Teachers play a vital, and often underappreciated, role in U.S. communities. They are responsible for educating our youth and young adults, and are instrumental in preparing the next generation of U.S. workers. Foreign-born teachers not only educate Americans, but also serve as cultural ambassadors for immigrant students who may not be as familiar with American traditions, customs, and social norms. Unfortunately, recent immigration policy changes and proposals could have a harmful impact on immigrant teachers and on potential immigrant teachers who have not yet arrived in the United States. This is unfortunate given the fact that there are teacher shortages in some regions of the United States and in some disciplines including bilingual education, foreign languages, mathematics, and science. Foreign-born teachers could help to alleviate these shortages. This paper provides a statistical and demographic portrait of immigrant teachers in the United States and highlights differences between native- and foreign-born teachers as well as between postsecondary and non-postsecondary teachers. It also examines changes in immigration policy impacting foreign-born teachers. A summary is provided in the Key Findings below. The data in this report comes from the Integrated Public Use Microdata Sample (IPUMS-USA) file and the U.S. Census. Five years of data are aggregated to increase the sample size and the accuracy of the estimates. Unless otherwise noted, data was limited to individuals who indicated their primary occupation was either a preschool and kindergarten teacher, elementary and middle school teacher, secondary school teacher, special education teacher, or postsecondary teacher.

Objective This study examined how characteristics of households and communities are implicated in the intergenerational transmission of gender inequality and particularly female genital cutting (FGC). Background Human capital perspectives suggest that socioeconomic inequality predicts FGC continuation. This study contributes to discussions of institutional change by examining the association of decisions to forego FGC with household decision making patterns and community gender norms. Method Multilevel logistic regression was deployed to analyze a pooled sample (N = 12,144) of six demographic and health surveys from Burkina Faso, Egypt, Guinea, Kenya, Mali, and Nigeria. A series of models examined how decision making styles, both at the household and community levels (2,524 demographic and health survey cluster aggregations), and community levels of FGC correspond with the risk of having a daughter cut. Results The results show that daughters are less likely to be cut when parents make key household decisions jointly. Autonomous decision making by women at the community level was associated with lower odds of daughters being cut. However, at the community level, the impacts of women's household decision making were attenuated when FGC was more prevalent. Conclusion The findings suggest that women's decision making status is an important factor in FGC abandonment, although that association is less robust when FGC is highly institutionalized. This study provides new insights into how women, families, and communities can disrupt the intergenerational transmission of behaviors associated with institutionalized gender inequality.

We investigate the training choices made by workers entering the Trade Adjustment Assistance (TAA) program. This is important as more workers enter these types of programs due to technological change and globalization. We show that workers that choose a training occupation beyond their skill level (skill overshooting) or previous wage level (wage overshooting) achieve higher earnings and wage replacement rates with the cost being that it lowers their reemployment rates. Specifically, skill overshooting lowers the reemployment rates for these workers by 2.0 to 3.2 percentage points, but they enjoy an increase in their earnings by 2.0-2.2 percent. Wage overshooting leads to a similar decline in the reemployment rate (2.2 percentage points) but shows a much larger increase in their earnings (6.9 to 8.5%). The findings are robust to various subsamples.

Worldwide, land ownership is concentrated in the hands of relatively few people. This paperstudies the impacts of land concentration on the long-run development of new communities inthe frontier United States using the “checkerboard” pattern of railroad land grants as a naturalexperiment that encouraged land accumulation. Based on modern property tax valuations andother data, historical concentration lowered investment by 23%, overall property value by 4.4%,and population by 8%, indicating persistent effects over 150 years. I argue that landlords’ use ofsharecropping agreements raised the costs of investment, a static inefficiency which persisted dueto transaction costs in land markets. I find little evidence for other explanations, including elitecapture of political systems. I use my empirical estimates to evaluate counterfactual policies,applying recent advances in combinatorial optimization to show that an optimal property rightsallocation would have increased my sample’s agricultural land values by $28 billion (4.8%) in2017.

Prior studies of the medium-run outcomes of universities' race-based affirmative action (AA) policies have been challenged by highly-censored data availability. This study analyzes a novel highly-detailed database of University of California (UC) applications in the years before and after its AA policy ended in 1998, linked to national degree attainment, state earnings records, and five universities' complete student transcripts. It presents two findings estimated using difference-in-difference designs. First, I show that ending AA caused substantial and persistent educational and labor market deterioration among URM UC applicants: each of UC's 10,000 annual URM freshman applicants' likelihood of earning a Bachelor's degree declined by 1.3 percentage points, their likelihood of earning any graduate degree declined 1.4 p.p., and their likelihood of earning at least $100,000 in each year between ages 30 and 37 declined by about 1 p.p. per year. These results imply that affirmative action's end decreased the number of age 30-to-34 URM Californians earning over $100,000 by at least 2.5 percent. Second, I show that ending AA did not improve URM students' relative performance or persistence in core physical, biological, or mathematical science courses, within or across impacted universities. These findings suggest that state prohibitions on university affirmative action policies have modestly exacerbated American socioeconomic inequities.

Background Ethiopia is commonly affected by drought and famine, and this has taken quite a toll on citi- zens of the country, particularly the under-five children. Undernutrition among under-five children in Ethiopia is a prominent public health concern, and it lacked attention for decades. However, the government of Ethiopia, together with other stakeholders, committed to over- coming the impact of malnutrition through the transformational plan. Here we show the mag- nitude of undernutrition among under-five children and the factors predicting the achievement of global nutrition targets set for 2025 at the World Health Assembly. Methods Ethiopian Demographic and Health Survey (EDHS) 2016 was used for this study. A total of 9494 child-mother pairs were included in this analysis. The nutritional status indicators (Height-for-age, Weight-for-height and Weight-for-age) of children were mea- sured and categorized based on the World Health Organization child growth standards. A multilevel logistic regression model adjusted for clusters and sampling weights were used to identify factors associated with stunting, underweight, and wasting. The indepen- dent variables were assessed by calculating the odds ratios with 95% confidence interval (CI). Result The prevalence of stunting was 38.3% (95% CI: 36.4% to 40.2%), under-weight 23.3% (95%CI: 21.9% to 24.9%) and wasting 10.1% (95%, CI: 9.1% to 11.2%). Sex of the child (male), children older than 24 months, recent experience of diarrhea, household wealth index (poorest), and administrative regions (Tigray, Amhara and developing regions) had a higher risk of undernutrition. On the other hand, children born from overweight mothers and educated mother (primary, secondary or higher) had a lower risk of undernutrition. Conclusion The burden of undernutrition is still considerably high in Ethiopia. Implimentation of strate- gies and policies that focus on improving the socioeconomic educatiional status of the com- munity need to be sustained. Generally, actions targeted on factors contributing to undernutrition among under-five children demands immediate attention to achieve national and global nutrition target.

This paper links between Beckerian literature that shows that marriage is a normal good with respect to male income and the literature that explores cultural changes as a result of exogenous events. I use the oil crisis of the 1970s as a positive shock on some males. The analyzed outcome is marital status at early twenties for women and at mid and late twenties for men. The probability to be never-married decreases in the American oilproducing areas immediately after the shock. This effect persists after the oil boom is over but longer for men than for women.

The social environment in which lesbian, gay, bisexual, transgender, and queer (LGBTQ) youths live influences health and well-being. We describe the development of the LGBTQ Supportive Environments Inventory (LGBTQ SEI), designed to quantify the LGBTQ-inclusiveness of social environments in the United States and Canada. We quantify aspects of the social environment including: (1) presence/quality of LGBTQ youth-serving organizations; (2) LGBTQ-inclusive community resources; and (3) socioeconomic and political environment. Using geographic information systems (GIS) tools, we aggregated data to buffers around 397 schools in three regions. The LGBTQ SEI can be used to assess the role of the social environment in reducing health disparities for LGBTQ youths.

This paper studies the link between the migration of US university graduates, innovation and productivity. Using migration flows extracted from the SESTAT database and following a simultaneous equation approach, it finds that there is a positive and statistically significant relationship between the migration flows of skilled economic agents and innovation (and productivity). Higher taxation and housing prices act as a decelerating force to migration. The role of science, technology, engineering and mathematics (STEM) graduates, potential investors and entrepreneurial education appear to play a salient role in regional innovation. The results are robust to various implementations, including the use of the instrumental variables approach.

In the United States, enrollment in public evening schools increased throughout the nineteenth century. The expansion of evening schools was far from uniform across space, however, with some cities embracing this form of education much more readily than others. This paper brings together information from the Census, Annual Reports of the U.S. Commissioner of Education, states’ school superintendent’s reports and factory inspection reports, and various secondary sources to examine the diffusion of public evening schools in the U.S. Although proponents of evening schools often cited the welfare of working children as the primary rationale for providing this type of education alternative, the econometric evidence suggests that the political economy of evening school provision hinged more on school boards’ responsiveness to differences in immigration levels and school overcrowding than exogenous differences in the proportion of children working.

Macfarlane and AbouZahr describe how data producers can assure users about the quality and integrity of information. They provide guidance about preventing, detecting, addressing and documenting errors and omissions that may compromise data quality whatever the source. They suggest how users can interrogate a dataset to determine whether quality assurance techniques have been implemented, from the design stage, to the processes of gathering, compiling, cleaning and analysing data, and to the eventual transformation of data into statistics and information for policy and programme use. The authors explore how data can be shared, combined, linked and triangulated to multiply information. Finally, they draw attention to the need to build and maintain trust in statistical information as central to decision-making and a core public good.

This article proposes a new measure of rental affordability to estimate the growing mismatch between changes in rent and income. Quartiles defined in 2000 for each area are updated for inflation and then used to describe rent and income distributions in 2016, comparing the 50 largest metropolitan areas with census and American Community Survey (ACS) data. The features and advantages of this constant quartile mismatch (CQM) indicator are compared with alternative indicators of affordability, including excessive rent burden and low-income housing supply gap. Unlike the other indicators, rent and income changes are separately identified, which explains the curious anomaly that the San Francisco or Washington, D.C., areas have been measured more affordable than the national average. The mismatch indicator in contrast measures growing stress on renters at both the high and low ends of the distribution. Strong upward shifts in rents are unmatched by increases in incomes in the top quartile, whereas losses of rentals in the bottom quartile leave low-income renters with much less opportunity than they had before. The new method thus conveys how the affordability problems in the lower end of the housing market are linked to shifts in the upper quartile and directly to losses in the bottom quartile. This broader characterization of affordability could help build broader based support for solving housing problems.

Inequality in socioeconomic status (SES)—education, income, and occupation—may further exacerbate the health gap between the “haves” and “have nots” by shaping health behaviors such as physical activity. For example, those in higher socioeconomic positions are consistently found to engage in more physical activity according to public health reports that focus on leisure activity. However, previous research investigating the role of SES in shaping engagement in housework, childcare, and paid work suggests different opportunities for physical activity. This discrepancy in how researchers ask questions about physical activity and the pathways people take to healthy activity raises the question: Do socioeconomic differences in physical activity look different when we look at other domains of physical activity beyond leisure? And, does how we measure SES matter? We draw on data from the American Time Use Survey (ATUS) to assess the roles of education, income, and occupation in the amount of time individuals spend in different types of physical activity. Results demonstrate that socioeconomic differences in physical activity change depending on the activity domain and, therefore, when all domains of physical activity are accounted for compared to leisure-only. Further, the measurement of SES matters: key indicators of SES (education, income, and occupation) have varying associations with levels and types of physical activity. Findings from this research have important implications for the assessment of physical activity across SES, ultimately impacting survey research and public health.

Unlike older communication technologies, the internet has broadened the scope for social interaction and enabled people to meet and interact with people outside their existing social network. This feature of the technology is perhaps most salient for its role in helping people search for mates. While the internet may enlarge the pool of prospective partners, access to a larger pool may also delay the transition to partnership as the option for alternatives may induce individuals to search longer. We empirically examine this effect of the internet on both heterosexual and homosexual partnership formation using nationally-representative data from the National Longitudinal Survey of Youth and the Current Population Survey from the US. We find that while the effect of the internet on the transition to partnership is negative at younger ages, the effect of the internet on increasing the propensity to partner becomes positive as individuals become older, for both homosexual and heterosexual partnerships.

The suburbanization of postwar American cities occurred as middle- and upper-class Americans, usually white, left cities for peripheral suburbs. At the same time that people were fleeing the city, jobs were too. In general, the second half of the 20th century saw a trend of economic decentralization at the level of the metropolitan area.1 Meanwhile, those remaining in the city generally did not have the resources to move and/or had limited mobility due to discrimination. As core cities lost more and more of their economic hegemony over metropolitan areas, it began (or rather, continued) to be difficult for the inner-city residents to find employment. This is the crux of the “spatial mismatch hypothesis:” there is a geographic separation between the unemployed and the job openings that they seek. Due to the assumed limited mobility of the unemployed, it is theorized that this spatial mismatch serves to reinforce the high unemployment rates found in core cities.

background The current immigration policy environment in the United States (U.S.) has poignantly affected Latino communities, with evidence of detrimental mental health and psychosocial effects. Few studies have employed conceptual and analytic models that incorporate interpersonal effects when assessing immigrant citizenship status and mental health. This study utilized dyadic analytic methods to simultaneously assess associations of personal and partner citizenship with psychological distress among a nationally representative sample of cohabiting Latinos age 18-65. methods The Integrated Public Use Microdata Series (IPUMS) prepared the dataset linking index adults with cohabiting partners in the 2016-17 National Health Interview Survey (NHIS) sample. Respondents self-reported U.S. citizenship and index adults self-reported psychological distress using the K6 scale. Structural equation modeling using the R package lavaan.survey accounted for clustering by couple and the complex sampling design, and tested independent and conjoint associations of personal and partner citizenship with psychological distress. results The sample included 3,740 Latino adults and their cohabiting partners. Sociodemographic characteristics were comparable between index adults and partners. Nearly a third of respondents were not U.S. citizens. Index citizenship was positively associated with psychological distress (ß=0.44, p=.03), while partner citizenship was not (ß=0.32, p=.12) in a preliminary structural equation model adjusted for sociodemographic characteristics. conclusion National surveillance data provide an important resource for understanding complex health patterns in U.S. populations. Our results highlight how dyadic analyses can test independent and conjoint effects of personal and partner citizenship in Latino populations, and the importance of examining legal status as a social determinant of health.

This study investigates the outcomes out-of-pocket payments (OOPP) produce in terms of income-related disparities in unmet health needs (UHN) due to inability to pay and highlights the commodifying effect of OOPP in European healthcare systems. It merges micro data from the European Union Statistics on Income and Living Conditions survey (EU-SILC) for 2005-2012, with macro data from the World Bank, OECD and WHO. Our results show that, first, across all European countries and years under study income determines whether a person reports an occasion within the last year where she needed medical treatment or examination but did not receive it due to inability to pay. Second, the more a country relies on OOPP as a means of healthcare financing, the higher the proportion of respondents that report UHN. Third, the share of OOPP amplifies the effect of income considerably. While the poorest decile has a 2 percentage points higher predicted probability of suffering from financially determined UHN than the richest decile in a country with relatively low OOPP (11% of total health expenditure), this difference soars up to 10 percentage points in a country with relatively high OOPP (25%).

Is having one native-born parent an advantage for the child of an immigrant? Much of the classical literature on immigrant assimilation would suggest that children with one native-born and one foreign-born parent (generation 2.5) should fare better than those whose parents are both foreign-born (generation 2.0) Generation 2.5 individuals should have greater access to native networks, face less discrimination, and better bicultural awareness. Despite these seeming advan- tages, recent studies suggest the opposite, with generation 2.5 having worse educational outcomes than their generation 2.0 counterparts. In this paper, we utilize propensity score matching to eval- uate differences in educational outcomes between these two groups. We estimate that on average, generation 2.5 have nearly half a year less education than their generation 2.0 counterparts despite having better-educated parents on average. A number of explanations for this are explored, with a higher degree of bilingualism for generation 2.0, foreign-born parents investing more in children's education, and access to highly skilled immigrant networks being the most promising explanations.

Querying databases to search for “best” objects matching users’ preferences is a fundamental problem of intelligent systems and applications. The skyline query is an important tool for solving such a best-matching problem from the concept of multi-criteria optimization. However, it has the size problem as the size of the results of a skyline query grows superlinearly with the number of criteria. Here, we propose to find both the informative and concise set of skyline, a refined skyline set without similar objects. The informativeness requires the reduced set to cover the skyline, i.e., for every skyline point in the original dataset, there exists a close point in the reduced set, which help users to understand the skyline in more detail and make a better decision. The conciseness requires the size of the reduced set that can cover the skyline is as smaller as possible, which help users to make a quick decision. Finding both the informative and concise set of skyline will boost the usability of intelligent systems. More specifically, we propose two new skyline queries to find the informative and concise set of skyline: minimum skyline query, and extended minimum skyline query. The main idea is to return the minimum number of approximation objects, in which there is an object within a predefined distance threshold for each skyline object. The difference of the two query types is that the former one selects approximation objects only from skyline set, while the latter one selects from the whole dataset. We present an exact solution which computes minimum skyline in linear time for a 2d-space. As both minimum skyline and extended minimum skyline problems are NP-hard for dimensionality at least three, we present greedy solutions that obtain a 1+lnR approximation of the optimums. A comprehensive performance evaluation demonstrates that the size of skyline set can be effectively reduced by using the proposed (extended) minimum skyline queries and our proposed algorithms have promising results.

Analyzing racial distribution and its temporal change in American urban areas is an active area of research. Most attention focused on assessing levels of racial segregation at the spatial scale of a metropolitan area. In this paper, we present an analysis of 1990–2010 changes to racial diversity and segregation on a much smaller spatial scale of an urban census tract. To access time-standardized racial information at the tract and at the census block scales we use multiyear compatible high-resolution population grids. Indices of racial diversity and segregation are calculated for over 30,000 tracts pooled from 41 metropolitan areas. Statistical analysis of this dataset reveals that during the 1990–2010 period urban tracts increased their diversity in line with diversity increases of entire metro areas, but unlike metros, they also increased their levels of segregation. We hypothesize that an increased tendency for the residences of people of the same race to spatially aggregate on the tract scale is the result of individuals exercising preferences regarding their neighbors in reaction to the nationwide increase in diversity of the American population. The study also re-derives diversity and segregation indices from the first principles of the information theory, highlights the need to think about the issue of racial diversity/segregation in terms of spatial patterns, and uses one-person-per-dot maps to connect diversity/segregation indices to actual racial patterns.