My dissertation focuses on understanding whether and how institutions, policies and norms lead to an inefficient allocation of human capital - with specific focus on marginalized individuals - and what kind of interventions can be used to reduce such inefficiencies. In Pink Work: Same-Sex Marriage, Employment and Discrimination, I analyze how the legalization of same-sex marriage in the U.S. affected employment levels among gay and lesbian couples. I compare same-sex couples living in different states over time to show increases in the individual and joint probabilities of being employed following the introduction of same-sex marriage in their state. I then provide empirical evidence suggesting that a decrease in discrimination towards sexual minorities was the driving mechanism. In my second dissertation chapter, I analyze the relationship between teacher demographic characteristics and student educational outcomes. In Why Does Teacher Gender Matter?, I show that the effect of high school math and science teacher gender on student interest and self-efficacy in these subjects becomes insignificant once teacher behaviors and attitudes are taken into account, thus pointing towards an omitted variable bias. Teacher beliefs about male and female ability in math and science – as well as how teachers treat boys and girls in the classroom – matter more than teacher's own gender. My last chapter reiterates my research philosophy of using state-of-the-art quantitative methods to analyze topics with important ramifications in the real world. Failing to graduate from high school has high individual and social costs. And yet, high schools in the U.S. tend to rely on few indicators in order to identify students at risk of dropping out. In Beyond Early Warning Indicators: High School Dropout and Machine Learning, I show that this parsimonious approach leads to identifying only a small subset of students who ends up dropping out. I show how schools can obtain more precise predictions by exploiting the available high-dimensional data jointly with machine learning techniques. I incorporate economic theory into machine learning: the algorithms are calibrated not by selecting an ad-hoc goodness-of-fit criterion, but by . . .

Latino/Hispanic children have substantially lower prevalence of neurodevelopmental disabilities (NDD) than other groups. The reasons for this appear to be complex, but are generally thought to be related to language barriers and lack of access to and utilization of healthcare services. Some researchers have examined these factors in Latino children with NDD, but none has examined whether these factors explain low prevalence of NDD in this population. This research uses nationally representative IPUMS-NHIS data to compare NDD prevalence in whites and Latinos and examines whether healthcare access and utilization as well as language barriers explain this disability disparity. The results show that healthcare access, healthcare utilization, and language barriers do not explain lower rates of NDD among Hispanic/Latino children. Cultural factors may be the reason for low NDD prevalence among Latino children in the United States.

Acceptance of mothers’ labor force participation is commonly considered evidence of support for gender equality. This approach overlooks perceptions of both men’s and women’s behavior in public and private spheres. Using Monitoring the Future surveys (1976–2014) to trace youths’ imagined division of labor arrangements, we show a more complicated picture of gender attitudes. Over this period, contemporary young people exhibited greater openness to a variety of division of labor scenarios for their future selves as parents, although the husband-asbreadwinner/wife-as-homemaker setup remained most desired. Using latent class analysis, we identify six configurations of attitudes: conventionalists, neo-traditionalists, conventional realists, dual-earners, intensive parents, and strong intensive parents. None of the configurations are gender egalitarian, showing equal support for both parents’ earning and care work. Race predicts preferences more than gender. By 2014, a greater proportion of young White people were classified as intensive parents while young Black people were more likely to desire a dualearner arrangement. Our findings suggest attitudes about divisions of labor are not necessarily tied to gender egalitarian principles, instead reflecting broader economic concerns about adequate income and parents’ time with children. Future research must distinguish acceptance of flexibility in dividing work and care responsibilities from gender egalitarian attitudes.

This paper develops a theory of large corporate headquarters’ location in post-industrial capitalism. It posits that human capital has become the primary factor in the location decisions of large corporate headquarters. It argues that such operations will locate in skilled cities that are also larger and globally connected. These hypotheses are tested using data from the Fortune 500 between 1955 and 2017. Count models are estimated to test the relative importance of human capital, population size and airport connectivity, alongside taxation and other factors identified in the relevant literature. The findings are consistent with the hypotheses.

Since taking office in 2017, President Trump has expanded interior immigration enforcement, made it easier for states and local governments to apprehend and detain illegal immigrants, and argued that building a wall is essential to reducing crime. These actions are largely based on the perception that illegal immigrants are a significant and disproportionate source of crime in the United States. This brief uses American Community Survey data from the U.S. Census to analyze incarcerated immigrants according to their citizenship and legal status in 2017. The data show that all immigrants—legal and illegal— are less likely to be incarcerated than native-born Americans relative to their shares of the population. By themselves, illegal immigrants . . .

The aim of this research is to utilize a novel approach called geographically weighted shift-share (GWSSA) analysis to estimate the degree and manner to which recent destination redevelopments have played a role in changing the characteristics of the nearby population and housing in Detroit between 1990 and 2010. The main benefit of geographically weighted shift-share analysis is that this technique isolates the local changes due to such projects while simultaneously controlling for the amount of the change expected for unrelated factors (e.g., the exodus of people leaving Detroit due to its overall negative reputation). Results suggest that such destination redevelopments in Detroit seem to be connected to a number of surprising positive local impacts during this period related to total population, 18-to-29-year-olds, non-Hispanic whites, employed civilians, unemployed civilians, households earning between $50,000 and $100,000 in annual income, total housing units, occupied housing units and vacant housing units.

The relationship between women and stability, if any, is a topic of much debate and research. Several large and influential organizations have all researched women’s effect on stability. Furthermore, several of these world organizations, the United Nations, in particular, have declared gender equality to be a driving force in promoting stability and conflict prevention. Due to the United States active involvement in conflict prevention in such regions as West Africa, research concerning the relationship between women and stability is of particular interest to the United States Africa Command. As such, this research applied Topological Data Analysis, combined with other machine learning algorithms, to Demographic and Health Survey Program data com- bined with Armed Conflict Location and Event Data so as to observe the relationship between women’s status and armed conflicts in the West African region. While this team did not observe any direct correlation between women’s well-being and stability - defined as a lack of armed conflict events - the chosen methodologies and data usage have potential implications for future research concerning stability and conflict.

Social and economic disparities between raciallethnic groups are a feature of the American context into which immigrants are incorporated and a key determinant of population health. We ask whether raciallethnic disparities in diabetes vary by nativity and whether native-immigrant disparities in diabetes very by race and over time in the United States. Using the 2000-2015 National Health Interview Survey, we estimate . . .

Human societies evolved alongside rivers, but how has the relationship between human settlement locations and water resources evolved over time? We conducted a dynamic analysis in the conterminous US to assess the coevolution of humans and water resources from 1790 to 2010. Here we show that humans moved closer to major rivers in pre-industrial periods but have moved farther from major rivers after 1870, demonstrating the dynamics of human reliance on rivers for trade and transport. We show that humans were preferentially attracted to areas overlying major aquifers since industrialization due to the emergent accessibility of groundwater in the 20th century. Regional heterogeneity resulted in diverse trajectories of settlement proximity to major rivers, with the attractiveness of rivers increasing in arid regions and decreasing in humid areas. Our results reveal a historical coevolution of human-water systems, which could inform water management and contribute to societal adaptation to future climate change.

Migration in North America is much more diverse than a single inward immigration flow; emigration from the United States has been growing numerically and in terms of the diversity of those leaving. Though exploration, description, and analysis of American emigration is largely absent from international migration literature, American citizens living abroad are important domestic political, social, and economic actors. The media promotes the idea of Americans in Mexico as retirees and in Canada as fleeing U.S. politics. Yet, the limited literature shows a disparity between how the media represents this group and more rigorous data-based emigrant profiles. This dissertation investigates this emigration flow, guided by research questions that: explore changes in demographic composition; examine the portrayal of American emigration in mass media; and compare the depiction of American emigration in secondary data to the narrative told by mass media.

The onset of the Great Recession (December 2007 - June 2009) has brought attention to the phenomenon known as NEETs--youth not in education, employment, or training. Coined in the UK and recognized by OECD countries, little attention has been given among population researchers in the U.S. Using data from the October Education Supplement of the Current Population Survey, the first aim of this investigation is to identify NEETs in the U.S. and situate the U.S. globally by answering the question: What is the prevalence of NEETs in the U.S. and how do we compare to other countries? Next, informed by research done in the UK, Australia, and Japan (among others), I seek to answer the questions: What micro and macro factors affect a young adult's risk of becoming a NEET? Further, is there an effect of the Great Recession on the incidence of NEETs in the U.S.?

Some have questioned the financial wisdom of homeownership and, especially,Black homeownership. This is understandable because the mortgage crisis dealtheavy blows to Black homeowners. One concern is that home values may not appre-ciate as much where Blacks purchase homes. We examine how Black homebuyersfared compared to White and Latino buyers in terms of home appreciation dur-ing the 2012 to 2017 recovery. We examine appreciation rates by race and ethnicityacross 15 metros. We then estimate the relationship between appreciation and therace and ethnicity of the homebuyer, as well as characteristics of the neighborhoodwhere the home is purchased. We find Blacks saw higher appreciation rates thanWhites in high- and medium-appreciation metros, but not in low-appreciation met-ros. We also find that in medium- and high-appreciation metros, buyers in raciallydiverse neighborhoods tended to see higher levels of appreciation. Also in higher-appreciation metros, those buying in lower-income neighborhoods tended to seehigher appreciation rates, while those in low-appreciation metros did not.

Moving to Opportunity (MTO) was a housing mobility program designed to investigate neighborhood effects, the influences of the social and physical environment on human development and well-being. Some of the results from MTO have been interpreted as evidence that neighborhood effects are not as strong as earlier evidence had indicated. This Commentary discusses new research suggesting that neighborhood effects are, on the contrary, as strong and policy relevant as suspected before the experiment. This Commentary also discusses why the interpretation of the MTO data is important: If neighborhood effects drive outcomes, then addressing racial inequality requires concerted efforts beyond ending racial discrimination.

This paper studies the cyclical behavior of job separation and the characteristics of matches between workers and jobs. We estimate a proportional hazard model with competing risks, distinguishing between different types of separations. A higher unemployment rate at the start of an employment relationship increases the probability of job-to-job transitions, whereas its effect on employment-to-unemployment transitions is negative. We then build a simple job-ladder model to interpret our empirical results. A model with two dimensional heterogeneity in match (job) characteristics has the same qualitative features as the data. Once the model is extended to include cyclicality in the offered match characteristics, it can fit the quantitative features of the data.

Spatially-explicit population projections by age are increasingly needed for understanding bilateral human–environment interactions. Conventional demographic methods for projecting age structure experience substantial challenges at small spatial scales. In search of a potentially better-performing alternative, we develop an empirically based spatial model of population age structure and test its application in projecting US population age structure over the 21st century under various socioeconomic scenarios (SSPs). The model draws on 40 years of historical data explaining changes in spatial age distribution at the county level. It demonstrates that a very good model fit is achievable even with parsimonious data input, and distinguishes itself from existing methods as a promising approach to spatial age structure modeling at the global level where data availability is often limited. Results suggest that wide variations in the spatial pattern of county-level age structure are plausible, with the possibility of substantial aging clustered in particular parts of the country. Aging is experienced most prominently in thinly populated counties in the Midwest and the Rocky Mountains, while cities and surrounding counties, particularly in California, as well as the southern parts of New England and the Mid-Atlantic region, maintain a younger population age structure with a lower proportion in the most vulnerable 70+ age group. The urban concentration of younger people, as well as the absolute number of vulnerable elderly people can vary strongly by SSP.

Some have heralded a resurgence of urban living in the U.S., particularly among young adults. Are Americans abandoning suburbs in favor of more urban lifestyles? What is the scope and scale of this urban resurgence? We develop a typology of neighborhoods to analyze the residential location of young and older U.S. adults from 2000 to 2011–15. Census and national travel survey data reveal that suburban population growth continues to outpace that in urban neighborhoods. Although young adults are more likely than older adults to live in urban neighborhoods, recent urban population growth is neither associated with suburban decline, nor being led by young adults. Significant recent population growth in the newest, suburban neighborhoods suggests that greenfield development remains the primary means to increase American housing supply. Shifting metropolitan growth from the suburban fringe would likely require expanding housing supply in urban neighborhoods, and bringing urban amenities to established inner-ring suburbs.

The Renewable Fuel Standard (RFS) is among the largest renewable energy mandates in the world. The policy is enforced using tradeable credits that implicitly subsidize biofuels and tax fossil fuels. The RFS relies on these taxes and subsidies to be passed through to consumers to stimulate demand for biofuels and decrease demand for gasoline and diesel. We study pass-through of the RFS subsidy for E85, a high-ethanol blend fuel, to retail fuel prices using weekly prices from over 450 fuel stations in the United States. We find that, on average, half to three-quarters of the E85 subsidy is passed through to consumers. However, pass-through takes 6–8 weeks, and station-level pass-through rates exhibit substantial heterogeneity, with the retailers’ market structure influencing both the speed and level of pass-through.

This paper investigates whether interracial contact in childhood impacts adult romantic relationships. We exploit quasi-random variation in the share of black students across cohorts within US schools. We find that more black peers of the same gender lead whites to have more relationships with blacks as adults. While we do not find impacts on labor market outcomes, there are significant effects on reported racial attitudes. Furthermore, an increase in meeting opportunities is unlikely to explain the increased interracial relationships, since the effect is persistent across time, space, and social networks. Overall, interracial contact during childhood has important long-term behavioral consequences.

Este estudo analisou a situação das famílias da cidade de Ponte Nova sob a perspectiva multidimensional nos de 1980, 1991, 2000 e 2012, a partir da metodologia adaptada de Barros, Carvalho e Franco (2003), tendo por base os microdados dos censos demográficos. Por meio do grande número de informações contidas na base de dados, tornou-se possível efetuar uma análise ampla que permite avaliar as condições de vida do domicílio. Em síntese, o índice de desenvolvimento das famílias de Ponte Nova em suas seis dimensões, com ressalva para o acesso ao trabalho, revelou progresso no nível de bem-estar das famílias. A geração deste importante índice pode, de certa forma, auxiliar na elaboração de políticas públicas que visam diminuir as desigualdades no município.

This chapter proposes that efforts to improve our understanding of factors affecting migrant health and longevity in the United States must consider migrants’ labor market incorporation and the structural conditions under which they work. I use public-use death certificate data to examine whether there is a mortality penalty for foreign-born workers in the secondary sector industries of agriculture and construction. I focus on the decade of the 1990s for two contextual and empirical reasons: (1) the decade was characterized by economic restructuring, restrictive immigration policy, increased migration, and dispersion of migrants to new geographic destinations; and (2) the 1990s is an opportunistic decade because 19 states coded the industry and occupation of the decedent during this time. These numerator mortality data and Census denominator data are used to compare all-cause mortality rates between working-age (16–64 years) US-born and foreign-born agricultural and construction workers, the overall foreign-born population, and foreign-born workers in health care – an industry where the foreign-born tend to work in well-paid occupations that are well-regulated by the state. The results show a clear mortality penalty for foreign-born workers in agriculture and construction compared to the overall foreign-born population and foreign-born healthcare workers. The results also show the mortality penalty for foreign-born secondary sector workers varies by industry. These findings support the argument that bringing work into our analyses is critical to understanding the contextual and structural factors affecting migrant health and survival.