The slow growth of high-paying jobs in the U.S. since 2000 and rapid advances in computer technology have sparked fears that human labor will eventually be rendered obsolete. Yet while computers perform cognitive tasks of rapidly increasing complexity, simple human interaction has proven difficult to automate. In this paper, I show that the labor market increasingly rewards social skills. Since 1980, jobs with high social skill requirements have experienced greater relative growth throughout the wage distribution. Moreover, employment and wage growth has been strongest in jobs that require high levels of both cognitive skill and social skill. To understand these patterns, I develop a model of team production where workers trade tasks to exploit their comparative advantage. In the model, social skills reduce coordination costs, allowing workers to specialize and trade more efficiently. The model generates predictions about sorting and the relative returns to skill across occupations, which I test and confirm using data from the NLSY79. The female advantage in social skills may have played some role in the narrowing of gender gaps in labor market outcomes since 1980.

This paper examines the impact of immigration on income inequality. Using data from 1990 and 2000 US Censuses, we link the changes in income inequality as measured by the Gini index with immigrant flows into each metropolitan area in the U.S. We address endogeneity of immigrant inflows by relying on variation in historical distribution of earlier immigrants from each source country. The results suggest that using the Gini index as a measure of income inequality results in immigration having stronger effects on inequality than the findings of other studies based on changes in skill-related wage premiums. Interestingly, low-skilled immigration as proxied by Mexican immigration is found to have little effect on income inequality. However, the estimates are subject to a downward bias if native workers respond to an increase in low-skilled immigration by moving away from the affected locations.

This report uses data on same-sex couples in the 2012 American Community Survey to assess the impact on LGB and heterosexual poverty rates of several types of hypothetical changes: one that reduces the gender wage gap between men and women, one that reduces the wage gaps for people of color (the gap between white and black workers and the gap between Hispanic and non-Hispanic workers), and one that reduces the wage gap for gay and bisexual men compared with heterosexual men. These changes could come from new policies designed to address wage gaps, such as reductions in the gender wage gap resulting from a policy of paid family leave, or through more stringent enforcement of new or existing nondiscrimination laws.

BACKGROUND: Chronic Obstructive Pulmonary Disease (COPD) is the third leading cause of death in USA, known to annually cause 134,676 American deaths. In 2011, it was estimated that 12.7 million adults were living with COPD and there are over 800,000 COPD-related hospital admissions in the USA annually. The increase in prevalence of COPD, and the severity of the disease, highlights the need for intervention in COPD treatment with a focus on prevention of exacerbations and self-management. Current research illustrates a number of ways to effectively manage COPD disease progression including: use of the GOLD guidelines to classify and treat COPD, medication, smoking cessation, and proper self-management of disease. However, there is very little research exploring the impact of healthcare provider-delivered, comprehensive patient education and smoking cessation counseling to improve self-management of COPD and contribute to the prevention of hospital readmissions. PURPOSE: The purpose of this study was to determine the perceived benefits and potential reduction of hospital readmission following COPD disease self-management education and smoking cessation counselling facilitated by trained Respiratory Therapists (RT). METHODS: A retrospective chart review of the first 10 months of an RT-delivered COPD education service with COPD patients on a specific service at The Wexner Medical Center was conducted. RTs administered patient education and recorded an assessment and evaluation in the electronic health record regarding the education session. A COPD assessment test (CAT) was also administered together with initial assessment of the patient by respiratory therapist. After collection of initial assessment data and delivery of the CAT instrument, patients were seen for follow-up by an RT and received tailored COPD education. Following the education session, patients were seen again once or twice more before they were discharged. The group of COPD patients who were not seen by the RT for patient education was also examined Results: Eighty three out of 204 (40.7%) patients with primary or secondary diagnosis of COPD received COPD education by Respiratory Therapists. These patients also had an average of over 2 hospitalizations in the past year, average smoking history of 39.3 pack years and over 3 additional comorbidities at the time of hospitalization. Greater than 85% of admitted patients with COPD diagnosis, who self-identified as current smokers, did not receive NRT. The percentage of respiratory related readmissions for patients seen by respiratory therapists and not seen by respiratory therapists was 10.8% and 11.6% respectively. The number of patients who received pulmonary rehabilitation prior to admission was 10 (12%). Conclusion: COPD education provided by an RT is a valuable intervention to managing COPD patients disease progression. RTs can play a larger role by contributing more to the COPD management program including smoking cessation programs and pulmonary rehabilitation information/counseling as part of the COPD education. RTs can also be placed at transitional care to provide more long term management of patients with COPD. Medication management should include tailored medication based on individual patients GOLD classification and should be a critical part of the COPD education provided by RTs.

This paper explores how inflows of low-skilled immigrants impact the tradeoffs women face when making joint fertility and labor supply decisions. I find increases in fertility and decreases in labor force participation rates among high-skilled US-born women in cities that have experienced larger immigrant inflows. Most interestingly, these changes have been accompanied by decreases in the strength of the negative correlation between childbearing and labor force participation, an often-used measure of the difficulty with which women combine motherhood and labor market work. Using a structured statistical model, I show that the immigrant-induced attenuation of this negative correlation can explain about 24% of the immigrant-induced increases in the joint likelihood of childbearing and labor force participation in the US between the years 1980 and 2000.

We consider a new source of racial disparities in test scores: African American students' disproportionate exposure to environmental toxins, and, in particular, lead. Using a unique individual-level dataset of children's preschool lead levels linked with future educational outcomes for children in Rhode Island, we show that state policies aimed at reducing lead exposure led to significant declines in children's blood lead levels among cohorts born between 1997 and 2004. Exploiting the change in child lead levels as a result of the policy, we generate causal estimates of the impact of preschool lead levels on reading and math test scores from grade three through grade eight in an IV framework. We find that a 5 micrograms per deciliter increase in child lead levels (the threshold at which the CDC recommends intervention) reduces test scores by 6 points or 43 percent of a standard deviation. The effects are stronger in the lower tail of the test score distribution and do not fade over time. The decline in racial disparities in lead exposures can explain roughly half of the 32 percent decline in the racial gap in test scores in these cohorts. JEL Codes: I24, J15, Q53, Q58 We thank Rebecca Lee and Alyssa Sylvaria of the Providence Plan for their generosity and help with the data,

Housing units within small and medium multi-family (SMMF) properties, defined as buildings with 2 to 49 units, comprise over 20% of the U.S. housing stock and are located primarily within the central cities or suburbs of metropolitan areas. However, this category of properties has sometimes been overlooked both in the media as well as in research, which have focused instead on the single-family and large multi-family (over 50 units) categories. Amalgamating the American Community Survey, American Housing Survey, and DataQuick databases, this study situates this segment of the U.S. housing stock in context by looking at cross-category comparisons and change over time. We map the geographic distribution of SMMF properties, describe their characteristics, and evaluate the degree to which they contribute to affordability within their specific market areas. Our data sets allow a rich examination of the variations both within the SMMF category and in comparison to the single- family and large multi-family property categories. The resulting analyses allow us to draw policy-relevant conclusions about this large segment of the housing stock and its importance in shaping housing supply and affordability at a national and regional level.

Rapid population growth, water and air pollution, overloaded public services, and traffic congestion can stress economies and result in unsustainable communities. Geographic Information Science (GIS) is a valuable technology for reversing negative these types of trends by identifying areas that may presently exhibit Smart Growth characteristics. Rather than expand on the current transportation infrastructure and develop new Smart Growth communities, San Diego Metropolitan’s Transit System (SDMTS) intends to use this study to review the current transit routing infrastructure in an effort to support communities exhibiting Smart Growth potential. Communities along existing transportation infrastructure will analyzed as potential Smart Growth and TOD communities. After the study is completed, SDMTS will have the geospatial data necessary for supporting future Smart Growth development.

The goal of these technical appendices is to provide detailed information on the methods, assumptions, and validation exercises we have undertaken in creating the California Poverty Measure (CPM). The key motivation for developing the CPM is to provide an arguably more accurate and comprehensive picture of poverty. This is no simple task, because the resources, expenses, and standards of living of California families must all be individually measured using a variety of data sources and methods. Indeed, this work is the product of a joint collaboration between the Stanford Center on Poverty and Inequality and the Public Policy Institute of California.

This study explores how industry-specific technological, organizational, and managerial features affected the employment of old male manufacturing workers in the early-twentieth-century United States. Industrial characteristics favorably related to the employment of old industrial workers include high labor productivity, less capital-and material-intensive production, short workdays, low intensity of work, high job flexibility, and formalized employment relationships. Results show that aged industrial workers were heavily concentrated in "unfavorable" industries, suggesting that the contemporary argument of "industrial scrap heap" was applicable for most of the manufacturing workers in the early-twentieth-century United States.

This study revisited the association of demographic predictors of environmental injustice with the location of Toxic Storage and Distribution (TSD) facilities sited between 1990 and 2000 in Texas. Using Ordinary Least Squares regression of extracted geospatial data, it determined that a shifting temporal dynamic in the location of the 31 TSD's permitted by the Texas Commission of Environmental Quality (TCEQ) followed paths of weak resistance enabled by low median house value and race (p-value<.05). The study reports a significant shift of TSD's to locations in Hispanic populated areas. Though, past studies provided bounded theoretical judgments, the present research concluded that, rational choice, inadvertence, and discrimination jointly predicted environmental injustice and recommends the facilitation of equity through shared responsibility and governance.

This paper examines the relationship between mayoral political ideology and siting decisions for affordable housing during two different periods in New York City. On the overarching goal of housing programs—the supply of housing affordable to low-income families and thus sustainable development—the United States government had endeavored to meet two trends: (1) the geographical and social integration of communities composed of households of varying incomes and other socio- economic traits, and (2) the encouragement of private investment, with the aim of reducing reliance on public subsidies. From the political-economic standpoint of urban theory, “distributive justice” maintains an emphasis on the development of affordable housing without residential segregation, whereas the concept of “economic efficiency” refers to promoting the economic development of a community in order to attract private investment. This conflict between distinct purposes of housing developments has been apparent in New York City. Given such conditions, two different mayors in office at two different times, Edward I. Koch and Michael R. Bloomberg, both confronted housing crises and presented large plans for addressing them. Koch, who was mayor during the 1980s, as a Democrat was concerned with distributive justice, whereas Bloomberg was a Republican whose political ideology was oriented towards economic efficiency. In this paper, I test whether the political ideology of the two mayors had an impact on placements in affordable housing, and the extent to which the housing developments that were built were oriented towards social integration or encouragement for private investment. Using regression analysis, I compare the characteristics of neighborhoods where the two administrations developed affordable housing units, focusing on racial composition, socio-economic factors, and property attributes.

Emergency visits are rising nationally, whereas the number of emergency departments is shrinking. However, volume has not increased uniformly at all emergency departments. It is unclear what factors account for this variability in emergency volume growth rates. The objective of this study was to test the association of hospital and population characteristics and the effect of hospital closures with increases in emergency department volume. The study team analyzed emergency department volume at New York State hospitals from 2004 to 2010 using data from cost reports and administrative databases. Multivariate regression was used to evaluate characteristics associated with emergency volume growth. Spatial analytics and distances between hospitals were used in calculating the predicted impact of hospital closures on emergency department use. Among the 192 New York hospitals open from 2004 to 2010, the mean annual increase in emergency department visits was 2.7%, but the range was wide (-5.5% to 11.3%). Emergency volume increased nearly twice as fast at tertiary referral centers (4.8%) and nonurban hospitals (3.7% versus urban at 2.1%) after adjusting for other characteristics. The effect of hospital closures also strongly predicted variation in growth. Emergency volume is increasing faster at specific hospitals: tertiary referral centers, nonurban hospitals, and those near hospital closures. This study provides an understanding of how emergency volume varies among hospitals and predicts the effect of hospital closures in a statewide region. Understanding the impact of these factors on emergency department use is essential to ensure that these populations have access to critical emergency services.

A drawback to research on interracial couplings is that it almost exclusively studies heterosexual relationships. However, compelling new evidence from analyses using the Census shows that interracial relationships are significantly more common among the gay population. It is unclear how much of this reflects weaker racial preference or more limited dating markets. This paper examines the interactions of white gay and straight online daters who have access to a large market of potential partners by modeling dyadic messaging behaviors. Results show that racial preferences are highly gendered, and do not line up neatly by gay or straight identity. White lesbians and straight men show the weakest same-race preference, followed by gay men, while straight women show the strongest same-race preference. Put differently, minority men are discriminated to a greater degree than minority women in both same-sex and different-sex dating markets. These results suggest that white gay men's higher rates of interracial cohabitation are driven more by constrained dating markets, while lesbians' appear to be driven by more open racial preferences.

We estimated the 2014 and 2024 population of U.S. Veterans using a cohort component population projection method at the Public Use Microdata Area (PUMA) level. Data for this analysis came from the U.S. Census for baseline national projections. We factored in estimates of mortality, adjusted for demographic characteristics, and added data from the U.S. Department of Defense (DoD) on Veterans entering the population. We estimated migration flows of Veterans using gravity models. Supplementary data came from American Community Surveys (ACS) and accounted for a variety of factors, including age, sex, race/ethnicity, service era, population size of sending and receiving areas, and distance between areas.

The Mexican origin population is one of the largest and fastest-growing racial/ethnic minority groups in U.S. schools. Mexican origin students are also one of the most educationally disadvantaged subgroups, exhibiting gaps with peers in educational outcomes throughout the schooling pipeline. This dissertation examines the extent to which the racial/ethnic and socioeconomic composition of high schools attended by Mexican origin youth contribute to their disadvantaged educational outcomes. Using data from the Educational Longitudinal Study of 2002, this research evaluates how Mexican origin high school students are distributed across schools by the racial/ethnic and socioeconomic composition of their peers, and assesses how racially/ethnically and socioeconomically isolated school environments impact levels of dropout and school engagement among Mexican origin adolescents. The results show that Mexican origin youth are more racially/ethnically and socioeconomically isolated in schools than both non-Latino white and black students. Mexican origin youth show limited evidence of spatial assimilation across schools by immigrant generational status. However, Mexican origin youth in households with greater socioeconomic resources are enrolled in more racially/ethnically and socioeconomically integrated schools than those in the most impoverished households. Mexican origin high school students that attend racially/ethnically and socioeconomically isolated schools in 10th grade have a greater . . . .

Using longitudinal household survey data from rural China and an identification strategy based on observed rainfall realizations, we are able to test household responses to idiosyncratic and covariate income shocks. We find that negative idiosyncratic income shocks increase migration and elicit household out rental of land. The effect of covariate income shocks is generally dependent on both the timing and the nature of the shock. Our results suggest that rainfall deficiencies during paddy maturing or harvesting seasons reduce the number of migrants by raising the marginal value product of farm labour, thereby increasing the opportunity costs associated with migration.

The past century was a period of increasing life expectancy throughout the age range. This resulted in more people living to old age and to spending more years at the older ages. It is likely that increases in life expectancy at older ages will continue, but life expectancy at birth is unlikely to reach levels above 95 unless there is a fundamental change in our ability to delay the aging process. We have yet to experience much compression of morbidity as the age of onset of most health problems has not increased markedly. In recent decades, there have been some reductions in the prevalence of physical disability and dementia. At the same time, the prevalence of disease has increased markedly, in large part due to treatment which extends life for those with disease. Compressing morbidity or increasing the relative healthspan will require “delaying aging” or delaying the physiological change that results in disease and disability. While moving to life expectancies above age 95 and compressing morbidity substantially may require significant scientific breakthroughs; significant improvement in health and increases in life expectancy in the United States could be achieved with behavioral, life style, and policy changes that reduce socioeconomic disparities and allow us to reach the levels of health and life expectancy achieved in peer societies.

This thesis examines how potential accessibility(A(P)) through transportation over the time span of this study (1830-2010) affected population growth by county for the state of Tennessee. It focuses on shifts in transportation networks from waterways to rail, and rail to roadways,using decennial census data and likewise temporally adjusted county boundaries. The span of this study was broken into four individual time periods to best measure major transitions in transportation: waterways(1830 -1850), railways(1860 -1920), historic roads(1930 -1970), and modern roads(1980 - 2010). Potential accessibility, which was anticipated to have influenced the population change taking place within the state over time, was measured using Esri ArcMap geographical information system (GIS) and a series of network datasets. Calculations of population sums, geographic measurements, and network accessibility were accomplished using both Microsoft (MS) Excel and Esri ArcMap. Linear regression modeling was performed using Statistical Package for the Social Sciences (SPSS). The results suggest that the variable influence was dependent on the study period, and although conclusively correlated at times, other variables in addition to or other than transport accessibility also proved significant in several of the study periods. Specifically, the waterways study period showed a direct correlation with the population growth and transport networks during this time, though additional variables could have contributed to population change as well. The railway network did not significantly contribute to population changes going on during this time, likely directly related to the onset of the civil war which hindered the development and growth of this transport system. While starting population share proved to be significant, with higher growth in counties that started out with larger populations, again additional variables could help explain population growth during the railway study period. Potential accessibility and starting share collectively explained almost 90% of the variance within the historic road model, proving significant and likewise leaving very little of the change in population unexplained during that time period. Oddly, while the potential accessibility was significant, unlike theorized within this study counties less accessible to transport networks actually grew more quickly than those with higher accessibility. Finally, modern roads were found to be significant in population change as well and highly correlated. Additional steps to improve on this study in the future would include considering connections outside of the state, particularly in non-Tennessee peripheral localities with high populations. Secondly, investigation of additional variables such as economic data over a shorter overall time span, or using dasymetric allocation methods, could also provide further explanation behind population changes taking place over time.