The changes in technology that took place in the US during the last three decades, mainly due to the introduction of computerization and automation, have been characterized as “routine-substituting.” They have reduced demand for routine tasks, but have increased demand for analytical tasks. Indirectly they have also increased the demand for manual and service type of occupations. Little is known about how these changes have impacted immigration, or task specialization between immigrants and natives. In this paper we show that such technological progress has attracted skilled and unskilled immigrants, with the latter group increasingly specialized in manual-service occupations. We also show that this immigration response has helped to reverse the polarization of jobs and wages for natives. We explain these facts with a model of technological progress and endogeous immigration. Simulations show that immigration in the presence of technological change attenuates the drop in routine jobs and the increase in service jobs for natives.

This study assesses whether Latinas’ ethnic and racial self-identification can predict their number of “children ever born” (CEB) after controlling for cultural, socioeconomic, and demographic factors. Analyzed together, these factors measure the role that existing racial/ethnic structures have on the experiences of Latino subgroups. I pool data from the Fertility Supplement of the Integrated Public Use Microdata Series (IPUMS) Current Population Survey. Following a series of zero-inflated Poisson regressions and controlling for cultural, socioeconomic, and demographic factors, women who ethnically self-identify as Mexican, Puerto Rican, or Central American have more CEB than women who self-identify as Cuban. Simultaneously, Latinas who racially self-identify as white have fewer CEB than nonwhite Latinas. I propose that the different racialized experiences of these groups can help explain these patterns. Moreover, I argue that the results provide empirical evidence of the multicausal explanations for intra-Latina fertility behavior.

How important is working with people who complement one’s skills? Using administrative data that record which of 491 educational tracks each worker in Sweden absolved, I quantify the educational fit among coworkers along two dimensions: coworker match and coworker substitutability. Complementary coworkers raise wages with a comparable factor as does a college degree, whereas working with close substitutes is associated with wage penalties. Moreover, this coworker fit does not only account for large portions of the urban and large-plant wage premiums, but the returns to own schooling and the urban wage premium are almost completely contingent on finding complementary coworkers.

Institutional laws and arrangements such as prevailing wage laws influence the employment levels and wage rates of the local labor supply. Conflicting research, however, has shown that prevailing wage laws lead to higher construction costs, while others show little to no relationship. Most of these studies are completed at the national level whose results at the regional level may not be applicable. This article examines the impact of prevailing wage laws on construction wages in the Mountain States of the nation. Difference-in-difference-difference models were used, and results indicate that for the Mountain States, removal of prevailing wage laws decreased wages by 4.4% after 10 years of the repeal. However, because of the available data used in this analysis, the impacts of repealing the prevailing wage laws on benefits could not be determined, which from previous research could be significant.

Direct care workers who provide assistance in clients’ homes, also known as home care workers, are a large and growing share of the U.S. labor force. In 2015, 1.7 million workers provided in-home, personal assistance to the elderly, the chronically ill, and individuals with disabilities, and this number was almost double the number working as home care workers in 2005. While this is still a female-dominated occupation—88% of the workers providing in-home care were female in 2015—the share has fallen somewhat from 92% female in 2005. Home care workers are included in two occupational categories, personal and home care aides and nursing, psychiatric, and home health aides, used to describe direct care workers in federal data sets; there were about 4.4 million direct care workers in both occupations in 2015. Here, we further identify direct care workers in these two occupations who work in the industries of home health care services or individual and family services as home care workers: about 38% of the total direct care workforce in the two occupations identified. Home care workers are also growing as a share of direct care workers. Among all personal and home care aides, those working in homes grew from 43% to 51% of the total between 2005 and 2015, and among all nursing, psychiatric, and home health aides, the share working in homes grew from 20 to 30% of the total across the same 10 years (see Appendix). The direct care occupations of personal and home care aides and nursing, psychiatric, and home health aides have much in common with other low-wage, female-dominated occupations. A 2016 study by researchers from the Institute for Women’s Policy Research (IWPR) working with Oxfam America identified the 22 largest, growing, female-dominated occupations (here defined as having 60% or more female incumbents) with median pay of less than $15 per hour in 2014 (Shaw, Hegewisch, Williams-Baron, & Gault, 2016). Personal and home care aides are the eighth largest of these occupations and nursing, psychiatric, and home health aides are the fourth largest. Among those 22, personal and home care aides constitute the single occupation with the highest growth rate projected through 2024 by the U.S. Bureau of Labor Statistics (BLS), at 25.9% from 2014–2024, while the growth rate for nursing, psychiatric, and home health aides is not far behind at 24.5%. The growth rate projected for all 22 low-paid, female-dominated occupations is 9.5% across the same period and 6.5% for all occupations (total employment). Aides in these two direct care occupations are older (median age 45 and 41 respectively) than the average workers in these 22 low-wage occupations (median age 36). Female personal and home care aides earn about $1.00 per hour less than female workers across all 22 low-wage, female-dominated occupations ($10.16 and $11.18 per hour, respectively) while female nursing, psychiatric, and home health aides earn just above the median for all 22 occupations at $11.83 per hour. In 2014, 78.8% of female personal and home care aides earned less than $15 per hour compared with 71.3% of all female workers in the 22 largest occupations; female nursing, psychiatric, and home health aides fare just slightly worse than all female workers with 72.0% earning less than $15 per hour (Shaw et al., 2016). Almost half of both groups of female direct care workers have education beyond high school; nevertheless, more than half have family incomes below the poverty or near-poverty level, faring somewhat worse than women in the 22 occupations as a whole and much worse than all women workers. Female direct care workers are disproportionately women of color and disproportionately foreign-born (only the occupations of personal appearance workers and maids and housekeeping cleaners have higher shares of foreign-born workers among the 22 occupations).

In this dissertation, I study the influences of social interactions on individuals’ labor market outcomes. The first chapter tests for causality in the positive relationship between teenage alcohol consumption and future earnings. Specifically, to investigate this relationship, I exploit the quasi-random variations in high school peer compositions as a treatment to teenage alcohol consumption. By using the National Longitudinal Study of Adolescent Health (Add Health) data, I find that high school peer compositions that cause teenagers to drink more do not have significant influences on their future incomes. This provides indirect evidence that the positive relationship between teenage drinking and future income is not causal. The second chapter examines whether immigrants who are living in ethnic enclaves have labor market advantages. By using 2000 and 2010 U.S. census data and a triple differences model, we find that given the same ethnic group average education, ethnic segregation reduces high-skill immigrants’ wages. This may be because the returns on education are higher for high-skill immigrants when they have more social connections with natives and work in native-dominated labor markets. We also find that as the ethnic group average education decreases, the benefits of ethnic segregation for low-skill immigrants also decrease, likely because competition between low-skill immigrants drives down their wages. The third chapter tests whether teenagers are forward-looking when they choose friends in high school. In particular, we assume that when teenagers choose friends, they consider both immediate payoffs (such as increases in popularity) and long-term economic gains (such as increases in their future earnings) from friendships. Then we estimate which is more important to teenagers when choosing friends, the immediate payoffs or the long-term economic gains. By using Add Health data and a three-period dynamic model, we find that the marginal utility of popularity is much higher than the marginal utility of future earnings, which implies that immediate payoffs are the key factors that influence teenagers’ friendship decisions. Moreover, the outcomes in the heterogeneity tests suggest that African Americans and Hispanics have higher returns on both popularity and future earnings than whites.

These essays are, ultimately, about policy challenges. In Chapter 1, I explore one way in which the hostile, divisive political environment undermines one fundamen- tal function of government performance: the enforcement of basic transparency laws over politically charged entities. In Chapter 2, I show that common labor market poli- cies affect the pace of technological change, a key driver of wage inequality to which the literature has struggled to find responses. In Chapter 3, my coauthors and I evaluate one program that was effective in improving health for poor populations in the minimally- governed peripheries of there country, where much of the world’s most extreme poverty is concentrated and where traditional development policy is nearly impossible to imple- ment.

This analysis quantifies the effect of House Bill No. 45, or the Big Government Get Off My Back Act passed in the state of Missouri. This bill was signed into effect in August 2011 and expired in 2014. The bill offers a tax deduction to small business owners who create full-time jobs and offer a competitive wage. A higher tax deduction can be applied if the employer provides an insurance premium to their employees and financially contributes to it. This research aims to measure effects from House Bill No. 45 on unemployment, job-related insurance enrollment, income, employer contribution to health insurance, and full-time employment using the difference-in-differences model. Cross-panel data obtained from the Current Population Survey was used to measure outcome variables in Missouri and selected comparison states before and after House Bill No. 45. The difference-in-differences estimator quantifies these changes for an economic interpretation. Notable results are that House Bill No. 45 is associated with an increase in policyholders of a job- related insurance policy, but did not have any effect on unemployment or full-time employment in Missouri compared to similar states during the same time period.

School choice is at the center of the Trump administration's education policy efforts, with initial proposals calling for additional funding for charters and other forms of public school choice, as well as the creation of a new federal private school choice program. Some advocates have raised concerns about whether expanding school choice will help disadvantaged families, especially in rural areas and other places where there may not be many schools from which to choose. Concerns about potential inequities in the availability of different schools to different families, based in large part on geography, are plausible but have not been subject to systematic empirical analysis. In this report, we begin to fill this gap by using nationwide data on the locations of public and private elementary schools to calculate the percent of American families that could potentially gain access to new school options under different national school choice policies. This baseline analysis of school locations does not consider important issues such as school capacity, existing choice programs, or possible changes in the supply of different kinds of schools that might result from choice policies. We estimate that private school choice and intradistrict choice (allowing families to choose any traditional public school in their district) have the largest potential to expand the sets of schools to which families have access, with more than 80 percent of families having at least one of these "choice" schools within five miles of home. Charters and interdistrict choice (allowing families to choose a traditional public school outside their district) still would provide potential new options within five miles for roughly half of families. Families with household incomes below the poverty line are more likely to have an intradistrict choice school or charter school nearby than families above the poverty line. We find few differences in proximity to private schools based on poverty. However, interdistrict choice appears likely to provide more new choices to families not in poverty. We find the largest differences in proximity to schools of choice between families in rural and urban areas. At least 60 percent of rural families are within ten miles of intradistrict choice, interdistrict choice, and private schools, but urban families are more likely to have these choices close by. The distance families are able and willing to travel may be more important for expanding school choice than the type of school the policy provides access to. For example, by increasing "as the crow flies" travel distance from one mile to five miles, we more than double the number of families who could potentially take advantage of a private school or an intradistrict choice policy. We also find that the potential availability of choice varies widely across states. For example, 95 percent of California and Massachusetts families live within five miles of a private school, compared to less than 60 percent of Montana and West Virginia families. We conclude that federal policymakers seeking to expand school choice should focus on policies that can function well in different contexts across the U.S.. For example, some states may want to focus on securing additional funding to improve equity of access to high-quality schools by providing better transportation options. Others may want to focus on expanding their charter or private school sectors, or on fostering more choice within the traditional public sector. A natural federal role is to provide resources to support such varied efforts through formula funding or competitive grant programs.

The thesis deals with spatial economic disparities in the United States. The first chapter, “The Evolution of Income Disparities across US Metropolitan Statistical Areas”, investigates how the spatial evolution of core-based city regions affects the dynamics of income disparities across Metropolitan Statistical Areas in the United States between 1971 and 2010. Treating initially nonmetropolitan counties as part of the functional economic system for the whole time period changes the internal composition of average per capita personal income thus biasing convergence analysis. The paper analyses the dynamics of the cross-sectional distribution of per capita personal income by comparing different methods to define MSAs over time. The results show that a cluster of high income economies emerges when MSAs are allowed to evolve spatially. The second chapter, “Urban governance Structure and Wage Disparities among US Metropolitan Areas”, analyses the determinants of spatial wage disparities in the US context for the period 1980-2000. Agglomeration benefits are estimated based on city productivity premia which are computed after controlling for the skills distribution among metropolitan areas as well as industry fixed effects. The drivers of productivity differentials that are taken into consideration are the size of the local economy, the spatial interactions among local autonomous economic systems and the structure of urban governance as well as the policy responses to the fragmentation issue. A metropolitan area with ten percentage more administrative units than another of the same size, experiences wages that are between 2,0% and 3,0% lower. The presence of a voluntary governance body is found to mitigate the problem of fragmentation only marginally, while the existence of special purpose districts have a negative impact on regional productivity. The implementation of a metropolitan government with a regional tax system is expected to increase productivity by around 6%. Finally, the third chapter, “The effect of immigration on convergence dynamics in the US”, studies the impact of immigration on the dynamics of the cross-sectional distribution of GSP per capita and per worker. To achieve this aim, we combine different approaches: on the one hand, we establish via Instrumental Variable estimation the effect of the inflow of foreign-born workers on output per worker, employment and population; on the other hand, using the Distribution Dynamics approach, we reconstruct the consequences of migration flows on convergence dynamics across US states.

The United States has long been the leading destination for immigration. In 2014, there were more than 42 million immigrants in the US, which constitutes 13.3% of the total population in the country (Zong & Batalova, 2016). Of these different immigrant groups, one group in particular has received increasing attention from labor economists: refugees. Unlike economic immigrants who moved to the United States for better economic opportunities, refugees fled to the United States to escape persecution in their home country. In other words, economic immigrants chose to come to the US under their free will, whereas refugees did not have much liberty to choose when and where they would be resettled for humanitarian purposes. Hence, economic immigrants and refugees differ primarily based on the length of time and variety of resources they have at their home country to prepare for settlement in the United States, namely acquiring English skills to increase the likelihood of employment. Refugees are likely to have less time and fewer resources to gain such US-specific skills prior to immigration and therefore be disadvantaged in the US labor market. It is hence important for policymakers to understand how the refugees fare in the United States to formulate better humanitarian resettlement programs. This paper aims to investigate how refugees perform in the US labor market in relation to economic immigrants, while controlling for demographic and human capital variables. The paper is organized in the following order: literature review, theoretical model, data/ empirical model, empirical results, and conclusion.

Traditionally, skyline and ranking queries have been treated separately as alternative ways of discovering interesting data in potentially large datasets. While ranking queries adopt a specific scoring function to rank tuples, skyline queries return the set of non-dominated tuples and are independent of attribute scales and scoring functions. Ranking queries are thus less general, but usually cheaper to compute and widely used in data management systems. We propose a framework to seamlessly integrate these two approaches by introducing the notion of restricted skyline queries (R-skylines). We propose R-skyline operators that generalize both skyline and ranking queries by applying the notion of dominance to a set of scoring functions of interest. Such sets can be characterized, e.g., by imposing constraints on the function’s parameters, such as the weights in a linear scoring function. We discuss the formal properties of these new operators, show how to implement them efficiently, and evaluate them on both synthetic and real datasets.

BACKGROUND: American migration rates have declined by nearly half since the mid-20th century, but it is not clear why. While the emerging literature on the topic stresses the salience of shifts in the composition of the American population, estimates of the contribution of population aging, increasing diversity, rising homeownership, and other shifts vary widely. Furthermore, it is unclear whether and how compositional shifts differ in their effects on migration over different geographic scales. OBJECTIVE: To gauge the contribution of compositional shifts to concomitant declines in migration over various distances, while allowing for group variations in the rates at which declines occur. METHODS: Drawing on individual-level IPUMS Current Population Survey data from 1982 to 2015, I use the Oaxaca–Blinder method to decompose declines in interstate migration, intrastate migration, and intracounty mobility. RESULTS: Between a quarter and a third of declines since 1982 are attributable to aging and increasing diversity. Changing ethnoracial composition exerts a stronger influence on interstate migration, while aging has a stronger effect on local mobility. Results also reveal more dramatic declines among non-Latino Whites and those under age 35, as well as a marked delay and decline in peak mobility rates with each successive birth cohort. CONCLUSIONS: Results point to social and economic shifts as the key drivers of American immobility, and the need for reorientation within the emerging literature. Future research should investigate the causes of group-specific rates of decline and focus on local mobility, where declines are most concentrated and where rising immobility is most problematic.

Between 1981 and 2008, US college attainment rates rose faster for young women than men. However, after the 2008 “Mancession,” male attainment rose faster than female attainment. The most widely supported explanations for women’s domination of the pre-2008 college expansion (improved contraceptive and household technologies, no-fault divorce laws, and young women’s greater college readiness), do not readily explain the post-2008 reversal in gendered attainment trends. We show, in a variety of ways, that sharp differences in female and male employment trends before and after 2008 offer a plausible account for the post-2008 reversal of gendered attainment trends. Pre-2008, a rapid increase in the representation of women in high wage occupations increased the incentive for women to go to college. Post-2008, this trend disappeared, and men, driven by receding opportunities in traditionally male sectors, were incentivized to go to college seeking access to service jobs, especially those whose wages are institutionally shielded from labor market competition. These results indicate some convergences in the ways that men and women capitalize on their college educations in the labor market.

U.S. early-life (ages 1–24) deaths are tragic, far too common, and largely preventable. Yet demographers have focused scant attention on U.S. early-life mortality patterns, particularly as they vary across racial and ethnic groups. We employed the restricted-use 1999–2011 National Health Interview Survey–Linked Mortality Files and hazard models to examine racial/ethnic differences in early-life mortality. Our results reveal that these disparities are large, strongly related to differences in parental socioeconomic status, and expressed through different causes of death. Compared to non-Hispanic whites, non-Hispanic blacks experience 60 percent and Mexican Americans 32 percent higher risk of death over the follow-up period, with demographic controls. Our finding that Mexican Americans experience higher early-life mortality risk than non-Hispanic whites differs from much of the literature on adult mortality. We also show that these racial/ethnic differences attenuate with controls for family structure and especially with measures of socioeconomic status. For example, higher mortality risk among Mexican Americans than among non-Hispanic whites is no longer significant once we controlled for mother’s education or family income. Our results strongly suggest that eliminating socioeconomic gaps across groups is the key to enhanced survival for children and adolescents in racial/ethnic minority groups.

College graduates are considerably more mobile than non-graduates, and previous literature suggests that the difference is at least partially attributable to college graduates being more responsive to employment opportunities in other areas. However, there exist considerable differences in migration rates by college major that have gone largely unexplained. This paper uses microdata from the American Community Survey to examine how the migration decisions of young college graduates are affected by earnings in their college major. Results indicate that higher major-specific earnings in an individual’s state of birth reduce out-migration suggesting that college graduates are attracted toward areas that especially reward the specific type of human capital that they possess.

This report presents an examination of innovation among women in STEM fields by identifying gaps in their entrepreneurial outcomes and highlighting future opportunities for policy improvements. First, it presents results of a descriptive data analysis using data from 2015 American Community Survey (ACS) and U.S. Census Bureaus 2007 and 2012 Survey of Business Owners (SBO). This empirical analysis compares characteristics and outcomes of women and men entrepreneurs in STEM fields; women entrepreneurs in STEM and non-STEM fields; and self-employed women and women in wage/salary employment in STEM fields. The empirical analysis employs two proxies for entrepreneurship based on availability in the data: self-employment in examining ACS data and business ownership in examining SBO data. Furthermore, it focuses on commercialization of scientific innovations in its initial phase: the creation of intellectual property.

Due in large part to increased migration from Africa and the Caribbean, black immigrants and their descendants are drastically changing the contours of health disparities among blacks in the United States. While prior studies have examined health variation among black immigrants by region of birth, few have explored the degree of variation in health behaviors, particularly smoking patterns, among first- and second- generation black immigrants by ancestral heritage. Using data from the 19952011 waves of the Tobacco Use Supplements of the Current Population Survey (TUS-CPS), we examine variation in current smoking status among first-, second-, and third/higher- generation black immigrants. Specifically, we investigate these differences among all black immigrants and then provide separate analyses for individuals with ancestry from the English-speaking Caribbean (West Indies), Haiti, Latin America, and Africathe primary sending regions of black immigrants to the United States. We also explore differences in smoking behavior by gender. The results show that, relative to third/higher generation blacks, first-generation black immigrants are less likely to report being current smokers. Within the first-generation, immigrants who migrated after age 13 have a lower probability of smoking relative to those who migrated at or under age 13. Disparities in smoking prevalence among the first-generation by age at migration are largest among black immigrants from Latin America. The results also suggest that second-generation immigrants with two foreign-born parents are generally less likely to smoke than the third/higher generation. We find no statistically significant difference in smoking between second-generation immigrants with mixed nativity parents and the third or higher generation. Among individuals with West Indian, Haitian, Latin American, and African ancestry, the probability of being a current smoker increases with each successive generation. The intergenerational increase in smoking, however, is slower among individuals with African ancestry. Finally, with few exceptions, our results suggest that intergenerational gaps in smoking behavior are larger among women compared to men. As additional sources of data for this population become available, researchers should investigate which ancestral subgroups are driving the favorable smoking patterns for the African origin population.

The female labor force participation rate in the United States leveled off around 1990 and began to decrease in the late 1990s. This paper shows that structural changes in the child care market play a substantial role in influencing the evolution of female labor force participation. I first provide new estimates of long-term trends in prices and hours of child care using the Survey of Income and Program Participation. Hourly expenditures on child care rose by 32% and hours of daycare used declined by 27%. Then, I build a life-cycle model of married couples that features a menu of child care options to capture important features of reality. The calibrated model predicts that the rise in child care costs leads to a 5% decline in total employment of females, holding all else constant. Finally, this paper provides two hypotheses and their supporting evidence about the causes of rising child care costs: (i) restrictive licensing to home-based child care providers, and (ii) the negative effect of expanded child care subsidies to lower income households on the incentives for those individuals to operate the home-based daycare.

In this paper we examine the effect of immigration into the U.S. on the U.S. housing market, both in terms of rents and single family house prices. We model the housing market in a spatial econometrics context using the spatial Durbin model. This approach helps us exploit and capture both the direct and indirect effects of immigration inflows on the U.S. housing market. We find that an increase in immigration inflows into a particular MSA is associated with increases in rents and with house prices in that MSA while also seeming to drive up rents and prices in neighboring MSAs. The patterns observed in the rental and house price markets, along with the larger spillover effects, are consistent with native-flight from immigrant receiving areas.