A broadly accepted view contends that the 2007-09 financial crisis in the U.S. was caused by an expansion in the supply of credit to subprime borrowers during the 2001- 2006 credit boom, leading to the spike in defaults and foreclosures that sparked the crisis. We use a large administrative panel of credit file data to examine the evolution of household debt and defaults between 1999 and 2013. Our findings suggest an alternative narrative that challenges the large role of subprime credit in the crisis. We show that credit growth between 2001 and 2007 was concentrated in the prime segment, and debt to high risk borrowers was virtually constant for all debt categories during this period. The rise in mortgage defaults during the crisis was concentrated in the middle of the credit score distribution, and mostly attributable to real estate investors. We argue that previous analyses confounded life cycle debt demand of borrowers who were young at the start of the boom with an expansion in credit supply over that period.

The presence of a westward-moving frontier of settlement shaped early U.S. history. In 1893, the historian Frederick Jackson Turner famously argued that the American frontier fostered individualism. We investigate the Frontier Thesis and identify its long-run implications for culture and politics. We track the frontier throughout the 1790–1890 period and construct a novel, county-level measure of total frontier experience (TFE). Historically, frontier locations had distinctive demographics and greater individualism. Long after the closing of the frontier, counties with greater TFE exhibit more pervasive individualism and opposition to redistribution. This pattern cuts across known divides in the U.S., including urban–rural and north–south. We provide suggestive evidence on the roots of frontier culture: selective migration, an adaptive advantage of self-reliance, and perceived opportunities for upward mobility through effort. Overall, our findings shed new light on the frontier’s persistent legacy of rugged individualism.

To respond to questions about the nature of Latino contributions to the United States, the Latino Donor Collaborative commissioned original research, the first of its kind, which has produced the following study. It presents a factual view of the importance of Latinos to our economy, for all Americans to understand, in business, non-profit organizations, politics, etc. We thought that Latinos were powering in the economy, but were pleasantly surprised to discover what is actually happening: • The GDP produced by Latinos in the U.S. in 2015 was $2.13 trillion. • If it were an independent country, the Latino GDP would be the 7th largest in the world, larger than the GDP of India, Italy, Brazil or Canada. The Latino GDP would trail only the U.S., China, Japan, Germany, the U.K., and France. • Of the top ten economies, it would be the third-fastest growing GDP. • The U.S. Latino GDP is growing 70% faster that the country’s non-Latino GDP. • Latinos accounted for 70% of the U.S. work force’s increase in the first half of this decade. • As young Latinos enter the work force and the older non-Latinos leave it, the Latino GDP will account for an increasing portion of the total U.S. GDP growth, projected to be 24.4% of total US GDP growth by 2020. The common perception of Latinos being a burden to U.S. society is utterly wrong. To the contrary, Latinos are the element most needed to fuel the growth of this country. All Americans have benefitted from the $2.13 trillion contribution the Latino GDP makes to the country, and should take steps to make sure it continues.

Founded in 1965, Head Start is designed to promote “school readiness of children under 5 from low-income families through education, health, social, and other services.” Created in 1994, Early Head Start focuses specifically on the youngest children-those under age 3, and pregnant women-and provides “early, continuous, intensive, and comprehensive child development and family support services to low-income infants and toddlers, and their families, and pregnant women and their families.” The Administration for Children and Families, housed within the U.S. Department of Health and Human Services, oversees and administers all Head Start programs through the federal Office of Head Start.

Artificial neural network (ANN) models are rarely used to forecast population in spite of their growing prominence in other fields. We compare the forecasts generated by ANN long short-term memory models with population projections from traditional cohort-component method (CCM) for counties in Alabama. The evaluation includes forecasts for all 67 counties that offer diversity in terms of population and socioeconomic characteristics. When comparing predicted values with total population counts from the 2010 decennial census, the CCM used by the Center for Business and Economic Research at the University of Alabama in 2001 produced more accurate results than a basic multi-county ANN model. Only when we use single-county models or proxy for a forecaster's experience and personal judgment with potential economic forecasts, results from ANN models improve. The results indicate the significance of forecaster's experience and judgment for CCM and difficulty, but not impossibility of substituting these insights with available data.

This paper investigates the effect of culture and home country self-employment rates on immigrant self-employment in the United States, post-migration. This study analyzes the effects for both men and women, focusing on the gender gap in self-employment. The empirical results show that home country effects have a small impact on self-employment, but most of this relationship is unexplained. Because the explanatory power of home country effects is so low, it is unlikely that culture significantly influences self-employment. I find that, contrary to my hypotheses, women from countries with high female self-employment rates are likely to see a larger decrease in self-employment than their male counterparts or women from countries with lower self-employment rates. The gender gap in self-employment increases in the U.S. because self-employment declines more for women than men. However, I do find that men from countries with high male self-employment will also see a larger decline in self-employment than men from other countries. Thus, I reject the home country self-employment hypothesis with regards to women and men. I find some evidence that immigrant self-employment rates are more related to stage of economic development in the host country than culture in the home country.

US manufacturing policies increasingly steer resources toward the act of innovation. Emerging case-study evidence suggests that this innovation leads to manufacturing job growth. However, the case-study evidence from which this claim is assembled is incomplete and selective. Using regional-level industry-occupation data for US manufacturing sectors, we test the contribution of manufacturing innovation activities to production employment growth within US regions, for the 2000-2006 and 2006-2010 periods. While production employment continued to disperse from sites of historical manufacturing concentration over both time periods, innovation activities provided some advantages. From 2000 to 2006, regions with higher innovation concentrations in high-tech and mediumlow technology industries, experienced slower rates of production employment decline. From 2006 to 2010, a period spanning the Great Recession, innovation activities were associated with reduced production job losses for industries of all technology levels. These results indicate that innovation has benefits beyond high-technology industries, but that those benefits are limited and selective.

Between 1940 and 1980 the wage gap between poorer U.S. cities and richer ones was shrinking at an annual rate of roughly 1.4%. After 1980, however, there was no further regional convergence overall. This paper quantifies the contributions of skill-biased technical change (SBTC) and agglomeration economies to the end of cross-city wage convergence within the U.S. between 1980 and 2010. I develop and estimate a dynamic spatial equilibrium model that looks at the causes of regional convergence and divergence. The model choice is motivated by novel empirical regularities regarding the evolution of the skill premium and migration patterns over time and across space. The model successfully matches the quantitative features of the U.S. regional wage convergence. Moreover, the model also reproduces changes in the skill ratio across U.S. cities, as well as, migration patterns after 1980. Finally, the counterfactual analysis suggests that SBTC explains much of change in cross-city wage differentials.

We isolate the effect of immigration-induced changes in the size and skill distribution of the labor force on labor market outcomes using a model in which firms endogenously respond to these changes. We analytically show that while the immigration-induced increase in the size increases the relative wages, employment and output shares of the skill intensive sector, changes in the skill distribution lead to analytically ambiguous effects. We derive quantitative results for the US economy under different counter-factual scenarios with respect to immigration-induced changes in size and skill distribution of the labor force, where these changes resemble those of U.S. as a whole, New York, California and Canada, and reflect different immigration policy regimes. For example, immigration increases the mass of workers at the lower range of the skill distribution in the U.S., and the upper range in Canada. Regardless of these differences across scenarios, our quantitative results indicate that immigration increases the relative average wages of the skill intensive sector. Further, real wages of all workers increase due to reduced prices caused by the increased size of the labor force.

Over the past years, the skyline query has already attracted wide attention in database community. In order to meet different preferences for users, the skycube computation is proposed to compute skylines, or cuboids, on all possible non-empty dimension subsets. The key issue of computing skycube is how to share computation among multiple related cuboids, which classified into sharing strict space dominance and sharing space incomparability. However, state-of-the-art algorithm only leverages sharing strict space dominance to compute skycube. This paper aims to design a more efficient skycube algorithm that shares computation among multiple related cuboids. We first propose a set of rules named identical partitioning (IP) for constructing a novel structure VSkyTree. Moreover, we present the reusing principle, which utilizes both sharing strict space dominance and sharing space incomparability by reusing VSkyTree on parent cuboids to compute child cuboids. Then, in top-down fashion, we design an efficient skycube computation algorithm RSkycube based on the reusing principle. Our experimental results indicate that our algorithm RSkycube significantly outperforms state-of-the-art skycube computation algorithm on both synthetic and real datasets.

This article examines the demographic and occupational selectivity of German immigration to South America (primarily Argentina and Brazil) and Australia, compared to Germans bound for the United States, and the geographic and occupational niches they occupied at various destinations. It draws upon both individual-level and aggregate data from censuses and migration records on three continents to examine occupational profiles, urbanization rates, sex ratios, age structure, and age heaping as a rough measure of “quality,” among German immigrants to these destinations, concluding that immigration to the United States tended to be the least selective.

It is difficult to underestimate the importance of education for individuals‟ lives. Educational attainment is a key characteristic of individuals with a strong positive impact on virtually all relevant life cycle events that social scientists are interested in (e.g. union formation and dissolution, fertility, getting a job, salary, migration, health status and, finally, age at death). Therefore, the spectacular expansion of education we have witnessed all over the world during the last decades has to be welcomed as a major social improvement. This expansion includes rising literacy rates (Crafts 2002) as well as increases in school enrollment rates and in completed years of primary, secondary and college education (Benavot and Riddle 1988, Benavot et al. 1991; Meyer, Ramirez, and Soysal 1992; Ramirez and Meyer 1980; Barro and Lee 2000; Cohen and Soto 2007; Morrisson and Murtin 2009). These worldwide gains on virtually all education indicators are exhaustively described in a recent book by Barro and Lee (2015). While the levels and trends of overall educational attainment indicators have been well documented, the study of educational inequality has received far less attention in the literature. Yet, the way in which education is distributed across the population does have direct implications for individuals‟ life chances. High levels of educational inequality today will typically generate and amplify inequalities in other welfare domains in the future, hindering social mobility and strengthening the intergenerational transmission of social exclusion and disadvantage (Breen and Jonsson 2005; Esping-Andersen 2009). In this context, it is therefore important to document the levels and trends of educational inequality and to explore whether inequality declines together with educational expansion or not. In the last years, some studies have aimed to estimate educational inequality measures around the globe and/or its regions (e.g. Castelló and Doménech 2002, Benaabdelaali et al. 2012, Dorius 2013, Meschi and Scervini 2013, Morrisson and Murtin 2013). Virtually all these studies are based on different versions of the dataset from Barro and Lee (see www.barrolee.com), which groups data in 4 or 7 broad educational attainment categories, depending on whether we consider both complete and incomplete educational stages. Unfortunately, by grouping the data in these coarse categories we lose sight of important variations that might be occurring both within and between education distributions, therefore downwardly biasing the estimated inequality levels – an issue we address in this paper. For the first time, we aim at unraveling global trends in education inequality using micro-level information about individuals‟ years of schooling. Such fine-grained information will allowus to describe global education inequality levels and trends with unprecedented accuracy. For that purpose, we have assembled a large dataset from different – yet comparable – data sources: the census micro-data samples from the IPUMS project, the Demographic and Health Surveys (DHS), the European Social Surveys (ESS) and the International Social Survey Programme (ISSP). Our database consists of 153 census samples and 1,011 household surveys covering 126 countries from the period 1960-2014. With this wealth of information, we aim to gain understanding on the nature of the variation in years of schooling among countries and recent time periods in several ways. First, we disclose the full pattern of variation in educational inequality and mean years of schooling for all 1164 country-year combinations. Recently, some authors suggested that a J-shaped relationship between average years of education and inequality emerges, as expansion at higher levels of education is likely to cover more selective parts of countries‟ populations (Meschi and Scervini 2013). Our relatively precise measurement of years of education should be particularly suited to identify such a J-shaped curve. Second, we select a consistent sample of 85 countries for the periods 1995-2004 and 2005-2014 to estimate global educational inequality and decompose this inequality into its within and between-country components. This kind of decomposition has already been explored in the domains of income (Anand and Segal 2014) and health (Edwards 2011), but remains to be unraveled and analyzed for the case of education. Finally, we investigate the contribution that the different educational stages (primary, secondary and tertiary education) have had on global educational inequality – a contribution that changes substantially across countries and over time as education expands. Also here, the precision of our years of education measure should give relatively accurate estimates of the relative role of educational stages in creating global educational inequality.

This paper examines the phenomenon of occupational hierarchies among immigrant labor groups in the United States. Using census data for 1940-2011 we document the persistent ranking of immigrant labor groups in major metropolitan areas reflected by their position in the empirical distribution of occupations based on the corresponding Duncan Socioeconomic Index values. Having established the existence and persistence of these hierarchies across regions and time we estimate a structural model of the allocation of immigrant labor to the occupational distribution on the basis of employers' perception of their perceived productivity. The model estimates suggest that while human capital characteristics are relevant determinants of location in the occupational distribution the key factor, and the cause of persistence, is the presence of immigrant networks in regional labor markets.

Over the 1990s, the share of foreigners entering the US high-skill workforce grew rapidly. This migration potentially had a significant effect on US workers, consumers and firms. To study these effects, we construct a general equilibrium model of the US economy and calibrate it using data from 1994 to 2001. Built into the model are positive effects high skilled immigrants have on innovation. Counterfactual simulations based on our model suggest that immigration increased the overall welfare of US natives, and had significant distributional consequences. In the absence of immigration, wages for US computer scientists would have been 2.6% to 5.1% higher and employment in computer science for US workers would have been 6.1% to 10.8% higher in 2001. On the other hand, complements in production benefited substantially from immigration, and immigration also lowered prices and raised the output of IT goods by between 1.9% and 2.5%, thus benefiting consumers. Finally, firms in the IT sector also earned substantially higher profits due to immigration.

Standard models of structural change predict that the share of agricultural value added and agricultural employment are equalized. In the data they are not. While both decline as the economy develops, value added per worker in agriculture is substantially lower than in non-agriculture. Moreover, this agricultural productivity gap is remarkably persistent despite the large reallocation of production factors across sectors. In this paper, we argue that this sectoral productivity gap might to a large extent be a spatial gap. Using a novel dataset for more than 700 US commuting zones between 1880 and 2000, we document that agricultural employment shares are strongly negatively correlated with average earnings and uncorrelated with subsequent net population outflows. These facts are consistent of substantive frictions to spatial mobility, which prevent the spatial equalization of marginal products. To quantify the strength of this mechanism, we construct a novel theory of spatial structural change by embedding an economic geography model in a dynamic, neoclassical model of the structural transformation. We show that spatial frictions can account for more than 50% of the observed productivity gap. This implies that the direct productivity gains from reallocating workers across sectors are modest.

The aim of this dissertation is to examine, model and estimate the importance of demand factors that shape the diet quality choices of the U.S. households. In particular, I focus on the low-income households, because these households are consuming food of lower diet quality. Understanding whether and how income is restricting these households in their food choices is important for the policy makers. First, I analyze the importance of the food access in explaining the difference in diet quality across income. Second, I study the importance of price effects of high nutritional quality food for the low-income households. Third, I analyze the differences in preferences across the U.S. cities

While Texas was among the states choosing not to participate in the Medicaid expansion under the Affordable Care Act, it nonetheless has seen improvement in the share of the population with health insurance coverage. Gains are notable among the noncollege-educated workingage population in Texas, a state that has long ranked near the bottom in health care coverage nationally.

The aim of this paper is to examine the manner and extent to which worker skill type affects agglomeration economies that contribute to productivity in cities. I use college majors to proxy for skill types among workers with a bachelor's degree. Workers with college training in information-oriented and technical fields (e.g., STEM areas such as engineering, physical sciences, and economics) are associated with economically important within-field agglomeration economies and also generate sizeable spillovers for workers in other fields. In contrast, within-field and across-field spillovers for workers with college training in the arts and humanities are much smaller and often nonexistent. While previous research suggests proximity to college-educated workers enhances productivity, these findings suggest that not all college-educated workers are alike. Instead, positive spillover effects appear to derive mostly from proximity to workers with college training in information-oriented and technical fields.

Because employment is a central social policy goal, policy analysts and policy makers are interested in better understanding whether and how jobs meet people’s needs. To contribute to research in this area, this dissertation uses nationally representative survey data and regression analysis to empirically examine how the characteristics of workers and their jobs affect access to employee benefits. The first two essays focus on access to the unemployment insurance program, and the third essay focuses on access to employer provided health insurance coverage, paid leave, and pensions. Together these chapters identify barriers and pathways between employment and benefits after the Great Recession and highlight ways in which policy makers can broaden the protective effects of employment in the new economy.

Although service to the nation–state features in academic and lay understandings of patriotism, claims of patriotism are rarely examined alongside contributions to the nation–state. The present study examines four behaviors—military enlistment, voting, monetary contributions, and census response—to evaluate the claim that certain parts of the United States, and specifically the communities of “real America,” contribute more than others to the country overall. Consistent with the words of several electoral candidates, ruralness, religiosity, political conservatism, and gun culture collectively identify a distinctive set of communities where residents are both more likely to report “American” as their ancestry and to vote for Republican presidential candidates, including Donald Trump. However, visual and statistical evidence undermine the claim that these communities contribute more than other parts of the country. Instead, and in several respects, these communities make smaller contributions to the nation–state than one would expect based on other characteristics. The findings undermine divisive claims about a “real” America that gives more than its “fair share.”