In a world where one’s future is heavily impacted by having postsecondary education, access to college is a pertinent research topic. Access is a widely researched topic, but only recently has college access been studied specifically. This study proposes a geographic information systems based methodology for quantifying college access at multiple spatial scales. This methodology was implemented with the Python programming language and ArcGIS. A sample of six metropolitan statistical areas were identified and analyzed using the developed methodology. Within this sample, college access varied primarily by socio-economic status although some variation between race/ethnicity was identified. Further research is needed to assess whether these trends are generalizable. Quantification of college access will aid policy-makers to prepare reforms to reduce the inequity of college access.

This paper examines the role of social interactions in location decisions. We study over one million long-run location decisions made during two landmark migration episodes by African Americans born in the U.S. South and whites born in the Great Plains. We develop a new method to estimate the strength of social interactions for each receiving and sending location. Social interactions strongly influenced the location decisions of black migrants, but were less important for white migrants. Social interactions were particularly important in providing African American migrants with information about attractive employment opportunities and played a larger role in less costly moves.

The present research documents the widespread misperception of race-based economic equality in the United States. Across four studies (n = 1,377) sampling White and Black Americans from the top and bottom of the national income distribution, participants overestimated progress toward Black–White economic equality, largely driven by estimates of greater current equality than actually exists according to national statistics. Overestimates of current levels of racial economic equality, on average, outstripped reality by roughly 25% and were predicted by greater belief in a just world and social network racial diversity (among Black participants). Whereas high-income White respondents tended to overestimate racial economic equality in the past, Black respondents, on average, underestimated the degree of past racial economic equality. Two follow-up experiments further revealed that making societal racial discrimination salient increased the accuracy of Whites’ estimates of Black–White economic equality, whereas encouraging Whites to anchor their estimates on their own circumstances increased their tendency to overestimate current racial economic equality. Overall, these findings suggest a profound misperception of and unfounded optimism regarding societal race-based economic equality—a misperception that is likely to have any number of important policy implications.

Multicore CPUs and cheap co-processors such as GPUs create opportunities for vastly accelerating database queries. However, given the differences in their threading models, expected granularities of parallelism, and memory subsystems, effectively utilising all cores with all co-processors for an intensive query is very difficult. This paper introduces a novel templating methodology to create portable, yet architecture-aware, algorithms. We apply this methodology on the very compute-intensive task of calculating the *skycube*, a materialisation of exponentially many skyline query results, which finds applications in data exploration and multi-criteria decision making. We define three parallel templates, two that leverage insights from previous skycube research and a third that exploits a novel point-based paradigm to expose more data parallelism. An experimental study shows that, relative to the state-of-the-art that does not parallelise well due to its memory and cache requirements, our algorithms provide an order of magnitude improvement on either architecture and proportionately improve as more GPUs are added.

This chapter explores current trends in household mobility by describing correlates of moving and individuals’ reasons for moving, exploring answers to the question, “Who moves and why?” While the research presented in Chap. 2 described household mobility trends in a large, demographic context, this chapter describes sociodemographic variations in household mobility and individuals’ reasons for moving. Drawing on nationally representative data from 2014–2015, household mobility and reasons for moving are explored as they occur differentially across age groups and by social class, race/ethnicity, housing tenure, and other demographic characteristics, such as gender and labor force participation.The primary goal of this chapter is to emphasize the variation in characteristics of movers and their reported reasons for doing so.

Legislation requiring paid time off for employees in case of personal illness or the illness of a child or family member is gaining popularity in the United States. This study examines whether it positively impacts the gender wage gap as women are more likely than men to take leave, paid or unpaid, in the event of a child or elder in their care becoming ill. I use both a difference in differences regression and a propensity score matching model with Consumer Population Survey data to examine the impact of paid sick leave legislation on womens wages. I find no statistically significant evidence that paid sick leave legislation improves womens wage outcomes relative to mens.

Immigrant workers are a growing share of the U.S. labor force and are overrepresented in certain occupations. This much is well documented, yet few studies have examined the consequences of this division of labor between foreign-born and native-born workers. This research focuses on one of the consequences of occupational segregation-worker health. We merge data from the 2004-2014 National Health Interview Surveys with occupational-level data from the Occupational Information Network 20.1 database and the American Community Surveys to examine the relationship between occupational segregation and health. First, logistic regression models show that working in an occupation with a higher share of immigrants is associated with higher odds of poor physical and psychological health. This relationship is more pronounced among native-born workers than among foreign-born workers. Second, we propose two explanations for the association between occupational segregation and health: (1) workers with less human capital are typically sorted into culturally devalued occupations with a higher concentration of immigrants, and (2) occupations with a higher percentage of immigrants generally have relatively poor work environments. We find sorting variables play a major role, whereas the smaller contribution of occupational environments to the segregation-health link is partly because of the heterogeneous (i.e., both positive and negative) indirect effects of different exposure measures. With the sustained high levels of immigration to the United States, the implications of integrated or segregated experiences in the labor market and their impact on workers are important avenues for health policies and future research.

How many generations does it take for skill gaps across immigrant sources to converge? Using data that links immigrant grandfathers in 1880 to grandsons in 1940, we show that ethnic group averages converge at a slower rate than a standard multigenerational model predicts. Third-generation outcomes are correlated with the average skill level of the first generation, above and beyond the effect of the grandfather. Ethnic skill gaps converge more quickly for descendants of grandfathers from the same 1880 neighborhood, suggesting that the clustering of the first generation into enclaves partially drives persistence of ethnic skill gaps for multiple generations.

Immigrant entrepreneurship is important to local and regional economies, cultural identity, placemaking, and tourism. Meanwhile, regional conditions, such as the development of suburban immigrant gateway communities and increases in the cost of business ownership, complicate local economic development efforts in urban ethnic districts. This research is presented as a mixed–methods case study of Devon Avenue in Chicago, IL, home to a significant concentration of South Asian–owned immigrant businesses. Challenges and pressures facing businesses are examined through merchant surveys and interviews. Observations reinforce the notion that cultural competency and strong grassroots leadership is vital for economic development planning so that “capitalizing” on an ethnic heritage does not become a tool for commodification or commercial gentrification. Agencies must also be mindful of the impacts associated with suburbanization of immigrant communities and take a long-term, regional approach to planning in ethnic commercial corridors.

The Stanford Education Data Archive (SEDA; seda.stanford.edu) 1 is an initiative aimed at harnessing data to help scholars, policymakers, educators, and parents learn how to improve educational opportunity for all children. SEDA includes a range of detailed data on educational conditions, contexts, and outcomes in school districts and counties across the United States. It includes measures of academic achievement and achievement gaps for school districts and counties, as well as district-level measures of racial and socioeconomic composition, racial and socioeconomic segregation patterns, and other features of schooling systems.

Racial dynamics and discrimination have been extremely important in influencing decline in the American Rust Belt. The mid-twentieth century departure of white and middle-class populations from cities was precipitated by a breakdown of discriminatory housing practices. This study examines the relationship among housing condition, vacancies, poverty, and demographics in Flint, Michigan, from 1950 to 2010. Historical census data from the National Historical GIS and housing condition data from the City of Flint government are aggregated to neighborhoods defined by economic condition factor (n = 102). Results of rank-difference correlation and geographically weighted regression indicate that, across neighborhoods with the greatest decline in housing condition, the strongest correlate was most often the increase in vacancy rates driven initially by racially motivated suburbanization–suggesting that demographic change alone is not primarily responsible for neighborhood decline. This research is important to understanding the long-term and ongoing consequences of mid-twentieth century racist housing practices, particularly as it relates to the implications of maintaining legacy infrastructure.

This paper analyzes the connections between three concurrent trends since 1950: (1) the narrowing and reversal of the educational gender gap; (2) the increasing labor force participation rate (LFPR) of married women; (3) the rising incidence of children living with only one parent. We hypothesize that the education production for boys is more adversely affected by a decrease in parental time input as a result of increasing maternal employment or parental absence. Therefore, a pronounced increase in the labor force participation rate of married women as well as the rising incidence of absent fathers may narrow and even reverse the educational gender gap in the child generation. We use micro data from the Norwegian registry to directly show that the parental employment during their childrens childhood has an asymmetric effect on the educational achievement of their own sons and daughters. We also document a positive correlation between the educational gender gap in a particular generation and the LFPR of married women in the mother generation as well as the incidence of parental absence (mostly absence of fathers) at the U.S. state level. We then propose a model that generates a novel prediction about the implications of these asymmetric effects on parental labor supply decisions and find supporting evidence in both the U.S. and Norwegian data.

We show that the structural change of the economy from agriculture to industry was a major determinant of the observed shift in intergenerational coresidence. We build a two-sector overlapping generation model of the structural change out of agriculture, in which the coresidence choice is endogenous. We calibrate the model on US data and simulate it. The model can match well the decline in US intergenerational coresidence between 1870 and 1940.

We develop a multi-sector gravity model with heterogeneous workers to quantify the aggregate and group-level welfare effects of trade. We estimate the model using the structural relationship between China-shock driven changes in manufacturing employment and average earnings across US groups defined by commuting zone and education. We find that the China shock increases average welfare but some groups experience losses as high as five times the average gain. Adjusted for plausible measures of inequality aversion, gains in social welfare are positive and only slightly lower than with the standard aggregation.

The choice of college major is a key stage in the career search process. About 40% of college students switch majors at least once, suggesting that major choice is a process rather than a single decision. This paper provides the first comprehensive analysis of major switching, modeling the choice process as a complex matching problem between student and major. We posit that both academics and preferences can lead students to switch majors, and our results confirm this. We first show that low grades serve as a signal of academic mismatch. Low grades predict switching majors - and the lower the grades, the larger the switch in academic terms. When students switch majors, their grades improve - and the larger the switch, the greater the improvement. Academics are only one factor in major switches, however. Overwhelmingly, when students switch majors, they are drawn to majors that look like them: females to female-heavy majors, blacks to black-heavy majors, and so on. Women also flee competitive majors - especially STEM majors - at much higher rates than men, even controlling for grades, and this includes women who enter college with high test scores. Women who leave STEM switch to majors that are much less male-dominated and competitive, suggesting that leaving STEM is more about fleeing the culture and makeup of STEM majors than it is about fleeing science.

BACKGROUND: Disparities in exposure to air pollution by race-ethnicity and by socioeconomic status have been documented in the United States, but the impacts of declining transportation-related air pollutant emissions on disparities in exposure have not been studied in detail. OBJECTIVE: This study was designed to estimate changes over time (2000 to 2010) in disparities in exposure to outdoor concentrations of a transportation-related air pollutant, nitrogen dioxide (NO2), in the United States. METHODS: We combined annual average NO2 concentration estimates from a temporal land use regression model with Census demographic data to estimate outdoor exposures by race-ethnicity, socioeconomic characteristics (income, age, education), and by location (region, state, county, urban area) for the contiguous United States in 2000 and 2010. RESULTS: Estimated annual average NO2 concentrations decreased from 2000 to 2010 for all of the race-ethnicity and socioeconomic status groups, including a decrease from 17.6 ppb to 10.7 ppb (−6.9 ppb) in nonwhite [non-(white alone, non-Hispanic)] populations, and 12.6 ppb to 7.8 ppb (−4.7 ppb) in white (white alone, non-Hispanic) populations. In 2000 and 2010, disparities in NO2 concentrations were larger by race-ethnicity than by income. Although the national nonwhite–white mean NO2 concentration disparity decreased from a difference of 5.0 ppb in 2000 to 2.9 ppb in 2010, estimated mean NO2 concentrations remained 37% higher for nonwhites than whites in 2010 (40% higher in 2000), and nonwhites were 2.5 times more likely than whites to live in a block group with an average NO2 concentration above the WHO annual guideline in 2010 (3.0 times more likely in 2000). CONCLUSIONS: Findings suggest that absolute NO2 exposure disparities by race-ethnicity decreased from 2000 to 2010, but relative NO2 exposure disparities persisted, with higher NO2 concentrations for nonwhites than whites in 2010.

We study the urban structure of the City of Detroit. Following several decades of decline, the city's current urban structure is clearly not optimal for its size, with a business district immediately surrounded by a ring of largely vacant neighborhoods. We propose a model with residential externalities that features multiple equilibria at the neighborhood level. In particular, developing a residential area requires the coordination of developers and residents, without which it may remain vacant even if its fundamentals are sound. We embed this mechanism in a quantitative spatial economics model and use it to rationalize current city allocations. We then use the model to examine existing strategic visions to revitalize Detroit. We also explore alternative plans that rely on development guarantees, and find that they could result in greater population growth and land price appreciation than existing plans. The widespread effects of these policies underscore the importance of using a general equilibrium framework to evaluate policy proposals.

Background: The Affordable Care Act established policy mechanisms to increase health insurance coverage in the United States. While insurance coverage has increased, 10%-15% of the US population remains uninsured. Objectives: To assess whether health insurance literacy and financial literacy predict being uninsured, covered by Medicaid, or covered by Marketplace insurance, holding demographic characteristics, attitudes toward risk, and political affiliation constant. Research Design: Analysis of longitudinal data from fall 2013 and spring 2015 including financial and health insurance literacy and key covariates collected in 2013. Subjects: A total of 2742 US residents ages 1864, 525 uninsured in fall 2013, participating in the RAND American Life Panel, a nationally representative internet panel. Measures: Self-reported health insurance status and type as of spring 2015. Results: Among the uninsured in 2013, higher financial and health insurance literacy were associated with greater probability of being insured in 2015. For a typical uninsured individual in 2013, the probability of being insured in 2015 was 8.3 percentage points higher with high compared with low financial literacy, and 9.2 percentage points higher with high compared with low health insurance literacy. For the general population, those with high financial and health insurance literacy were more likely to obtain insurance through Medicaid or the Marketplaces compared with being uninsured. The magnitude of coefficients for these predictors was similar to that of commonly used demographic covariates. Conclusions: A lack of understanding about health insurance concepts and financial illiteracy predict who remains uninsured. Outreach and consumer-education programs should consider these characteristics.

This paper analyses the impact of the business cycle on labour market dynamics in EU member states and the US during the first decade of the 21st century. Using unique measures of labour market flows constructed from worker-level micro data, we examine to what extent macro shocks were transmitted to national labour markets. We apply the approach by Blanchard and Wolfers (2000) to analyse the role of the interaction of macroeconomic shocks and labour market institutions for worker transitions in order to explain cross-country differences in labour market reactions in a period including the Great Recession. Our results suggest a significant influence of trade unions in channelling macroeconomic shocks. Specifically, union density moderates these impacts over the business cycle, i.e. countries with stronger trade unions experience weaker reactions of the unemployment rate and of worker transitions.

We explore the educational response to fracking, a recent technological breakthrough in the oil and gas industry, taking advantage of the timing of its diffusion and spatial variation in shale reserves. We show that fracking has significantly increased demand for less-educated male labor and high school dropout rates of male teens, both overall and relative to females. Our estimates imply that, absent fracking, the male-female gap in teen dropout rates in affected states would have narrowed by nearly 40% between 2000 and 2013 instead of by only a tenth. Fracking did not reduce the return to high school for men by enough to plausibly explain the full effects, suggesting the importance of a rising opportunity cost of enrollment for the findings. Other explanations, like changes in school inputs or family income, receive less empirical support.