Older and younger people have long been known to have very different social lives. Past research on support and close confidant networks has shown that old age is associated with less and more kin-focused social interaction. Yet, we know remarkably little about the ways in which older versus younger people access their personal networks during the comings-and-goings of daily living. Psychosocial theories, which emphasize preference and personality differences between the young and old, have richly informed explanations of why aging is associated with changes in various network characteristics. However, social structural theories, which emphasize how the availability of other people to interact with varies with the life course, has garnered much less attention as explanations of network differences between the young and old. This dissertation advances the state of knowledge on this topic by examining how people spend their time, who they spend their time with, and the extent to which age differences in time use are explained by life course and social structural factors. To address my research questions, I leverage interpersonal data on who is present during the performance of daily activities from a large sample of U.S. population using the American Time Use Survey. I find that life course and social structural variables account for a large part of the relationship between age and time spent with others. Depending on the relation, the social structure accounts for between 14\% and 65\% of the variance in social time. I find that elderly people tend to interact with others during leisure activities that are sui generis social while younger adults spend their leisure time with others on all types of leisure. Furthermore, poor health tends to suppress the effects of age on time spent doing certain activities (like social leisure) and tends to augment the effects of age on other activities (like traveling alone). These results strongly suggest that the social structure plays an important role in shaping social interaction across the life course.

Could racial wealth inequality have been reduced if freed slaves had been granted land following the Civil War? This paper exploits a plausibly exogenous variation in policies of the Cherokee Nation and southern United States to identify the impact of free land on the size of the racial wealth gap. Using data on land, livestock, and home ownership, I find evidence that former slaves who had access to free land were absolutely wealthier and experienced lower levels of racial wealth inequality in 1880 than former slaves who did not. Furthermore, their children continued to experience these advantages in 1900.

p-Sensitive k-anonymity model has been recently defined as a sophistication of k-anonymity. This new property requires that there be at least p distinct values for each sensitive attribute within the records sharing a set of quasi-identifier attributes. In this paper, we identify the situations when the p-sensitive k-anonymity property is not enough for the sensitive attributes protection. To overcome the shortcoming of the p-sensitive k-anonymity principle, we propose two new enhanced privacy requirements, namelyp+-sensitive k-anonymity and p,a-sensitive k-anonymity properties. These two new introduced models target at different perspectives. Instead of focusing on the specific values of sensitive attributes, p+-sensitive k-anonymity model concerns more about the categories that the values belong to. Although (p,a)-sensitive k-anonymity model still put the point on the specific values, it includes an ordinal metric system to measure how much the specific sensitive attribute values contribute to each QI-group. We make a thorough theoretical analysis of hardness in computing the data set that satisfies either pa-sensitive k anonymity or (p,a)-sensitive k-anonymity. We devise a set of algorithms using the idea of top-down specification, which is clearly illustrated in the paper. We implement our algorithms on two real-world data sets and show in the comprehensive experimental evaluations that the two new introduced models are superior to the previous method in terms of effectiveness and efficiency.

We propose a new identification strategy to measure the causal impact of government spending on the economy. Our methodology isolates exogenous cross-sectional variation in government spending using a novel instrument. We use the fact that a large number of federal spending programs depend on local population levels. Every ten years, the Census provides a count of local populations. Since a different method is used to estimate non-Census year populations, the discontinuous change in methodology leads to variation in the allocation of billions of dollars in federal spending. Our IV estimates imply that government spending has a local income multiplier of 1.88 and an estimated cost per job of $30,000 per year. We also show that the local effects are not larger than aggregate effects at the MSA and state levels. Finally, we characterize the heterogeneity of the impacts of government spending and find that it has a higher impact in low growth areas

Homeownership, a primary component of household wealth, confers benefits not just in terms of the value of home equity itself, but also the tax benefits and inflationprotection associated with owning property. The 1990s represented a booming time in the economy and record low interest rates which allowed homeownership to become moreavailable to more people than ever. As a result, the US housing market experienced significant growth and home values began to soar in part due to rising incomes. However,this period of rapid expansion in the housing market was followed by a rapid decline, precipitated by the recession, as home values began to plummet and foreclosures steadilyincreased. This study examines the impact that recent macroeconomic fluctuations had on the likelihood of homeownership for African American women compared to their white counterparts. Using data from the American Housing Survey (19972009), this tenure spatial analysis used a logistic regression model to examine the odds in favor ofhomeownership during economic fluctuations along with taking into consideration other important determinants. The empirical results show that there are significant differences in the likelihood of homeownership between African American women and white females.

After 1994, the homeownership rate in the USA departed from its historical secular pattern and increased from 64.0 percent in that year to a peak of 69.0 percent in 2004. Although it is currently trending down, the US homeownership rate is still above the levels recorded before 1998. This chapter summarizes its history and explains what factors are behind its recent behavior.

In this paper we estimate the utility functions over partners characteristics from the aggregate matching patterns, using a structural two-sided matching model without transfer. A distinct feature of our approach is the ability to separately identify utility functions of men and women, which is absent in the matching models with transfer;e.g., Choo and Siow (2006). We argue that the deferred-acceptance algorithm can be represented as a special demand/supply system. It thus leads to a fast algorithmto compute the joint distribution of characteristics of married couples implied by the model without simulation. Based on it, we present a set of new nonparametric identification results and propose consistent estimators, which are free from the curse of dimensionality induced by large number of players. Testable implications of Men(Women) optimal stable matching are also investigated. Furthermore, we consider the inference problem without imposing equilibrium selection. We show that a setof moment inequalities can be derived from the no-blocking-pair condition without solving the game. Besides marriage market, our estimators can also apply to other two-sided matching markets in labor and IO.We use the data of Current Population Survey to estimate the utility functions over spouses education level. We find that men care more about the similarity in spouseseducation than women do. Meanwhile, womens education level is becoming more attractive to men compared to 20 years ago. It is well known that marriage market is one of the key considerations of education choice, but such endogeneity problem in empirical two-sided matching models is usually assumed away. Therefore, we develop a structural pre-marital educational choice model that accounts for marriage market prospect. We use the estimated preference to compute the return to schooling within marriage, and estimate the cost distributions of education via the structural model. By shifting the cost distribution of women via the lump-sum tuition subsidy, we find that the college attendance rate increases for both women and men. Moreover, the new policy creates more college-educated couples, while the correlation of the joint distribution of education of married couples remains unchanged.

During the past century, innovation in mechanics, computing technology, medicine, and business practices has driven economic growth, raised wages, and helped Americans lead longer and healthier lives. The development of assembly line production, for example, and its application to the mass production of automobiles reduced the time to produce the Model T Ford by 68 percent over six years and reduced its cost by 62 percent, allowing middle-class families to afford what had once been a luxury (Williams, Haslam, and William 1992). The rapid pace of innovation and increases in productivity continued for most of the century, expanding the efficiency of American workers and providing more valuable goods and services at lower prices.Since the 1970s, however, the pace of innovation has slowed, leading to lower overall wage growth for American workers. Moreover, those gains that have been made have not been shared equally across society. Although average wages have risen, buoyed by strong gains at the top of the distribution, the wages of many Americans have stagnated or fallen after adjusting for the cost of living over the past forty years. Reinvigorating the momentum of innovation that benefits all Americans is imperative to create broad-based economic growth and higher living standards.To take on this challenge, The Hamilton Project held a forum, PhDs, Policies, and Patents: Innovation and Americas Future, on June 28, 2011. The discussion explored the evolving role of innovation in driving broad-based economic growth in the United States and the policy environment necessary to foster new ideas in science, technology, and business. From that conference The Hamilton Project pulled from the statements of each of our panelists to identify a dozen facts about innovation. These dozen facts encapsulate three themes: First, innovation has historically improved Americas overall standard of living through higher wages, lower prices, and health advancements. Second, the pace of innovation has slowed more recently and the gains from innovation have not benefitted all Americans. Third, in todays increasingly competitive global economy, current U.S. policies are not doing enough to promote innovation. Without purposeful policies and necessary investments to spur innovation, the United States may not experience the same sort of economic and technological advances in the current century that we enjoyed in the past.

The Early Childhood Advisory Council (ECAC) in Minnesota makes recommendations to the Governor and Legislature, and is responsible for fulfilling the duties required by federal and state statutes. The Council was created in 2008 by the Governor’s Executive Order 08-14. The ECAC consists of 18 members, including the State Director of the Head Start Collaboration, and one representative each from the Minnesota Departments of Education, Health and Human Services. The governor, the Minnesota House of Representatives and the Minnesota Senate each appoint members. At least two appointees are public members who are parents of a child under the age of six. The 2010 Minnesota Legislature directed Minnesota’s Early Childhood Advisory Council to make recommendations on the creation and implementation of a statewide School Readiness Report Card (Minn. Stat. § 124D.141.Subd 2 (5)). The purpose of the report card is to monitor the state’s progress toward the goal of having all children ready for kindergarten by the year 2020.1 (See Appendix A) The report card is to include both child outcomes and indicators of systems and services. The legislation stated that “costs incurred by the council in making these recommendations must be paid from private funds.” Private funds from the School Readiness Funders Coalition covered the costs, and Wilder Research was retained as the contractor to work with the Minnesota Departments of Education and Human Services, and the ECAC on developing the report card. This report documents the process Wilder Research used on behalf of ECAC to develop the report card indicators, including reviewing literature, working with ECAC committees, gathering feedback and comments from national experts and the public, and obtaining approval from the ECAC. It describes the indicators recommended to constitute the School Readiness Report Card, and the data sources and data collection timelines for each. Finally, the report presents recommendations on benchmarking.

For decades, investments in public education have boosted U.S. productivity and earnings, forged a path out of poverty for many families, helped disadvantaged students narrow the learning gap with their peers, and developed a workforce that continues to be among the most productive and innovative on Earth. More recently, this engine of growth has lost momentum. While per-pupil spending has continued to rise, educational attainment and performance have stagnated over the last thirty years. Because workforce skills are closely linked to productivity and compensation, the stagnation in education has contributed tostatic or even declining earnings for many Americans. In this paper, The Hamilton Project provides a dual-track approach to improving future educational outcomes: 1) tackling structural barriers to unlock the largest gains in student achievement and 2) in the near term, implementing relatively simple cost-effective reforms that improve student performance. The first approach examines opportunities for structural changes to Americas educational systema new way of doing business. These include generalizing the best practices of top performing charter schools and changing the current systems for identifying, hiring, and retaining highly-effective teachers. The second approach focuses on smaller, cost-effective reforms that could be implemented without dramatically re-thinking how schools operate, such as student incentive and early childhood education programs, and managerial and organizational changes at the school and district levels. In todays environment of tight school budgets, it is essential not just to know how different approaches impact student performance, but also how much they cost. To this end, The Hamilton Project outlines a metric for comparing educational interventions and calls on policymakers to identify and test more policies and programs in a consistent way. Taken as a whole or piecemeal, we believe these types of reforms hold the potential to reinvigorate our existing system of education.

Data publishing has generated much concern on individual privacy. Recent work has shownthat different background knowledge can bring various threats to the privacy of published data.In this paper, we study the privacy threat from the full functional dependency (FFD) that isused as part of adversary knowledge. We show that the cross-attribute correlations by FFDs(e.g., Phone?Zipcode) can bring potential vulnerability. Unfortunately, none of the existinganonymization principles (e.g., k-anonymity, l-diversity, etc.) can effectively prevent againstan FFD-based privacy attack. We formalize the FFD-based privacy attack and define the privacymodel, d;l-inference, to combat the FD-based attack. We distinguish the safe FFDs that willnot jeopardize privacy from the unsafe ones. We design robust algorithms that can efficientlyanonymize the microdata with low information loss when the unsafe FFDs are present. Theefficiency and effectiveness of our approach are demonstrated by the empirical study.

In the 2006 American Community Survey (ACS), 6% of respondents with Latin American ancestry answered no when asked whether they were Hispanic themselves. Conventional definitions of the Hispanic population exclude such respondents as not Spanish/Hispanic/Latino even though they are self-identified Latin American descendants.Since their exclusion may bias our assessments of Hispanic social mobility, it is important to know more about them. Non-Hispanic identification is most common among Latin American descendants who (1) list both Latin American and non-Latin American ancestries, (2) speak only English, and (3) identify as White, Black, or Asian when asked about their race. Ancestry and racial identity are considerably more influential than respondents education, income, place of birth, or place of residence. These findings support both traditional straight-line assimilation and a more recent racialized assimilation theory in explaining discrepant responses to the ethnicity and ancestry questions among Latin American descendants.

The "marriage boom" was a major determinant of the "baby boom" in the United States. One of the best-known explanations for these phenomena is Easterlin's relative cohort model. Using an age-period-cohort model of marriage this paper will try to show that the marriage boom is not a cohort effect but mostly a period effect. Previous explanations have ignored the fact that the marriage boom started immediately after the National Housing Act of 1934 established the Federal Housing Administration to oversee a program of home mortgage insurance against default. This paper shows that a period factor, the Federal Housing Administration and Veteran Affairs shares of total mortgage originations, explains most of the marriage boom.

This chapter analyses the determinants of immigrants' citizenship take-up in Canada and the United States. It also reviews the recent literature on the economic benefits of naturalisation among immigrants to Canada and the United States and provides some evidence on the association between citizenship and labour market outcomes in these two countries.

In the years after World War II, the University of Chicago (U of C) enjoyed a position as a leader in higher education with the ability to help provide for national economic growth and global security through professional education and scientific research. It also faced a dramatically changing set of neighborhood conditions that threatened its leadership status. University administrators pursued an ambitious agenda of redevelopment and neighborhood management in South East Chicago in order to fight a wave of racial transition. In doing so, the university formed and led a coalition of top urban universities that shared real estate practices and helped create federal policy that made universities integral parts of urban renewal initiatives in the 1960s. This effort to create, manage, and redevelop housing, including student housing, provoked strident opposition from the student body and set the emerging New Left against the university in an early salvo of the student movement.

Objectives. We seek to examine what common characteristics Latino voters share distinctively from nonvoting Latinos and how they differ from those of non-Latino voters. Methods. We use the method of classification tree to find what variables best describe the shared characteristics of Latino and non-Latino voters. Results. The results indicate that age, the strength of partisanship, and the level of education characterize both Latino and non-Latino voters. However, there is a sharp difference in how age interacts with other the two variables. In the Latino sample, the overwhelming majority of younger people do not turn out to vote, and it is among older Latinos that education and partisanship play an important role in distinguishing voters and nonvoters. By contrast, among non-Latinos, it is younger people whose participation is sensitive to the level of education or strength of partisanship, while the older are overwhelmingly voters regardless of other factors. Conclusions. At the individual level, Latinos in the United States still face substantial barriers in political incorporation: in contrast to non-Latinos, they do not seem to develop the habit of voting even after they have aged enough, unless they are helped by higher levels ofeducation or stronger partisanship. At the aggregate level, the pool of Latino likely voters is relatively small, which in turn emphasizes the potential significance of the GOTV campaigns in increasing participation rates among Latinos.

In a database the data concepts changes over time and this phenomenon is called as concept drift. Rules of concept drift describe how the concept changes and sometimes they are interesting and mining those rules becomes more important. CDR tree algorithm is currently used to identify the rules of concept drift. Building a CDR tree becomes a complex process when the domain values of the attributes get increased. Genetic Algo- rithms are traditionally used for data mining tasks. In this paper, a Genetic Algorithm based approach is proposed for mining the rules of concept drift, which makes the mining task simpler and accurate when compared with the CDR-tree algorithm.

This Migration Information Source Spotlight focuses on Caribbean immigrants residing in the United States and examines the population's size, geographic distribution, and demographic and socioeconomic characteristics. The data used are the most recent detailed data available and come from the US Census Bureau's 2009 American Community Survey (ACS), the 2000 Decennial Census (as well as earlier censuses), and the Department of Homeland Security's Office of Immigration Statistics