The average human capital of an ethnic group is a major factor in the economic outcomes of future generations. Naturally, there are variations in skills within ethnic groups across geo- graphic settlements. Therefore, variations in skills across settlements of the same ethnic group can explain divergent outcomes within ethnic groups. In this paper, I investigate the interplay between the average skills of an immigrant group, termed general ethnic capital (GEC), and local measures of skills for that immigrant group, termed local ethnic capital (LEC). I first link foreign-born males observed in the 1920 and 1940 full-count US censuses using a probabilistic machine learning method. Using these linked records, I analyze the interplay between GEC and LEC. While GEC remains a significant factor, LEC is a major determinant in the intergenera- tional economic mobility of immigrants. I find that a one-unit increase in LEC is associated with a 0.14 to 0.28 standard deviation greater occupation income score, an 8 to 11 percent increase in wage and salary income, and a 10 to 16 percentage point increase in the likelihood of high school completion.

The 1896 presidential election between William Jennings Bryan and William McKinley has new salience in the wake of the 2016 presidential contest. We provide the first systematic analysis of presidential voting in 1896, combining county-level returns with economic, financial, and demographic data. We show that Bryan did well where interest rates were high, railroad penetration was low, and crop prices had declined. We show that further declines in crop prices or increases in interest rates would have been enough to tip the Electoral College in Bryan’s favor. But to change the outcome, the additional changes would have had to be large.

Long-run wage stagnation for lower-wage workers—and rising inequality between high- and middle-wage workers—seems to indicate a modern labor market in which many workers have little bargaining power. In the middle of the 20th century, more than 30 percent of U.S. workers were members of a union: a core institution that provides workers with bargaining power. Today, after a long decline that took place almost entirely within the private sector, just 10.5 percent of workers (and 6.4 percent of private sector workers) are union members. We find that the decline in private sector union membership has been driven by falling union density both within industries and within states, with a smaller role for shifting industry composition. The decline in union membership is economically important: unions lift wages, reduce inequality, and shape how work is organized, among other effects. We examine options for reinforcing enterprise-level unions as well as other models for collective bargaining and enhanced worker voice.

The Washington region faces serious housing challenges that undermine the well-being of many residents. Regulatory constraints on how much new housing can be built, what types of housing are added to the stock, and where that housing is located limit production and increase its cost. Constrained housing supply, coupled with regional growth, pushes up rents and prices for existing housing. These pressures cause especially steep housing cost increases and displacement in some communities that have historically been home to people with low and moderate incomes and people of color.

Study Objectives To document trends in self-reported sleep duration for the noninstitutionalized U.S. civilian population from 2004 to 2017 and examine how sleep trends vary by race/ethnicity. Methods We use data from the National Health Interview Survey (NHIS) for U.S. noninstitutionalized adults aged 18–84 from 2004 to 2017 (N = 398 382). NHIS respondents were asked how much they slept in a 24-hour period on average, which we categorized as ≤6 hr (short sleep), 7–8 hr (adequate sleep), and ≥9 hr (long sleep). We used multinomial logistic regression models to examine trends in self-reported sleep duration and assess race/ethnic differences in these trends. Our models statistically adjusted for demographic, socioeconomic, familial, behavioral, and health covariates. Results The prevalence of short sleep duration was relatively stable from 2004 to 2012. However, results from multinomial logistic regression models indicated that there was an increasing trend toward short sleep beginning in 2013 (b: 0.09, 95% CI: 0.05–0.14) that continued through 2017 (b: 0.18, 95% CI: 0.13–0.23). This trend was significantly more pronounced among Hispanics and non-Hispanic blacks, which resulted in widening racial/ethnic differences in reports of short sleep. Conclusions Recent increases in reports of short sleep are concerning as short sleep has been linked with a number of adverse health outcomes in the population. Moreover, growing race/ethnic disparities in short sleep may have consequences for racial and ethnic health disparities.

The study of intergenerational mobility was once viewed as a quintessentially sociological topic that was widely investigated using occupational mobility tables. However, the popularity of occupational mobility tables seems to be rapidly dwindling. This change is associated with the increasing popularity of the economic approach to modeling intergenerational mobility which is not encumbered by the shortcomings of occupational mobility tables. The first limitation of the latter is the contextual nature of occupation which provides an increasingly imprecise indicator of the individual’s earnings or other socioeconomic outcomes. The second limitation is the lack of focus on long-term earnings and the continued reliance on cross-sectional data in an era of increased labor market volatility. The third limitation is the dubious practice of partitioning mobility into structural-mobility versus circulation-mobility and focusing on primarily the latter to make generalizations about the level of social fluidity in society. The fourth limitation is the failure of occupational models to discern important . . .

Human mobility, both short and long term, are important considerations in the study of numerous systems. Economic and technological advances have led to a more interconnected global community, further increasing the need for considerations of human mobility. While data on human mobility are better recorded in many developed countries, availability of such data remains limited in many low- and middle-income countries around the world, particularly at the fine temporal and spatial scales required by many applications. In this study, we used 5-year census-based internal migration microdata for 32 departments in Colombia (i.e., Admin-1 level) to develop a novel spatial interaction modeling approach for estimating migration, at a finer spatial scale, among the 1,122 municipalities in the country (i.e., Admin-2 level). Our modeling approach bridges a significant gap in the availability of migration data at administrative unit levels finer than those at which migration data are typically recorded. Due to the widespread availability of census-based migration microdata at the Admin-1 level, our modeling approach opens up for the possibilities of modeling migration patterns at Admin-2 and Admin-3 levels across many other countries where such data are currently lacking.

The current study seeks to identify a possible connection between the consolidation and reorganization of public school districts and schools and state-level legislation throughout the United States from 1993 through 2012. A mixed methods approach was utilized. Quantitative analysis of statewide public school district data identified states exhibiting downward trends in total numbers of schools and districts while enrollment increased or remained consistent. Nine Downward Trending States (DTS) were identified: Alaska, Arkansas, California, Illinois, Kansas, Nebraska, Oklahoma, Oregon, and South Carolina. Specific terms were used to search state legislature websites of the DTS to identify legislative actions potentially connected to consolidation and reorganization. Search terms utilized were: public schools, districts, consolidation, reorganization, funding, taxes, facilities, enrollment, construction, cost, and transportation. Major findings include 138 legislative actions potentially connected to consolidation and reorganization in these states. Qualitative analysis of the identified materials classified all legislative actions into one of three categories based upon how these actions pertained to districts and schools from financial, procedural, and structural standpoints. Few bills were passed into law and this study found no authentic connection between state legislation and public education consolidation and reorganization. Recommendations for further study include analysis of state-level historical/political actions in DTS, examination of changes in local politics, changes in population, changes in industry, etc. in towns, municipalities, and counties in relation to school and district consolidation and reorganization, and analysis of student performance in DTS during the 1993-2012 time of consolidation and reorganization.

Among people under 30 years old, drowning is one of the leading causes of death from unintentional injury. There are also striking racial disparities in drowning; in 1999 to 2010, the African American drowning rate was 1.4 times the white drowning rate and the American Indian/Alaska Native (AI/AN) drowning rate was 2 times the white drowning rate. The AI/AN rate is higher than both the African American and Latino drowning rate, but there is an alarming lack of research on AI/AN drowning. Of particular concern, while the overall drowning rate has declined nationally, in the last five years the female AI/AN drowning rate has spiked. In this project, we first seek to accurately describe the geographic patterns of AI/AN drowning rates. We then will identify what policies, practices, economic changes, and geographic factors are associated with the AI/AN drowning disparity, particularly the recent increase in AI/AN women who have drowned.

Research has found a meaningful income gap between males and females across several occupational settings, and this is also true within law enforcement. As more female workers enter the criminal justice system, it is important to revisit and update these patterns of gender inequality to account for the changing gender dynamics within this occupation. Using Current Population Survey data, we document the gender differences in pay among police over the past 28 years. Police officers experience income advantage compared with the general working population, but they also show a stable gender gap in pay. While this stable inequality is better than other public-sector jobs—which have experienced a growth in the gender pay gap—it represents a continued disadvantage for police women, despite the growing number of women working in law enforcement and the rules governing public-sector employment. We further decompose the gendered pattern in police pay by whether these individuals work for federal, state, or local agencies, and find that those working for state government show stark declines in the gender gap in pay while those working for local or federal agencies experience little to no change in this gender income inequality over time. We conclude with a discussion of the policy implications of our findings and directions for future research on gender inequality within law enforcement occupations.

Despite all efforts in the past few decades, the pace of male-female wage convergence was very slow. San Francisco Bay Area as an advanced, culturally diverse and a pioneer socioeconomically metropolitan suffers from male-female wage discrimination. It is the purpose of this study to estimate the average extent of discrimination against female workers in the Bay Area and to provide a quantitative assessment of the sources of wage inequality using Blinder-Oaxaca decomposition. The results indicate that influencing factors such as education, marital status, and work experience are rewarded differently between men and women. Additionally, the major portion of the wagegap remains unexplained with human capital characteristics.

Why do high-income black households live in neighborhoods with characteristics similar to those of low-income white households? We find that neighborhood sorting by income and race cannot be explained by financial constraints: High-income, high-wealth black households live in similar-quality neighborhoods as low-income, low-wealth white households. We provide evidence that black households sort across neighborhoods according to some non-pecuniary factor(s) correlated with the racial composition of neighborhoods. Black households sorting into black neighborhoods can explain the racial gap in neighborhood quality at all income levels. The supply of high-quality black neighborhoods drives the neighborhood quality of black households.

Better access to reproductive healthcare increases women's propensity to become entrepreneurs. Access correlates positively with female entrepreneurial activity and negatively with female entrepreneurial age. Examining firm size and personal income suggests it also improves survival and success of female-led businesses. None of these results hold when tested on men, women above 40, or other placebo professions. To establish causality, I exploit the Roe v. Wade landmark decision, the staggered enactment of state laws restricting abortion providers, and an index tracking state-level regulation of reproductive care. All three analyses suggest that policies securing better reproductive care enable more women to become entrepreneurs.

This dissertation explores three topics in labor economics related to labor market inequality. In the first chapter, I provide updated estimates of black-white gaps in earnings, education, and employment. My estimates are the first to account for the substantial non-reporting of black men to household based surveys. I first demonstrate that previous estimates of the undercount are understated and provide estimates of the undercount of black men that are robust to under-coverage in vital statistics data. I then use variation in incarceration rates to show that 90 percent of the incarcerated population would have been non-reporting had they not been incarcerated. I argue that this suggests that non-reporting is almost entirely driven by the population at risk of incarceration. I then use data on labor market outcomes of inmates prior to incarceration to show that accounting for non-reporting meaningfully increases estimated gaps in black-white educational attainment, unemployment rates, and annual earnings. In the second chapter, I analyze the career effects of inducing single mothers into employment through welfare reform. Using the Survey of Income and Program Participation matched to Social Security Administration earnings data, I compare the career trajectories of a cohort of single mothers in 1984, before the major impacts of welfare reform, to a cohort of single mothers in 1998. Women in the 1998 cohort have higher labor market participation rates but the effect is not sustained once their children reach age 18. I develop a likelihood weighting technique with which I identify the single mothers who were most likely to be marginal employees. I find that 24 percent of marginal employees reach $25,000 annual earnings. Women who obtained administrative jobs experienced greater earningsgrowth. In the final chapter I analyze the impact of changes to funding for State Mental Health Agencies (SMHAs) on incarceration. SMHAs provide services for mental illness including services directly targeting people with mental illness in the criminal justice system. I find that cutting SMHA funding by one percent leads to a .2 percent increase in admissions to state prisons. I then show that this is primarily driven by impacts on reincarceration and sentencing.

The literature on Hispanic immigrant health and disability has primarily focused on Mexicans – the largest foreign-born population in the US. Relatively little is known about disability by country of origin among the growing population of “Other Hispanics.” Using representative data from ACS 2012-2016, we compare Mexicans to Cubans, Dominicans, Ecuadorians, Guatemalans, Peruvians, Salvadorans and island-born Puerto Ricans and with US-born populations. Hispanic immigrants tend to have lower rates of disability than US-born populations and non-Mexicans are generally found to be less likely to have a disability than foreign-born Mexicans. For example, Colombian women (men) are 1.9 (1.9), Guatemalans 2.0 (3.9), Peruvians 4.4 (2.0), and Salvadoran women (men) are 1.5 (3.2) percentage points less likely to report being disabled than Mexicans. The heterogeneity across Hispanic immigrants by country of origin is partly accounted for by differences in age and socio-economic status, as Mexicans tend to be younger and less educated.

This study investigates the extent to which job process automation, which has resulted in wage inequality and job polarization in the USA and has affected US interstate migration over the past two decades. The level of automation in each state is calculated using data on the degree of automation of each occupation. In particular, this study examines how the difference in the levels among states explains the movement of migrants. The results show that people move to states with more automation in skilled occupations and less automation in unskilled occupations. This finding implies that automation has a complementary (substitution) effect on skilled (unskilled) occupations. The results also show that the former effect is larger and more robust than the latter one. Further analyses use migration flow data classified into several subgroups and find that both skilled and unskilled workers in most occupations move to states with more automation in skilled occupations and less automation in unskilled occupations.

The nonprofit Urban Institute is a leading research organization dedicated to developing evidence-based insights that improve people's lives and strengthen communities. For 50 years, Urban has been the trusted source for rigorous analysis of complex social and economic issues; strategic advice to policymakers, philanthropists, and practitioners; and new, promising ideas that expand opportunities for all. Our work inspires effective decisions that advance fairness and enhance the well-being of people and places.

Over the past 50 years, the United States has experienced major shifts in geographic mobility patterns among its highly-educated citizens. Some states today are keeping and receiving a greater share of these adults than they used to, while many others are both hemorrhaging their homegrown talent and failing to attract out-of-staters who are highly educated. This phenomenon has far-reaching implications for our collective social and political life, extending beyond the economic problems for states that lose highly-educated adults. This report describes what this so-called “brain drain” looks like across the 50 U.S. states. We use data from the 1940 through 2000 decennial censuses and the 2010 and 2017 American Community Surveys to measure brain drain in each state. We define a highly-educated “leaver” as someone in the top third of the national education distribution who resides in a state other than her birth state between the ages of 31 and 40. We then analyze brain drain using two measures: “gross” brain drain and “net” brain drain. Gross brain drain is defined as the share of leavers who are highly educated minus the share of adults who remain in their birth state (“stayers”) who are highly educated. Net brain drain is the share of leavers who are highly educated minus the share of entrants to a state who are highly educated. We find that brain drain (and brain gain) states tend to fall along regional lines, although there are a number of exceptions to this general rule. Overall, dynamic states along the Boston-Washington corridor (Massachusetts, New York, New Jersey, and Maryland), on the West Coast (California, Oregon, Washington), and in other parts of the country (Illinois, Texas, Colorado, Arizona, and Hawaii) are the best at retaining and attracting highly-educated adults. Meanwhile, states in northern New England (New Hampshire and Vermont), the Rust Belt (Pennsylvania, Ohio, Indiana, Michigan, Wisconsin, and Missouri), the Plains (North and South Dakota and Iowa), and the Southeast (West Virginia, Kentucky, Tennessee, South Carolina, Alabama, Mississippi, and Louisiana), as well as Delaware, fare the worst on both counts. We also find that most of the top-performing, brain gain states experienced improvements in terms of gross drain, net drain, or both from 1970 to 2017. On the other hand, many brain drain states, especially in the Southeast, have seen declining fortunes on one or both of these measures during this period. Others, including most of the Rust Belt states, have consistently faced high gross drain and net drain over the past half-century. Our report provides evidence that highly-educated adults flowing to dynamic states with major metropolitan areas are, to a significant extent, leaving behind more rural and post-industrial states. This geographic sorting of the nation’s most-educated citizens may be among the factors driving economic stagnation—and declining social capital—in certain areas of the country. If we are connecting less with communities and people who are different than us, we could be more likely to see adversaries among those in whom we might otherwise find a neighbor.

This report examines the gender and racial wealth gaps in Central Ohio, focusing on the causes and extent of these gaps as well as on promising strategies for addressing them. Drawing on multiple data sources— including national data on wealth, local and state data on women’s employment and economic status, an online survey and focus groups, and interviews with policymakers and program leaders—the report analyzes how wealth accumulation differs between women and men and how it differs among women along racial and ethnic lines, examining the obstacles that prevent women from accumulating wealth. It builds on the Institute for Women’s Policy Research’s longstanding report series, The Status of Women in the States, which has provided data on the status of women nationally and for all 50 states plus the District of Columbia since 1996. The Status of Women in the States publications use data from U.S. government and other sources to analyze women’s status across multiple issue areas. These reports highlight women’s progress and its lack and encourage policy and programmatic changes that can improve women’s opportunities. This report was funded by The Women's Fund of Central Ohio with additional funding from the NoVo Foundation.

At the beginning of the twentieth century, U.S. cities had greater mortality than its rural areas; by midcentury, this had reversed. The details of when, where, and for whom the urban mortality penalty reversed is not well known, largely because data to address those questions are limited. Here, we prevent new national and regional estimates of infectious mortality, divided by race, for urban and rural areas from 1922-1944. We show that, already in 1922, rural mortality exceeds or equals urban mortality. For whites, median urban and rural mortality are strikingly similar, in the country as a whole and in each region, across this entire period. For nonwhites, regional patterns differ: nonwhites evince a rural mortality penalty in the Midwest and West but an urban penalty in the South. These results speak to ongoing debates about the public health contribution to the mortality decline. At the beginning of the twentieth century, living in cities posed a greater risk of mortality than living in rural areas in the United States (Higgs 1973; Condran and Crimmins 1980; Haines 2001; Cain and Hong 2009). As one paper title summarized the situation heading in to the twentieth century: "Survival in 19th Century Cities: The Larger the City, the Smaller Your Chances" (Cain and Hong 2009). By midcentury, this had reversed (Haines 2001): the development of modern public health infrastructure meant that, for the first time in the historical development of cities, cities became safer places to live than rural areas. This reversal of the urban mortality penalty was driven by a reversal in where infectious diseases, in particular, were concentrated. Although this stylized history is well known, the details of when, where, and for whom the urban mortality penalty reversed is not well known, largely because data to address those questions are limited. Here, we prevent new national and regional estimates of infectious mortality, divided by race, for urban and rural areas from 1922-1944. These estimates are based on newly available data on deaths to detailed causes of death in each state, collected by the Department of Commerce at the time in the annual Vital Statistics.