This report is about understanding the periods of progress and the periods of stagnation in changes in the achievement gap that have occurred over the past several decades. The authors try to understand what might have contributed to the progress as well as probe the reasons that may account for the progress halting, in the hope of finding some clues and possible directions for moving forward in narrowing the achievement gap. The authors focus on three periods of history, but not in chronological order. The first is the decades of the 1970s and 1980s, when NAEP (National Assessment of Educational Progress) reported large reductions in the gaps in reading and mathematics scores. Second, the report focus on the period from about 1990 until 2008, when the gap wobbled around a generally straight trend line, although scores of 9- and 13-year-olds generally rose overall. And third, the report takes a more expansive view, beginning early in the 20th century, in an attempt to understand the impact of a variety of factors on changes in the gap. These factors include information on educational attainment, employment and earnings, child well-being, the family, neighborhoods and the effects of concentrated poverty and deprivation, lack of social capital, and intergenerational mobility. Appendices include: (1) Trends in NAEP White-Black Reading Gaps at Selected Percentiles; and (2) Trends in NAEP White-Black Mathematics Gaps at Selected Percentiles. (Contains 58 footnotes, 16 figures, and 1 table.)

Data seems to be an increasingly important part of everyone’s life, both within librarianship and the social sciences. Most librarians are able to easily find charts and tables, but sometimes more detailed information is needed. Sometimes custom charts and tables need to be built. This is where data sets come in. These collections of raw data allow users to manipulate and massage variables as they see fit. Where a chart or a table is limited by whichever variables the author chose to include and make available, raw data represents all of the data collected for a given project, allowing endusers to select and manipulate whichever components strike their fancy in whatever manner makes sense for their own research. While one could devote a book to all of the interesting data sets freely available online, here is a sample of some of the more interesting ones.

According to the U.S. Bureau of Labor Statistics, the share of foreign-born workers in the labor market increased from 14% to 17% between 1994 to 2008. At the same time, foreign-born union members increased, from 9% to 11%. Immigrants in the United States are an economically disadvantaged group in the labor market. Previous studies suggest that union members and other workers covered by collective agreements receive union wage premiums about 15 percent over nonunion members in the United States. Joining unions could be a good approach for foreign-born workers to receive higher wages. In this connection, the goal of this paper is twofold: one, to estimate the willingness of foreign-born workers to join unions, and two, to determine the union wage premium for foreign-born workers and whether there is a statistical difference in the union relative wage effect for foreign- and native-born workers. The results show that foreign-born workers have a lower probability of joining unions, ceteris paribus. The wage differential between union and nonunion workers for foreign-born workers is only 11.3%, while that for native-born workers is 13.3%. This 2-percent difference of the union impact on wages of native- and foreign-born workers is statistically significant. Among the foreign-born workers, Mexicans have the highest union relative wage effect (22.4%). This study also finds that the union/nonunion wage differentials for both female foreign- and native-born workers are smaller than those for their vi male counterparts. Moreover, the union wage premium is greater for foreign-born workers in the private sector than for those in the public sector. By region, unions have higher wage impact in the West Coast than in the East Coast. In light of the numerous criticisms leveled against estimating the wage differential between union and nonunion workers using the ordinary least squares (OLS) method, this study estimates the union impact on wages of foreign-born and native-born workers using the propensity score matching (PSM) methodologies (nearest neighbor and kernel matching methods) proposed by Rosenbaum and Rubin (1983), and compares the results with those obtained using the OLS approach. The data on the wages and salaries of male workers aged 16 years and above are obtained from the Current Population Survey and span the period 1994-2008. Both the propensity score matching and OLS estimates indicate that the union/nonunion wage differentials for male foreign-born workers lie between 12% (OLS) and 27% (PSM). In addition, our results suggest that there is little difference in the union/nonunion wage differential between native- and foreign-born workers. The estimates of the union impact on wages using the propensity score matching technique are higher than those derived using OLS for both native- and foreign-born workers. Furthermore, among the foreign-born workers, the union relative wage effect is found to be higher for Mexican-born workers (26-42%), while for Asian-born workers it is lower and statistically insignificant based on the OLS. Further decomposition of the data into three different skill groups (high school dropouts, those with a high school degree, and those with a college degree or higher) reveals that, in general, the less skilled (high school dropout) foreign-born workers have the greatest union wage impact. However, the union wage premium is relatively larger for highly skilled workers (with a college degree or higher) among Mexican-born workers. In chapter 3, we study the effect of job training on the US immigrant workers, using the 1996, 2001 and 2004, Survey of Income and Program Participation (SIPP) data. We improve upon prior studies by setting up our training evaluation model, studying the impact of training on both the average and the distributional earning of workers, and comparing the differences in the return to training for immigrant and native workers by applying the vii Quantile regression (QREQ) model, the DiNardo, Fortin and Lemieux (DFL) reweighting methods, and propensity score matching method (PSM). From our distribution study, we find that training has a positive effect on wages for immigrant workers for most parts of income distribution. The DFL reweighting technique shows that after removing all observable characteristics differences between trained and untrained workers, training still increases wage premium for both natives and immigrants throughout the income distribution. Our analysis provides strong evidence for the hypothesis that after corrected for observable characteristics differences between trained and untrained workers, the effect of training is relatively larger for rich natives, much larger for middle income natives and similar for the poor natives and immigrants. Furthermore, the PSM results show that the job training premium for foreign-born workers is between 0.063 and 0.184, whereas for nativeborn workers it is between 0.108 and 0.229. There is 4-percent difference in the job training premium between native and immigrant. All estimates are statistically significant. Our results suggest that OLS estimates underestimate the training premium.

Massive immigration to Hawaii between 1868 and 1924 transformed the ethnic structureand size of its population. Sex ratios of men and women of marriageable age weresometimes larger than 2.0 for Chinese, Japanese, and Caucasian residents. Weinvestigate whether the skewed sex ratios increased the bargaining power of relativelyscarce females, allowing them to negotiate more favorable terms to their marriages and toallocate more family resources to female children. Using three IPUMS data samplesfrom the 1900, 1910, and 1920 Territorial Censuses of Hawaii, we estimate the effects ofchildren and, in particular, the differential effects of sons and daughters on the laborsupply of married men and married womens. We find that married men tend to workmore and married women less when a daughter is added to their family. By contrast, thedecline in labor supply of married women is smaller and the increase in labor supply ofmarried men is larger when a son is added to their family.

This paper analyzes the longevity benefits of education in the form of improved life expectancy, monetized survivorship gains and longevity-adjusted Mincerian returns. Mortality data from the NLMS reveal a negative and statistically significant effect of schooling on eleven-year mortality in the order of -0.005 (OLS and Cox PH models), -0.016 (IV-2SLS) and -0.021 (IV Cox PH model), with region of birth and US compulsory schooling laws in place between 1925 and 1939 serving as instruments for schooling. These marginal effects induce life expectancy improvements at age 25 of 0.15, 0.31 and 0.40 years, respectively. Using a lifetime expected utility maximization model to monetize these gains yields the following longevity-adjusted Mincerian returns to schooling: 7.1% for white males (6.2% income, 0.9% longevity), 7.0% for white females (6.5% income, 0.5% longevity), 5.6% for black males (5.3%income, 0.3% longevity), and 4.9% for black females (4.6% income, 0.3% longevity). Longevity gains accrue well into late-adulthood, crest around age 50 and decrease with schooling in proportion to income gains. Analysis of the long-run trends of income and longevity returns with IPUMS data reveals marked similarities between race and gender groups from 1940 to 1990. Longevity returns are rapidly rising since 1970, but this tendency reverses for black males in 1980. Steadily increasing since 1950, Mincerian returns soar after 1980, especially among blacks. The comparison of longevity and Mincerian return estimates across NLMS and IPUMS datasets provides consistency and robustness to the results in spite of the different mortality and income measures employed.

We study the effects of private school competition on public school students test scores in the wakeof Floridas Corporate Tax Credit Scholarship program, now known as the Florida Tax Credit ScholarshipProgram, which offered scholarships to eligible low-income students to attend private schools. Specifically,we examine whether students in schools that were exposed to a more competitive private school landscapesaw greater improvements in their test scores after the introduction of the scholarship program, thandid students in schools that faced less competition. The degree of competition is characterized byseveral geocoded variables that capture students ease of access to private schools, and the varietyof nearby private school options open to students. We find that greater degrees of competition areassociated with greater improvements in students test scores following the introduction of the program;these findings are robust to the different variables we use to define competition. These findings arenot an artifact of pre-policy trends; the degree of competition from nearby private schools mattersonly after the announcement of the new program, which makes nearby private competitors more affordablefor eligible students. We also test for several moderating factors, and find that schools that we wouldexpect to be most sensitive to competitive pressure see larger improvements in their test scores asa result of increased competition.

This data brief is the second in a series that profiles children of immigrants using up-to-date census data and other sources.1 The first brief highlighted the fast growth of the immigrant population and the increase in children of immigrants, along with important demographic trends. The current publication describes the family circumstances of children of immigrants, including family structure and parental employment.

From almost every angle, immigration generates interest and controversy. Scholars, pundits and policymakers regularly debate immigration and its effects: on culture, on jobs, on schooling. In particular, both academic and popular commentators have focused on whether immigration is associated with increases in unemployment, use of public benefits, or crime. Examinations of these questions have generally revealed that immigration has no effect, or that the effect, if present, is small. Even in the heated debate about immigration and employment, which receives the most popular attention, academics on both sides . . .

We study the importance of family ties on economic behavior. We define our measure of family ties using individual responses from the World Value Survey (WVS) regarding the role of the family and the love and respect that children are expected to have for their parents in 81 countries. We show that with strong family ties home production is higher and families larger, labor force participation of women and youngsters, and geographical mobility lower. To assess causality, we look at the behavior of second generation immigrants. Our results overall indicate a significant influence of the strength of family ties on economic outcomes.

We perform probit-based OaxacaFairlie decompositions of the change in ownership rates for four ethnic groups and three age groups over five censuses, and then construct second order decompositions of the white/non-white differentials. There is substantial heterogeneity in how Hispanic, Asian and Black households of various age cohorts converge to and diverge from their white counterparts with respect to homeownership.

Although there has been a considerable body of work on skylineevaluation in multidimensional data with totally ordered attributedomains, there are only a few methods that consider attributes withpartially ordered domains. Existing work maps each partially ordereddomain to a total order and then adapts algorithms for totallyordereddomains to solve the problem. Nevertheless these methodseither use stronger notions of dominance, which generate false positives,or require expensive dominance checks. In this paper, wepropose two new methods, which do not have these drawbacks.The first method uses an appropriate mapping of a partial order to atotal order, inspired by the lattice theorem and an off-the-shelf skylinealgorithm. The second technique uses an appropriate storageand indexing approach, inspired by column stores, which enablesefficient verification of whether a pair of objects are incompatible.We demonstrate that both our methods are up to an order of magnitudemore efficient than previous work and scale well with differentproblem parameters, such as complexity of partial orders.

We analyze how sexual orientation is related to household savings using 2000 US Census data, and find that gay and lesbian couples own significantly more retirement income than heterosexuals, while cohabiting heterosexuals save more than their married counterparts. In a household savings model, we interpret this homosexual-specific differential as due to the extremely low fertility of same-sex couples, in addition to the precautionary motives driving cohabiting households to save more than married ones. Evidence from homeowners ratio of mortgage payments to house value exhibits the same pattern of savings differentials by sexual orientation and cohabiting status.

This study implements the modern poverty measure for Minnesota using the American Community Survey (ACS) and simulates the potential effects of alternative safety net policies on poverty. The analysis uses the TRIM microsimulation model to correct for survey underreporting and to add information required for this poverty measure, including near-cash benefits, taxes and nondiscretionary expenses. The alternative simulations apply new program rules and behavioral assumptions to recalculate family resources and poverty. The results show the importance of the modern poverty measure for analyzing state policies and also highlight the numerous decisions and imputations required to implement the new measure. Keywords: Poverty Measurement

The Sloan Center on Aging & Work initiated the Talent Pressures and Aging Workforce Industry Report Series to help employers (and others interested in the aging of the workforce) understand the unique and emerging talent pressures within the leading sectors of the U.S. economy: Accommodation and Food Services; Administration and Support, Waste Management and Remediation Services; Construction; Finance and Insurance; Health Care and Social Assistance; Manufacturing; Professional, Scientific and Technical Services; Retail Trade; Transportation and Warehousing; and Wholesale Trade. The reports are designed to offer succinct accounts of five overarching concerns . . .

Using a newly developed geographic information system transportation database, we study the impact of gaining access to rail transportation on changes in population density and the rate of urbanization between 1850 and 1860 in the American Midwest. Differences-in-differences and instrumental variable analysis of a balanced panel of 278 counties reveals only a small positive effect of rail access on population density but a large positive impact on urbanization as measured by the fraction of people living in incorporated areas of 2,500 or more. Our estimates imply that one-half or more of the growth in urbanization in the Midwest in the late antebellum period may be attributable to the spread of the rail network.