Recently, there is a surge of interest on mining valuable information from the given datasets. As one of the most important information mining tasks, influence analysis has drawn tremendous attention in both industry and academic communities. Due to the large scale of dataset, there is an emerging call for efficient processing influence related queries. In this thesis, we study three important influence related problems regarding three types of data, i.e., product and user preference data, spatio-textual objects, and set-valued data. Firstly, for product and user preference data, we formulate the problem of influence-based cost optimization on user preference functions, which is critical to unlock the great scientific and social-economic value of these data. By utilizing the classical k-level computation techniques, we show the solution space of our problem can be reduced to a finite number of possible positions (points). To efficient . . .

The influence of environmental conditions on fertility decision-making is becoming increasingly important in the context of contemporary climate change. Deforestation, land availability, and environmental quality may shape decisions regarding family size, particularly in regions with high levels of natural resource dependence. This research examines the relationship between fertility timing and precipitation in rural Mexico by linking household event-history data to municipal-level precipitation measures. Even after controlling for other factors that impact fertility, in historically dry areas, households are more likely to have a child following above average precipitation, using both 1-year and 2-year prior precipitation measures. Conversely, the relationship between precipitation and fertility timing in humid areas of rural Mexico is not statistically significant. Overall, the findings reveal that the fertility-environment connection is highly context-specific and differs across climate zones in Mexico, but that fertility timing is associated with recent rainfall patterns for households in dry areas of rural Mexico.

The model presented in this paper experiments with a comprehensive simulant agent in order to provide an exploratory platform in which simulation modelers may try alternative scenarios and participation in policy decision-making. The framework is built in a computationally distributed online format in which users can join in and visually explore the results. Modeled activity involves daily routine errands, such as shopping, visiting the doctor or engaging in the labor market. Further, agents make everyday decisions based on individual behavioral attributes and minimal requirements, according to social and contagion networks. Fully developed firms and governments are also included in the model allowing for taxes collection, production decisions, bankruptcy and change in ownership. The contributions to the literature are manifold. They include (a) a comprehensive model with detailing of the agents and firms activities and processes and original use of simultaneously (b) reinforcement learning for firm pricing and demand allocation; (c) social contagion for disease spreading and social network for hiring opportunities; and (d) Bayesian networks for demographic-like generation of agents. All of that within a (e) visually rich environment and multiple use of databases. Hence, the model provides a comprehensive framework from where interactions among citizens, firms and governments can be easily explored allowing for learning and visualization of policies and scenarios.

The purpose of this report is to explore the importance of paid medical, family, and parental leave for workers with disabilities and unpaid family caregivers (who may or may not themselves have a disability) of children, parents, or other family members (working or not) with disabilities. In other words, the report focuses on paid leave for both people with disabilities who receive care and people with or without disabilities who provide supports and services to them. The report begins with a brief overview of statistical data on disability and work in the United States. It then explores the benefits of paid leave for people with disabilities and their families before providing an overview of current access to and utilization of paid leave. Finally, it outlines principles to maximize the impact and reach of paid leave for people with disabilities and their families.

The construction of new or renovation of old theaters; sport stadiums; museums; casinos; parks; and other destination sites (i.e., henceforth referred to as “destination redevelopments”) are among the most popular, alluring and expensive types of urban revitalization projects around the world. In addition to aiming to attract new visitors, local officials and other community stakeholders often invest in these projects in an attempt to both retain existing residents and recruit new residents into the neighborhoods in which these redevelopments are located. Previous research has documented some of the socioeconomic effect of specific subcategories of destination redevelopments, most particularly with respect to its impact on real estate value. However, despite the fact that the entire category of these projects are promoted to have a similar socioeconomic impact, many of the subcategories are relevant to only specific cities. Scant research has explored the degree to which this entire category of redevelopments alters the local socioeconomic composition of nearby neighborhoods. Moreover, previous studies have tended to draw conclusions about local statistical changes without simultaneously controlling for municipal trends, trends in commonly defining characteristics (for analyses of cohorts), and the effects of spatial dependency. To bridge these gaps in the literature, the present research proposes a novel geographically-weighted shift-share analysis approach that uses GIS to analyze the socioeconomic impacts at the local level. It then applies this technique to assess the impact of the collective category of destination redevelopments in the seemingly disparate cites of Detroit and Las Vegas between 1990 and 2010.

While scholars have been developing valuable research on race and racism for decades, this work does not often reach the beginning college student or the general public, who rarely learn a basic history of race and racism. If we are to dismantle systemic racism and create a more just society, people need a place to begin. This accessible, introductory, and interdisciplinary guide can be one such place. Grounded in critical race theory, this book uses the metaphor of the Racism Machine to highlight that race is a social construct and that racism is a system of oppression based on invented racial categories. It debunks the false ideology that race is biological. As a manual, this book presents clear instructions for understanding the history of race, including whiteness, starting in colonial America, where the elite created a hierarchy of racial categories to maintain their power through a divide-and-conquer strategy. As a toolbox, this book provides a variety of specific action steps that readers can take once they have developed a foundational understanding of the history of white supremacy, a history that includes how the Racism Machine has been recalibrated to perpetuate racism in a supposedly "post-racial" era.

This dissertation is composed of three distinct studies. Study 1 asks what type of 'public opinion' is most likely to influence policy. Studies arguing for a strong link between public opinion and policy outcomes have focused on purely political sentiments almost exclusively. These studies have neglected to account for research on racialized politics which suggests racial sentiments often play a key role in shaping policy outcomes. Yet as often as public opinion is implicated for policy outcomes, and as often as racial sentiments are implicated in public opinion, few studies have quantitatively assessed the link between racial factors and actual policy outcomes. The goal of the present study is to address this gap by analyzing the relative influence of liberal-conservative ideology, attitudes about the role of government, policy-specific preferences, and racial sentiments for Medicaid generosity in the U.S. states from 1988-2012. This study analyzes a unique dataset composed of MRP public opinion estimates, socio-structural measure, and Medicaid . . .

We explore the early effects of recent Medicaid expansions on prescriptions and Medicaid payments for evidence-based smoking cessation medications: Zyban, Chantix, and Nicotrol. We estimate differences-in-differences models using data on the universe of prescription medications sold in retail and online pharmacies for which Medicaid was a third-party payer. Our findings suggest that expansions increased smoking cessation prescriptions by 36% and total payments for these medications by 28%. We provide evidence that these payments were financed by Medicaid programs and not patients. Overall our findings suggest that the recent Medicaid expansions allowed low-income smokers to access efficacious cessation medications.

There is substantial evidence on the importance of education as a driver of earnings, productivity, and economic growth. However, knowledge of the specific role of associate's degrees in U.S. economic growth is limited. We analyze the sources of U.S. economic growth and identify the contribution of associate's degree holders to improvements in earnings, labor quality, productivity, and overall economic growth. We find evidence that substitution toward workers with associate's degrees has increased U.S. earnings, aggregate labor quality, and productivity, and that these effects are concentrated in the health care, trade, and government sectors. While the average educational attainment of people entering the labor force has plateaued, our results suggest that shifting workers from some college to associate degrees could improve earnings, the quality of the workforce, productivity, and growth, potentially without more time spent in school.

The share of foreign-born workers in the U.S. information technology (IT) industry is much higher than their share of the labor force. In fact, foreign-born workers hold more than half the creative IT jobs located in metropolitan areas where IT innovation clusters are located. Nevertheless, except for in Silicon Valley, U.S.-born workers and workers born abroad to American parents still hold the highest proportion of creative IT jobs.

Current evaluations of career technical education (CTE) programs seeking to assess labor outcomes for individuals are missing a generalizable model of program quality. Studies either focus on differences between CTE participants and those who do not participate or on specific, non-generalizable program effects. Using broad quality measures developed in a paper published by the Metropolitan Policy Center at Brookings as well as ACS and CPS survey data, this study seeks to assess whether the established program quality metrics used by Brookings hold for CTE programs and hold when applied to a broad population study.

Several studies have argued that teacher pensions are a raw deal for most teachers and should be replaced with account-style plans. This report examines research that most teachers working today are building a secure retirement. According to the author, the myth that most teachers get a raw deal while a lucky few receive generous pensions is based on flawed studies that give equal weight to career teachers and to those who leave after a year or two. A shift to account-style plans would not benefit most teachers and would increase teacher turnover to the detriment of students. While the existing pension system can and should be tweaked to meet changing needs, it successfully serves the goals of attracting and retaining teachers, promoting orderly retirement, and providing retirement security.

Access to financing is one of the main issues firms are dealing with. In general, financial constraints determine firms’ development and their size distribution (Angelini and Generale, 2008). Especially for small and medium-sized firms with constrained access to bond or equity markets (The Economist, 2015), bank loans account for the primary part of external financing (Berger and Udell, 2002). This project analyzes how entrepreneurs and banks interact by modeling long-term credit relationships between them. Long-term credit relationships help to overcome information asymmetries through dynamic contracting. To the best of our knowledge we are the first who deal with such a long-term lending relationship in a general equilibrium framework . . .

Statistical agencies frequently publish microdata that have been altered to protect confidentiality. Such data retain utility for many types of broad analyses but can yield biased or insufficiently precise results in others. Research access to de-identified versions of the restricted-use data with little or no alteration is often possible, albeit costly and time-consuming. We investigate the advantages and disadvantages of public-use and restricted-use data from the American Community Survey (ACS) in constructing a wage index. The public-use data used were Public Use Microdata Samples, while the restricted-use data were accessed via a Federal Statistical Research Data Center. We discuss the advantages and disadvantages of each data source and compare estimated CWIs and standard errors at the state and labor market levels.

The decade-long decline in the homeownership rate in the United States has generated substantial discussion over its future path. In the face of continued uncertainty, this Article seeks to assess what we know and do not know about the sources of the decline and the likely trajectory of the homeownership rate in coming years. The analyses use the Annual Social and Economic Supplement (ASEC) of the Current Population Survey for 1985 to 2015 to examine the determinants of changes in the homeownership rate, using shift-share analyses to measure the extent to which changing demographics explain the observed changes. The results show that demographic trends—aging of the population, increasing racial/ethnic diversity, delayed marriage and childbirth, and related factors—explain only a small portion of the housing market’s boom and bust. Instead, the homeownership rate’s rise and fall have been due to broader changes in the economy, credit conditions, and housing markets. This Article then presents homeownership projections for 2015 to 2035, describing three scenarios that define a range of homeownership outcomes. The low and high scenarios presented in this Article produce a range for the national homeownership rate of 60.7% to 64.8% by 2035. The analyses describe the implications of each scenario for growth in the number of homeowner households, as well as the distributional implications of lower versus higher homeownership rates for homeownership outcomes by age, race/ethnicity, and family type.

The goal of this project was to identify locations along MSHs that present high risk for the occurrence of pedestrian and bicyclist collisions and to determine the characteristics of those locations that are associated with high collision risk. The study was conducted in two parts. One determined methods to identify collision hotspots on MSHs. Hotspot analyses point to locations with high frequencies of collisions. These hotspots can be used to identify problematic locations that are potential candidates for safety improvements. For example, identifying and ranking high traffic collision zones is essential for developing and enforcing efficient countermeasures for pedestrian and bike safety. Knowing the locations of collision hotspots will also guide law enforcement and safety policies and priorities. Departments of transportation can focus on these zones to enhance traffic safety within their limited financial resources. The second part of the study employed models to examine the effects on the risk of collision occurrence of MSH infrastructure and traffic characteristics, as well as the land use and built environment characteristics, along the MSHs. Supporting material can be found in the Appendices.

The 1965 Immigration Act allowed a huge influx of new immigrants from Latin America, Asia, and the Caribbean, which extremely increased the levels of racial/ethnic composition of the U.S. society. Despite the fact that immigration from Europe to the U.S. has not stopped in this new era, the majority of research has focused on the labor market experiences of these nonwhite immigrants. New immigrant groups are also added to the white racial category as the U.S. Census Bureau started to refer "white” to a person having origins in any of the original peoples of Europe, the Middle East, or North Africa. However, there is a shortage of academic research on the labor market experiences of these foreign-born non-Hispanic white immigrants, who differ in size, ethnic composition, socioeconomic background and geographic dispersion in the U.S. society. This research aims to fill this gap by examining whether or not earnings disparity exists between these immigrants and non-Hispanic US-born white Americans, and how much of this disparity is determined by the intersection of ethnicity and gender along with individual- and structural-level characteristics. Applying multilevel regression models to the combined waves of data from the IPUMS and U.S. Census Bureau (1980-2010), the results show that earnings vary by ethnicity/gender, and there is significant earnings inequality between US-born white men and foreign-born white immigrants. Even more pronounced is significant gender earnings inequality within and between ethnic groups. Earnings gaps significantly vary across local labor markets, but much of the difference is determined by ethnicity/gender and individual-level predictors. Compared to temporal and regional context, local labor market context is not a major determinant of earnings achievement in the U.S. However, while the direct effects of local labor markets are trivial, they do have indirect effects on earnings through individual factors.

The labor force participation rate has been falling in this country for nearly two decades. For men of prime working age, it has been falling for more than half a century. And the fall has been particularly acute among black men. The decline in participation has also accelerated since the Great Recession, largely due to the start of retirement by baby boomers. Low participation is distinct from unemployment—looking for a job but not finding one—which has fallen sharply since the recession. It is also distinct from the lingering problem of underemployment— settling for part-time or occasional work but wanting full-time work that matches one’s skills. Rather, a falling participation rate means more people are simply unable or unwilling to work at current wages.

Polarisation in the labour market involves a fall in the share of intermediate-level jobs in an economy, and a simultaneous rise in both high- and low-level jobs. It therefore represents a break from late twentieth-century thinking, where skills were typically thought as being a dichotomy of high and low, rather than a trichotomy of high, intermediate and low levels, and when it was supposed that . . .

Many immigrants lack both English skills and health insurance coverage. Understanding the effect of English skills on health insurance is difficult because English skills are correlated with many unobservable characteristics that are also related to health insurance. In this paper, I exploit the fact that young children can learn a new language much more easily than older children to examine how English skills affect health insurance coverage for immigrants and their children. I find that English skills greatly improve immigrants' access to employer-sponsored health insurance. While Medicaid covers a majority of children who do not have employer-sponsored health insurance because of their immigrant parents' poor English skills, immigrants with poor English skills are much more likely to be uninsured. I test for heterogeneous responses to Medicaid expansions based on English ability and find evidence that the effect of satisfying Medicaid's income requirements on Medicaid coverage is smallest for immigrants with the worst English skills, which suggests that the different effects for parents and their children may not be entirely because of different Medicaid income thresholds for adults and children.