions and geography, offering actionable guidance for sustainable urban development in Uzbekistan.

The 2021 expansion of the Child Tax Credit (CTC) led to a historic reduction in poverty in the United States, particularly for children. Research showed that child poverty fell immediately and substantially. On an annual basis, according to the US Census Bureau, child poverty fell to its lowest level on record in 2021: 5.2 percent (Creamer et al. 2022). Moreover, the CTC benefit’s monthly delivery likely reduced volatility in income and poverty; research has shown that volatility compromises family and child well-being (Hamilton et al. 2022). The dramatic reductions in poverty induced by the expanded CTC represent positive changes to economic well-being. There are potentially larger and longer-run benefits from an increase in economic security for families with low and moderate levels of income (Garfinkel et al. 2022). Income supports enhance children’s lifetime social and economic outcomes by allowing families to meet basic needs and by increasing families’ income stability. Specifically, transfer programs that provide cash and near-cash supports have been shown to promote stronger educational, emotional, and health outcomes (Akee et al. 2018; Hardy 2022; Hardy, Hill, and Romich 2019; Hoynes, Schanzenbach, and Almond 2016; Rothstein and Wozny 2013). The 2021 expanded CTC extended full refundability to families with little or no taxable income. Adults with young children between 0 and 5 years old received refundable credits of $3,600 per child, while those with children between 6 and 17 years old received credits of $3,000 per child. These benefit changes allowed for more of the lowest-income families—historically, those from non-Hispanic Black, Hispanic, and American Indian and Alaska Native communities (Hardy 2022)—to benefit from the program (Center on Poverty and Social Policy at Columbia University, 2021). The Census’s Supplemental Poverty Measure (SPM) showed that children from all racial and ethnic minority groups experienced relatively large reductions in poverty rates, but that SPM poverty rates fell most dramatically for Black and Hispanic children. Black child poverty rates fell by 17 percentage points between 2009 and 2021, while SPM child poverty rates fell from 30 percent to 8 percent among Hispanic children over the same period (Creamer et al. 2022). But where in the country did the expanded CTC reduce child poverty the most? It is not obvious, for example, whether the expanded CTC would have reduced poverty more or less in higher- versus lowerpoverty states, or whether the degree of poverty reduction differed by the cost of living in states. Income distributions vary across states, as does the depth of poverty (i.e., how close or far families lie from the poverty line) within any given state. One well-established feature of federally administered transfer programs is that they tend to reallocate resources from higher-income states to lower-income states. And, importantly, states vary on cost of living, which is an often-underexplored driver of poverty. These differences across states are especially relevant today, given well-documented housing supply gaps and staggeringly high housing costs facing many families. On the one hand, some of the nation’s poorest states, disproportionately situated in the South, are among the least expensive. On the other hand, these same less-expensive states tend to provide weaker safety net protections and make lower investments in education; strong safety nets and higher investments in education are two core features of successful economic mobility strategies (Ziliak 2019). This essay investigates how the CTC affected child poverty across states. In our two primary analyses, we examine how the reduction in child poverty varies across two characteristics: state-level cost of living (high vs. low cost of living) and state-level poverty (high vs. low pretax/transfer poverty rates). We find that, although the CTC caused substantial reductions in poverty in each kind of state (i.e., high vs. low cost of living, high vs. low pretax/transfer poverty rates), poverty reductions were the highest in low-cost, highpoverty states, which are those states with a relatively lower cost of living and with a higher baseline poverty rate. It stands to reason that, when the expanded CTC sunset on December 31, 2021, those states were also where child poverty increased the most.

This dissertation explores several topics in welfare, well-being, and labor economics, with a focus on: (1) health, wealth, and racial and ethnic welfare inequality; (2) the natural environment and well-being; and (3) whether labor markets place a wage premia for jobs that require workers to consume disamenities. To achieve these goals, the study utilizes three distinct datasets and applies a range of machine learning and econometric techniques, including natural language processing algorithms, as well as dynamic panel data estimators, natural experiments, and microsimulations. In Chapter 1, titled “Beyond Income: Health, Wealth, and Racial/Ethnic Welfare Gaps Among Older Americans”, we estimate racial and ethnic disparities in well-being among the older U.S. population using an expected utility framework that incorporates differences in consumption, leisure, health, mortality, and wealth. We use longitudinal data from the Health and Retirement Study (HRS) supplemented with data from the Consumption and Activities Mail Survey (CAMS). Together, these provide a long and rich panel (1992- 2016) for our analysis. Our measure broadly indicates that racial and ethnic inequality is larger than suggested by other welfare metrics such as income or consumption. We also find health, mortality, and wealth gaps are important in explaining the level of racial and ethnic welfare inequality among the older Americans in our sample, with leisure playing a comparatively minor role. Our decomposition exercises show that a majority of the estimated welfare gaps are determined by age sixty initial conditions as opposed to racial and ethnic differences in dynamic processes after age sixty. Our morbidity counterfactuals further suggest that eliminating common heath risk factors such as hypertension or diabetes in late-life only marginally closes overall welfare gaps. These simulations suggest that policies aimed at closing racial and ethnic gaps in late-life may be more successful and efficient if targeted earlier in the life-cycle. In other words, outside of direct wealth transfers, it may largely be too late to target such interventions directly at older populations. In Chapter 2, titled “The Morning Advantage: Differential Returns to Sunlight Exposure on Well-Being”, we estimate the effect of sunlight exposure on well-being by mimicking a natural experiment that utilizes the transition to daylight savings time as an external shock to the reallocation of sunlight between the morning and evening induced by differences in sunrise and sunset times across space, and time. We combine a collection of geolocated and timestamped tweets from Twitter with Natural Language Processing algorithms to create a comprehensive panel dataset of well-being (2014-2022) for the United States. Our findings show that the returns to sunlight on sentiment are stronger in the morning than in the evening. These results contribute significantly to the ongoing debate about whether to continue or abandon the practice of daylight savings. Specifically, the positive turn of sentiment in the morning highlights the underappreciated benefits to human well-being. Therefore, the potential shifting to darker mornings and brighter evenings following the proposed Sunshine Protection Act may do more harm than good. In Chapter 3, titled “The Compensation of Conscience: Evidence from the U.S. Labor Market”, we investigate compensating differentials in the U.S. labor market related to the degree of moral compromise required in different occupations. Specifically, we explore whether jobs that require workers to compromise their moral values offer higher compensation to compensate for the disamenities that contradict their moral beliefs. To conduct our analysis, we utilize data from the National Longitudinal Survey of Youth 1997 (NLSY97) and supplement it with data from the Occupational Information Network (O*NET) job descriptor, which allows us to develop a continuous measure of moral index across occupations. This data provides a rich and extensive panel spanning from 1997 to 2017 for our analysis. Our findings, obtained through the use of two-ways fixed-effects and first-difference models, indicate that jobs that require workers to compromise their moral principles are associated with higher compensation. This suggests that there is indeed a compensating differential for engaging in disamenities that conflict with a worker’s moral values. Additionally, we observed that workers with a college education receive higher pay in jobs that require moral compromise, indicating that individuals with a college degree may have more employment opportunities and greater bargaining power, influencing their compensation preferences. Furthermore, we discovered evidence supporting an asymmetric relationship between changes in the occupational moral index and total hourly compensation. This relationship appears to be responsive to the intensity of moral compromise in the job.

Purpose Prior studies of cardiovascular health (CVH) disparities among immigrants of South Asian origin in the United States have examined South Asians as one homogenous group, focused primarily on Indian-origin immigrants, and examined risk at the individual level. Methods We present current knowledge and evidence gaps about CVH in the three largest South Asian-origin populations in the United States—Bangladeshi, Indian, and Pakistani—and draw on socioecological and lifecourse frameworks to propose a conceptual framework for investigating multilevel risk and protective factors of CVH across these groups. Results The central hypothesis is that CVH disparities among South Asian populations exist due to differences in structural and social determinants, including lived experiences like discrimination, and that acculturation strategies and resilience resources (e.g., neighborhood environment, education, religiosity, social support) ameliorate stressors to act as health protective factors. Results Conclusions: Our framework advances conceptualization of the heterogeneity and drivers of cardiovascular disparities in diverse South Asian-origin populations. We present specific recommendations to inform the design of future epidemiologic studies on South Asian immigrant health and the development of multilevel interventions to reduce CVH disparities and promote well-being.

I investigate the systemic problem of economic externalities from multiple angles with the goal of improving the way that we formulate, quantify, evaluate, and advance economic welfare and environmental sustainability.Externalities are costs (or benefits) that result from economic activities and transactions which are not paid (received)1 by those directly involved. Some aspect of the cost or harm is external to the direct parties, which means that the market price is lower than it would otherwise be, with some part being ‘paid’ by others, usually in the form of some harm suffered. An example is air or water pollution caused by a factory: the firm has direct costs (materials, equipment, infrastructure, labour etc) which it, and potentially its customers, pay, but downwind and downstream communities suffer negative health and quality of life impacts that are not part of the costs paid by the producer or the consumer.Externalities undermine the theoretical optimum and welfare maximizing function of competitive markets, fundamentally skewing outcomes and causing major harm as a result of economic activity. Without accounting for externalities, the profit maximising and cost minimising impetus of markets guarantees harm, because it is always cheaper to undertake activities wherein some of the costs are not paid by the firm, while the revenues are realised directly. Issues of sustainability can be understood as negative externalities that impact the welfare of people in the future (Brundtland 1987).In my investigations, I generate novel analyses and tools for explaining, quantifying, and evaluating externalities. I complete assessments and analyses of the Genuine Progress Indicator (GPI) for California and the United States, and suggest improvements to its methodologies. The GPI is a macroeconomic indicator that incorporates assessments of a number of significant externalities in order to construct a more comprehensive measure of welfare. I produce a cross-sectional analysis of the Ecological Footprint (EF) efficiency in national welfare provision. EF measures the anthropogenic draw on renewable biological resources, the externality of unsustainable impact on natural resources. Finally, as a foundation for ongoing work examining externalities and related policy questions, I build an open source and free software package, MPSGE.jl, that facilitates easier Computer General Equilibrium (CGE) modelling. The equilibrium framework of CGE models lends itself to applications accounting for externalities, such as the imposition of Pigouvian taxes2.1 While there are both negative and positive externalities, in general I will default to the negative case for discussion throughout for readability, unless explicitly described otherwise. 2 Pigouvian taxes and subsidies (Pigou 1920) imposed and provided by the government, can adjust market prices to incorporate the externality cost, to more fully reflect and optimise social welfare.My GPI work, presented in Chapters 1 and 2, includes calculating and analysing the GPI of California and the United States in order to measure truer social welfare over time, while I also analyse the indicator and its strengths and weaknesses.In Chapter 1, we estimate the GPI for California for a five-year period, 2010-2014. Within this relatively short time period, which includes the recovery from the Great Recession, we examine how inequality, nonmarket activities, and environmental degradation, affects the GPI of California. We also evaluate our estimation of the California GPI (CA-GPI) in two specific ways. First, we compare California’s GPI to an alternative indicator of social welfare, the Human Development Index (HDI) for California. Our comparison points to the GPI as a more holistic measure of sustainable economic well-being, although the HDI is useful in evaluating educational attainment, life expectancy, or earnings across regions or demographic groups in the state. Second, we compare our estimation of CA-GPI to the California results from a GPI estimation for all fifty states for 2011, and evaluate how different methodological decisions and data selection affect the results. Comparison of the two GPI assessments shows how the use of region-specific data compared to scaled national data increases the accuracy of estimates. However, using data and methods that prioritizes standardization is essential for comparing the GPI across regions, though the trade-off is diminished regional accuracy. The chapter concludes with a discussion of the uses of the GPI to evaluate policies, and suggests fruitful steps forward. Chapter 2 argues that important improvements in the Genuine Progress Indicator can be made by directly calculating the loss of natural resources, the benefits of leisure, and adjusting for inequality using a global norm, rather than using local, historical benchmarks. Local benchmarking is an obstacle to the standardisation and comparability of the GPI. We provide alternative methods for the five components that have used benchmarking in the standard GPI. We present new empirical estimates for the GPI of the United States and California over the period 1995 through 2017, calculated with and without the alternative methods. Using the alternative methods, we show that some differences between the GPI of the U.S. and CA are artefacts of the benchmark methods. Implementing the alternative methods narrows the gap between the U.S. and CA GPI, as it reduces the U.S. environmental costs, and removes the artificial differential between the U.S. and CA in the cost of inequality. We find that the GPI provides insight into net welfare not reflected in GDP, both with and without the benchmarking methods. Overall, we suggest that the GPI can be significantly improved with these high priority revisions without changing the fundamental approach or theoretical framework.In Chapter 3, I present a novel data analysis and visualization that combines indicators of different of national welfare in conjunction with each country’s associated Ecological Footprint, generating a measure of Ecological Footprint Efficiency, that is, the efficiency in providing economic services while minimizing the externality of ecological impact. The Ecological Footprint (EF) measures humanity’s draw on renewable biological resources. I use a specific set of data from a model which tracks the EF through the global supply chain to seven categories of final consumption. Using that EF data enables a direct association with selected data from the Sustainable Development Goals Indicator (SDGI) tracking the quality of the welfare benefits, under each of the seven categories.In Chapter 4, I detail my research contribution in developing MPSGE.jl, a novel, open-source software platform to facilitate simpler, error-reducing, fast, and free Computable General Equilibrium (CGE) modelling. The package is an evolution of the Mathematical Programming System for General Equilibrium analysis (MPSGE, Rutherford 1987) in the open-source Julia programming language. MPSGE.jl provides free and open-source access to the succinct-form model-construction functionality of its predecessor, and provides additional features such as an algebraic print of the model equations and easy integration with the growing ecosystem of other packages in the Julia programming language. I describe the package’s structure and use, and illustrate its benefits as part of a general-use and increasingly popular scientific programming language with an application. I use Monte Carlo methods to perform sensitivity analyses on a variety of parameters within a national model of the United States, and generate visualisations of the results with a standard plotting package.

We examine how the availability of prescription opioids affects labor market activity and household economic well-being. While greater access to opioids may lead people to substance use disorders and negative economic consequences, appropriate pain medication may allow some individuals to effectively participate in the labor market. We study prescription drug monitoring programs (PDMPs), which were designed to curb inappropriate opioid prescribing and assess how these policies affected labor force attachment and credit outcomes. We use variation across states in the timing of implementation of PDMPs and recent methods developed for difference-in-difference event study designs with multiple time periods. In line with previous work, we find that PDMPs lead to a decline in opioid prescribing rates. Although we find that these reductions in opioid supply have no clear effect on measures of labor force activity in our pooled sample, we see some suggestive evidence of negative effects on labor force attachment in states where there is less scope for substitution to illicit drugs. We also show that PDMPs lead to a decline in credit scores and increases in the number and amount of third-party debt collections, and that these effects are more pronounced in states lacking an illicit market. These findings suggest that some individuals are likely negatively affected by the lack of access to pain medication due to the PDMP laws.

While many people are having conversations about the state of the American health ecosystem, its challenges, and potential solutions, most of these conversations only focus on a single ecosystem component. Further, assessments of health and healthcare often fail to examine the critical role of mental health in overall well-being. Rios Partners’ Health of Health report aims to provide a holistic assessment of the US health ecosystem. The 2023 edition takes advantage of trusted data sources to assess the state of US physical and mental health through four pillars. Representing the demand side of healthcare, this pillar includes metrics measuring the treatment individuals receive (or do not receive) and their associated health outcomes. Representing the supply side of healthcare, this pillar includes metrics measuring healthcare’s human resources and physical infrastructure. – Representing the funding structures of the healthcare system, this pillar includes metrics measuring the cost of healthcare and who pays for it. Representing innovations in healthcare, this pillar includes metrics measuring investment in new technologies and actions taken to improve healthcare delivery.

Many Illinois households are eligible for safety net benefits that can help to improve their economic well-being. However, many of those eligible for benefits do not receive them. Program changes and new outreach strategies could help safety net programs reach more families and children, but designing the best interventions requires knowing more about who receives and does not receive assistance. Further, answering that question at the national level isn’t sufficient, because every state has a unique set of policies and implementation approaches, as well as a different starting point in terms of the portions of eligible families currently receiving various benefits. This analysis provides a snapshot of safety net eligibility and program participation rates in Illinois, combining estimates of the numbers of people eligible for benefits in Illinois with actual data on benefit recipients.We provide eligibility and participation rate estimates for seven programs—Temporary Assistance for Needy Families (TANF), Supplemental Security Income (SSI), the Supplemental Nutrition Assistance Program (SNAP), the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC), Public and Subsidized Housing, the Child Care and Development Fund (CCDF), and the Low Income Home Energy Assistance Program (LIHEAP)—and we provide eligibility data for an additional program, the Earned Income Tax Credit (EITC). The analysis rests on detailed estimates of program eligibility produced by the Urban Institute’s ATTIS (Analysis of Transfers, Taxes, and Income Security) microsimulation model.

Policies supporting families with young children provide an important context for human development. The two primary public policies available to caregivers around and after childbirth are parental leave and early care and education (ECE). A substantial body of research evaluates the effects of parental leave and ECE policies on various outcomes, but most existing studies focus on average treatment effects in the population. We know much less about how policy effects vary by family demographics or by child care program characteristics. The three studies in this dissertation aim to increase our understanding about the circumstances under which child and family policies are more or less effective in supporting families with young children. Study 1 documents maternal wage dynamics around childbirth and their heterogeneity by education using German administrative data. Women with low education experience a smaller drop and a faster recovery of their wages than women with higher levels of education. These differences are largely explained by the fact that women with low education have their first child at a younger age. To investigate whether public policies can influence these wage dynamics, I exploit a paid family leave policy change in 2007 to set up a differences-in-regression- discontinuities design. The policy change shortened the duration of monthly benefit receipt, increased the amount of monthly transfers, and encouraged secondary caregivers to spend at least two months on leave. I find suggestive evidence that the policy did not have an effect on wage loss after childbirth for women with high education. Women with low education earn a larger share of their pre-birth wage in the second year after childbirth under the new policy regime. This is most likely because they return to work faster. My results suggest that the policy change only influenced labor market behavior of mothers with economic constraints. Study 2 provides novel insights into ECE access by using a new indicator: distance traveled for child care. It documents trends in how far families travel to access care in the United States by neighborhood income using geographic mobility data for 2019 for n = 106,916 child care programs. The findings indicate that distance traveled follows an inverted U-shaped pattern. Families who live in the lowest and highest income neighborhoods tend to travel less for child care than families in the middle of the income distribution. In a case study examining the state of Illinois, the pattern is consistent with the physical availability of child care. Findings are discussed in terms of how distance traveled as an indicator can help define the child care market and its implications for early childhood policy. Study 3 focuses on the effect of ECE on parental outcomes. In this paper, coauthored with Professor Terri Sabol, we use family stress theory to argue that the financial and logistical burden of paying for and managing child care arrangements can act as repeated stressors in families’ lives, and may negatively influence parental mental well-being. We examine whether the provision of free and high-quality early care alleviates these stressors and leads to better parental health and well-being. We use data from the Head Start Impact Study, a nationally representative randomized controlled trial from the early 2000s, to answer the research question. Next to documenting the average effect of offering Head Start on parental well-being, we also explore heterogeneity in these effects by program characteristics, including family-centered services and supports in a program. The three studies in this dissertation inform our understanding of how birth-to-5 child and family policies influence lives of families with young children within two different national contexts, Germany (with high public funding) and the United States (with lower public funding). Moving beyond documenting average effects, they showcase how policy impacts vary by family demographics and child care center characteristics. These insights contribute to policy design and could help researchers, practitioners, and policy makers to work together to build policies that better support families with young children

SUMMARY Chapter 1: The Effect of WWI Military Service on the Long-Term Outcomes of Immigrants Military service has a long-lasting impact on mental, physical, and socioeconomic well-being. Although previous research has concentrated on the effect of military service on the native-born population, military experience may have different effects on immigrants through improving English language skills, fostering social interactions with natives, and providing a faster path to U.S. citizenship. I use historical Census data and an instrumental-variables approach to analyze the effect of WWI military service on the long-term outcomes of immigrants. The instrument reflects the likelihood of being drafted based on two characteristics: age at the time of the draft and being born in a country classified as an enemy of the U.S. during WWI. I find that foreign- born WWI veterans were more likely to become naturalized citizens and work in protective services, but veterans earned less after the war than their non-veteran peers. Chapter 2: My Brother and Me: The Consequences of Being Foreign-Born Immigrant children represent a significant share of the U.S. population. However, foreign- born children are often disadvantaged compared to their native-born peers due to differences in language skills, schooling, and cultural integration. I use historical Census Data to analyze the differences in schooling and labor market outcomes between U.S.-born and foreign-born siblings to understand the long-term effects of nativity. Children observed in the 1910 decennial Census are linked to their 1940 Census records using a unique method of linking individuals across Census waves. Compared to their native-born siblings, those born abroad are 10.5, 4.1, and 1.7 percentage points less likely to complete eighth grade, high school, and college respectively. The effects are larger for children who arrived at older ages. I do not find a significant impact on wages, employment, and other labor market outcomes. These findings indicate that foreign-born status is a significant determinant of long-term outcomes of children. Chapter 3: Exploring the Impact of Local Media Coverage on Ethnic Arrest Disparities with Ashley Muchow U.S. media coverage linking immigration with crime has proliferated over the past three decades at the same time local law enforcement officers have assumed important roles in immigration enforcement. While scholarship has demonstrated the ability of media to shape public opinion on immigration, relatively little research has empirically assessed its effect on policing practice. We use novel data on local television newscasts on immigration and crime and agency-level arrest data from the National Incident-Based Reporting System from 2009 to 2016 to examine whether such coverage increases Hispanic-White arrest disparities. Given the endogenous nature of local news, we use Sinclair Broadcast Group acquisitions as an instrumental variable to isolate the effect of news coverage on arrest differences. We find that news coverage increases ethnic arrest disparities for drug crimes but has no discernible impact on arrest differences for violent offenses. Supplemental analyses suggest that increases in Hispanic-White drug arrest rate disparities are more pronounced in areas served by sheriff departments and experiencing immigrant population growth. These findings demonstrate the potential for local news coverage to influence policing practice and highlight the scenarios under which such coverage may aggravate ethnic disparities in criminal justice contact.

Purpose Housing quality is associated with health and well-being; however, little research examines these factors by location. In this policy brief, we examine rates of two key housing quality indicators (having incomplete plumbing and incomplete kitchen facilities) by rural-urban location, as well as at the intersections of racial/ethnic identity and disability status.

Research on cross-sector differences has long demonstrated that workers in public and nonprofit sectors are more prosocially and intrinsically motivated, which in turn shapes their work behavior and outcomes, but little evidence exists on how public service employment is associated with workers’ life quality outside of the organizational context. Using cross-sectional data pooled from the Well-being Module of the American Time Use Survey, we investigate whether sectors of employment can predict workers’ subjective well-being (SWB) beyond the work domain. The results suggest public servants across all levels of government as well as nonprofit organizations experience higher life satisfaction than their for-profit counterparts. However, there are different patterns in daily experiential well-being across levels of government. Further analyses by work and non-work days demonstrate that work itself is likely to be a key factor affecting workers’ daily experience across sectors. Implications for theory and practice are discussed.

Household wealth data at the local level are generally not widely available, especially statistics disaggregated by race and ethnicity. Using machine learning, we estimate net worth and emergency savings data at the local, city, state, and national levels. We also disaggregate our estimates by racial and ethnic groups at the city, state, and national levels. We use machine-learning models trained on the Survey of Income and Program Participation (SIPP), a survey with detailed wealth information but too few observations for local estimates, to estimate emergency savings and net worth using the American Community Survey (ACS), which allows for state and local estimation. The imputations allow us to estimate the proportion of households with more than $2,000 in emergency savings and median net worth at the household level. We then aggregate household-level data to different geographic levels. Household wealth is a safety net. It protects families from unexpected expenses such as replacing a water heater and income shocks such as a jobless spell. Household wealth is also a springboard. It gives families the opportunities to invest in wealth-building opportunities like starting a small business or moving to an area with more opportunity. Understanding wealth is necessary for uncovering the barriers to wealth generation and designing policies that unlock opportunity for everyone. Two datasets, the Federal Reserve Board’s Survey of Consumer Finances and the US Census Bureau’s Survey of Income and Program Participation (SIPP), have detailed information about wealth and are typically used for national or state estimates (Bhutta et al. 2020). Unfortunately, little information is widely available about wealth at the local level, especially disaggregated by different racial and ethnic groups. This is because household surveys with adequate sample sizes for local estimation, such as the American Community Survey (ACS), do not include detailed information about wealth. We employ machine learning to leverage a smaller nationally representative survey with detailed questions about household wealth to impute household wealth onto the ACS, which allows for small area estimates. We released this novel dataset with the Urban Institute’s “Financial Health and Wealth Dashboard” in 2022. In particular, we use machine learning to estimate median net worth and the proportion of households with at least $2,000 emergency savings at the local level defined as Public Use Microdata Areas (PUMAs). We provide financial measures not only for a city, but also for subregions (Public Use Microdata Areas, or PUMAS) within many cities and for different racial and ethnic groups. City leaders and policymakers are able to use the dashboard to identify wealth disparities within cities. Because household wealth measures for subregions within cities are not typically available in public survey data, we use a machine-learning method to fill the gap in the existing survey data. We use household measures including net worth and emergency savings to better understand households’ wealth. Liquid assets—the sum of assets in checking accounts, stocks, bonds, and other liquid savings accounts—can indicate households’ resilience and ability to bounce back from financial shocks. Net worth—total assets minus total debt—can provide an overview of households’ economic well-being and their ability to pursue new opportunities. Overall, the 2022 financial health dashboard provides firsthand data and analysis to city leaders and policymakers for a better understanding of financial health, financial resilience, wealth, and debt within local regions in their cities and counties. They will also be able to compare their cities and counties with neighboring cities and counties. This works builds on previous asset and wealth imputation research. Using 2014 data, the Prosperity Now Asset Scorecard estimated the asset poverty rate, liquid asset poverty rate, and share of households with liquid assets for many cities in the US. The Federal Reserve Bank of “St. Louis’s Real State of Family Wealth”2 provides national-level average wealth for various demographic groups overtime. Using 2013 data, Ratcliffe and colleagues (2017) estimated the shares of unbanked and underbanked populations for different PUMAs in New York City. This project advances this literature by (1) looking at a broader set of asset outcomes; (2) estimating assets at the PUMA level throughout the country; (3) using more recent data than the literature; and (4) disaggregating the estimates by race and ethnicity when possible. Because PUMA boundaries are often smaller than city boundaries, our analysis sheds light on wealth disparities within cities.

Background: The extent of food deprivation and insecurity among infants and young children—a critical phase for children's current and future health and well-being—in India is unknown. We estimate the prevalence of food deprivation among infants and young children in India and describe its evolution over time at sub-national levels. Methods: Data from five National Family Health Surveys (NFHS) conducted in 1993, 1999, 2006, 2016 and 2021 for the 36 states/Union Territories (UTs) of India were used. The study population consisted of the most recent children (6–23 months) born to mothers (aged 15–49 years), who were alive and living with the mother at the time of survey (n = 175,614 after excluding observations that had no responses to the food question). Food deprivation was defined based on the mother's reporting of the child having not eaten any food of substantial calorific content (i.e., any solid/semi-solid/soft/mushy food types, infant formula and powdered/tinned/fresh milk) in the past 24 hours (h), which we labelled as “Zero-Food”. In this study, we analyzed Zero-Food in terms of percent prevalence as well as population headcount burden. We calculated the Absolute Change (AC) to quantify the change in the percentage points of Zero-Food across time periods for all-India and by states/UTs. Findings: The prevalence of Zero-Food in India marginally declined from 20.0% (95% CI: 19.3%–20.7%) in 1993 to 17.8% (95% CI: 17.5%–18.1%) in 2021. There were considerable differences in the trajectories of change in the prevalence of Zero-Food across states. Chhattisgarh, Mizoram, and Jammu and Kashmir experienced high increase in the prevalence of Zero-Food over this time period, while Nagaland, Odisha, Rajasthan and Madhya Pradesh witnessed a significant decline. In 2021, Uttar Pradesh (27.4%), Chhattisgarh (24.6%), Jharkhand (21%), Rajasthan (19.8%) and Assam (19.4%) were states with the highest prevalence of Zero-Food. As of 2021, the estimated number of Zero-Food children in India was 5,998,138, with the states of Uttar Pradesh (28.4%), Bihar (14.2%), Maharashtra (7.1%), Rajasthan (6.5%), and Madhya Pradesh (6%) accounting for nearly two-thirds of the total Zero-Food children in India. Zero-Food in 2021 was concerningly high among children aged 6–11 months (30.6%) and substantial even among children aged 18–23 months (8.5%). Overall, socioeconomically advantaged groups had lower prevalence of Zero-Food than disadvantaged groups. Interpretation: Concerted efforts at the national and state levels are required to further strengthen existing policies, and design and develop new ones to provide affordable food to children in a timely and equitable manner to ensure food security among infants and young children. Funding: This study was supported by a grant from the Bill & Melinda Gates Foundation INV-002992.