This research explores the economic causes and consequences of language structures. It advances the hypothesis and establishes empirically that variations in pre-industrial geographical characteristics that were conducive to higher return to agricultural investment, larger gender gap in agricultural productivity, and more hierarchical society, are at the root of existing cross-language variations in the presence of the future tense, grammatical gender, and politeness distinctions. Moreover, the research suggests that while language structures have largely reflected the coding of past human experience and in particular the range of ancestral cultural traits in society, they independently affected human behavior and economic outcomes.

Although heritage language (HL) speakers have received scholarly attention in recent years as an interdisciplinary research theme among language educators, linguists, and policy makers, we know very little about their demographic makeup and trends of their demographic change. In this study, I have analyzed regional and chronological changes of HL speakers between 1980 and 2010, using U.S. census data. The results show sharp differences in HL speakers' demographics by language and region

In recent years, Mexican immigrant living in Arizona have faced several challenges arising from the recent economic crisis and the anti-immigrant policies. In this paper, we analyze the familiar adaptation strategies developed for them in order to optimize their economic and non-economic resources and remain in Arizona. Based on 20 interviews to Mexican families whose were living at Phoenix in 2015, we examined three issues: the family labor reorganization by sex, the public invisibility with the aim to avoid deportations, and making the most of the family documented members.

This paper investigates using multiple datasets (e.g., the CPS and NSAL) whether the increasing presence of foreign born blacks and their native-born children are obscuring summary estimates of the progress made by third generation and higher African Americans. Three measures of "black" were created, (1) a third generation and higher blacks, excluding foreign born blacks, (2) a foreign born black community including first and second generation blacks, and (3) a black-alone group, which included foreign born blacks and third generation and higher blacks. Four estimates of progress were analyzed including percent of high school and college completion, labor force participation rates, the percentage of children living with single mothers, and self-reported arrest rates. It was hypothesized that a summary measure that collapses all blacks into one category-the black-alone group-will not accurately assess the well-being of American blacks, the community of foreign born blacks, and third generation and higher blacks. The analyses generated four findings: First, there are significant gender differences between the foreign born community and third generation and higher blacks. Second, the results revealed that there are substantial differences between the black foreign born community and third generation and higher . . .

Using two million census records, we document cultural assimilation during the Age of Mass Migration, a formative period in US history. Immigrants chose less foreign names for children as they spent more time in the US, eventually closing half of the gap with natives. Many immigrants also intermarried and learned English. Name-based assimilation was similar by literacy status, and faster for immigrants who were more culturally distant from natives. Cultural assimilation affected the next generation. Within households, brothers with more foreign names completed fewer years of schooling, faced higher unemployment, earned less and were more likely to marry foreign-born spouses.

A large literature studies the effects of expanding insurance eligibility to young adult dependents, a major provision of the Patient Protection and Affordable Care Act (PPACA). I provide new evidence on the effects of dependent coverage mandates by compiling original legal data on the timing and content of initial state adoption of these laws during the 1980s and 1990s; most existing research leverages much smaller eligibility expansions during the 2000s. Using data from the 1996-2014 Annual Social and Economic Supplement of the Current Population Survey, the 1986-2014 Current Population Surveys, and the 2008-2014 American Community Surveys, I estimate the effects of state dependent mandates and estimate the effects of the PPACA dependent mandate with controls for pre-existing state mandates. I show that the effects of initial state adoptions during the 1990s had much larger and more robust effects on dependent coverage than the eligibility expansions of the 2000s studied in most prior work. I find that the likelihood of having insurance coverage increased by 6 percent under state mandates and by 8.2 percent under the PPACA mandate. The increase is driven by a large increase in private insurance: 7.5 percent under state mandates and 11.8 percent under the PPACA mandate. I find that state mandates had no effect on public insurance coverage but that the ACA mandate decreased the likelihood of public insurance coverage consistent with crowding in. I find hetereogenous effects by sex with males have larger coverage gains. Despite the gains in insurance, I find no effect on self-rated health. Looking at labor market outcomes, I find evidence of increased entrepreneurship, some evidence of a decrease in average weekly hours, mixed evidence of changes in unemployment duration, and no effect on labor force participation. Looking at education, I find an increased likelihood of having a bachelors degree and of taking some college courses. I further investigate how dependent mandates affect parents decisions and find that state dependent mandates have no effect on the heads of households labor supply or overall insurance coverage, though there is evidence that, among parents with employer sponsored insurance, those who have eligible children are more likely to switch to an employer sponsored family plan and this effect is much larger for households with only one parent present. Among employer sponsored insurance policyholders I find no evidence of shifting costs through decreased wages. However, I do find evidence that some employers reduce costs by no longer paying premiums on insurance plans.

Using both cross-sectional and panel data, this article revisits the evolution of the financial premium between 1970 and 2011 with a distributional approach. I report that above-market compensation was present in the finance sector in the 1970s, but concentrated mostly at the bottom of the earnings distribution. The financial premium observed since the 1980s, however, is largely driven by excessive compensation at the top, a development that increasingly contributes to the national concentration of earnings. Furthermore, the analysis suggests that the financial premium for top earners remained robust in the early 2000s, when deregulation slowed down, and in the aftermath of the recent financial meltdown. These findings are inconsistent with the account that the earnings differential is driven by unobserved skill difference and demand shocks but supportive of the institutional account of rising inequality.

U.S. Army doctrine requires that commanders understand, visualize, and describe the infrastructure component of the Joint Operating Environment to accomplish the Armys missions of protecting, restoring, and developing infrastructure. The functionality of modern cities relies heavily on interdependent infrastructure systems such as those for water, power, and transportation. Disruptions often propagate within and across physical infrastructure networks and result in catastrophic consequences. The reaction of communities to disasters may further transfer and aggravate the burden and facilitate cascading secondary disruptions. Hence, a holistic analysis framework that integrates infrastructure interdependencies and community behaviors is needed to evaluate vulnerability to disruptions and to assess the impact of a disaster. The research for Human-Infrastructure System Assessment (HISA) for Military Operations adopts the Capability Approach (CA) to measure and predict the impact of potential infrastructural interdictions on the City of Maiduguri, Borno State, Nigeria. With the CA, 10 capabilities are identified to describe the well-being levels of Maiduguri. To quantify these 10 capabilities, 16 indicators were chosen to represent them. These indicator justifications provide the rationale for choosing the indicators for the corresponding capabilities and predictive modeling. Developing probabilistic predictive models of the indicators (or their indices) allows analysis of social well-being in relationship to cascading infrastructure failure.

A difference-in-difference approach was used to compare the effects of same-sex domestic partnership, civil union, and marriage policies on same- and different-sex partners who could have benefitted from their partners' employer-based insurance (EBI) coverage. Same-sex partners had 78% lower odds (Marginal Effect = -21%) of having EBI compared with different-sex partners, adjusting for socioeconomic and health-related factors. Same-sex partners living in states that recognized same-sex marriage or domestic partnership had 89% greater odds of having EBI compared with those in states that did not recognize same-sex unions (ME = 5%). The impact of same-sex legislation on increasing take-up of dependent EBI coverage among lesbians, gay men, and bisexual individuals was modest, and domestic partnership legislation was equally as effective as same-sex marriage in increasing same-sex partner EBI coverage. Extending dependent EBI coverage to same-sex partners can mitigate gaps in coverage for a segment of the lesbians, gay men, and bisexual population but will not eliminate them.

Race-specific given names have been linked to a range of negative outcomes in contemporary studies, but little is known about their long-term consequences. Building on recent research which documents the existence of a national naming pattern for African American males in the late nineteenth and early twentieth centuries (Cook, Logan and Parman, 2014), we analyze long-term consequences of distinctively racialized names. Using over 3 million death certificates from Alabama, Illinois, Missouri and North Carolina from 1802 to 1970, we find a robust within-race mortality difference for African American men who had distinctively black names. Having an African American name added more than 1 year of life relative to other African American males. The result is robust to controlling for the age pattern of mortality over time and environmental factors which could drive the mortality relationship. The result is not consistently present for infant and child mortality, however. As much as 10% of the historical between-race mortality gap would have been closed if every black man was given a black name. Suggestive evidence implies that cultural factors not captured by socioeconomic or human capital measures may be related to the mortality differential.

Introduction Diabetes mellitus incidence has more than doubled in the U.S. over the past 2 decades. Not all sectors of the population have experienced the increase proportionally. The goal of this study was to determine if disparities in diabetes by education and race/ethnicity have increased over time, and if there are differences by gender and birth cohort. Methods Repeated cross-sectional data were used from the 19732012 National Health Interview Survey of adults aged 2584 years. Logistic regression models were run and predicted probabilities were calculated to determine if disparities in self-reported diabetes by education and race/ethnicity changed over time, by gender and birth cohort (birth before 1946, 19461970, 1971 or after). Analyses were conducted in 20142015. Results Relationships between education or race/ethnicity and diabetes were modified by time for people born before 1971, with stronger effect modification for women than men. Inequalities in diabetes prevalence grew over time, although the magnitude of disparities was smaller for the 19461970 cohort. For example, in 20052012, the gap in diabetes prevalence for women with the highest and lowest levels of education was 12.7% for pre-1946 versus 7.9% for 19461970. Similar trends were seen for differences between non-Hispanic whites and non-Hispanic blacks or Hispanics. Results were inconclusive for the youngest cohort. Conclusions Diabetes disparities are evident. Smaller differences in later cohorts may indicate that large structural changes in society (e.g., Civil Rights movement, increased educational and economic opportunities) have benefited later generations.

Metadata are critical in epidemiological and public health research. However, a lack of biomedical metadata quality frameworks and limited awareness of the implications of poor quality metadata renders data analyses problematic. In this study, we created and evaluated a novel framework to assess metadata quality of epidemiological and public health research datasets. We performed a literature review and surveyed stakeholders to enhance our understanding of biomedical metadata quality assessment. The review identified 11 studies and nine quality dimensions; none of which were specifically aimed at biomedical metadata. 96 individuals completed the survey; of those who submitted data, most only assessed metadata quality sometimes, and eight did not at all. Our framework has four sections: a) general information; b) tools and technologies; c) usability; and d) management and curation. We evaluated the framework using three test cases and sought expert feedback. The framework can assess biomedical metadata quality systematically and robustly.

Public schooling in the U.S. has numerous critics, many of whom suggest that alternatives such as providing vouchers for private schools may be more effective. This paper combines decennial census and American Community Survey data for various years to examine the relationship between cohort-level private schooling rates and later earnings during adulthood. We also explore differences by sex and examine the role played by the quantity of education completed and occupational attainment. We find a significant positive relationship between private schooling rates and adult earnings for women but a small relationship for men.

I use the Current Population Survey March Supplement and a regression discontinuity design to demonstrate a positive impact of premium tax credits, implemented as a part of the 2006 health reform in Massachusetts, on non-group private health insurance coverage.

For forty years, the Tuskegee Study of Untreated Syphilis in the Negro Male passively monitored hundreds of adult black males with syphilis despite the availability of effective treatment. The study’s methods have become synonymous with exploitation and mistreatment by the medical profession. To identify the study’s effects on the behavior and health of older black men, we use an interacted difference-in-difference-in-differences model, comparing older black men to other demographic groups, before and after the Tuskegee revelation, in varying proximity to the study’s victims. We find that the disclosure of the study in 1972 is correlated with increases in medical mistrust and mortality and decreases in both outpatient and inpatient physician interactions for older black men. Our estimates imply life expectancy at age 45 for black men fell by up to 1.5 years in response to the disclosure, accounting for approximately 35% of the 1980 life expectancy gap between black and white men and 25% of the gap between black men and women.

This paper documents how labor costs affect firm capital investment and stock returns. I estimate wage premia across U.S. industries and show that the negative investment-return relation implied by q -theory is steeper for high wage firms than low wage firms. Based on the empirical evidence that wage and labor adjustment costs are positively related, a extended investment-based model predicts the interaction effect, since capital-labor complementarity implies that labor market friction also govern investment decision. The inflexibility induced by wage offers new insights on asset prices and corporate investment.

This paper analyzes differences in multidimensional poverty between immigrants and natives in the U.S using 2014 microdata from the American Community Survey. Drawing from a normative framework based in the Capability Approach and a methodological measurement in the Alkire-Foster method, the paper finds that immigrants disproportionally contribute to overall poverty. Among the six deprivations in the US-MPI, healthcare and education contribute most to both immigrant and native poverty. Consistent with past literature, there is a significant mismatch in identification between income and multidimensional measures. The results also indicate that immigrant poverty varies by citizenship status as well as by sending region. The paper finds that Mexican immigrants - the largest immigrant population - are also the poorest.

The authors used the National Health Interview Survey (NHIS) to estimate how the Affordable Care Act Medicaid expansion affected health insurance enrollment, by source of coverage, among childless adults who became newly eligible for Medicaid in 2014. The NHIS data allowed the authors to report changes in enrollment by source of coverage and to conduct subgroup analyses of Medicaid take-up by gender, age, and other characteristics. Newly eligible childless adults in expansion states were 8.9 percentage points more likely to be insured in 2014 relative to similar adults in nonexpansion states, reflecting gains in Medicaid with little to no offsetting decrease in private coverage. Subgroup patterns of take-up among the newly eligible differed from findings previously reported for the wider low-income population, many of whom were previously eligible. Because these estimates isolate the behavior of newly eligible adults, these findings may be useful for anticipating take-up if nonexpansion states with limited Medicaid eligibility under current law choose to expand in the future. Similarly, because the control group excludes adults who became eligible for subsidized insurance coverage through the Health Insurance Marketplace, these findings provide insight into the effects of Medicaid expansion relative to a counterfactual involving neither Medicaid expansion nor Marketplace subsidies.

Background A common issue in descriptive injury epidemiology is that in order to calculate injury rates that account for the time spent in an activity, both injury cases and exposure time of specific activities need to be collected. In reality, few national surveys have this capacity. To address this issue, we combined statistics from two different national complex surveys as inputs for the numerator and denominator to estimate injury rate, accounting for the time spent in specific activities and included a procedure to estimate variance using the combined surveys. Methods The 2010 National Health Interview Survey (NHIS) was used to quantify injuries, and the 2010 American Time Use Survey (ATUS) was used to quantify time of exposure to specific activities. The injury rate was estimated by dividing the average number of injuries (from NHIS) by average exposure hours (from ATUS), both measured for specific activities. The variance was calculated using the delta method, a general method for variance estimation with complex surveys. Results Among the five types of injuries examined, sport and exercise had the highest rate (12.64 injuries per 100000h), followed by working around house/yard (6.14), driving/riding a motor vehicle (2.98), working (1.45) and sleeping/resting/eating/drinking (0.23). The results show a ranking of injury rate by activity quite different from estimates using population as the denominator. Conclusions Our approach produces an estimate of injury risk which includes activity exposure time and may more reliably reflect the underlying injury risks, offering an alternative method for injury surveillance and research.

Our data are drawn from the Census Bureaus American Community Survey and from other Census and U.S. Bureau of Labor Statistics datasets. We also make use of the extensive research conducted by economistsincluding ourselvesin recent years on minimum wages, and upon research on related economic topics. Our estimates of the effects of a $15 minimum wage are also based upon existing research on labor markets, business operations, and consumer markets. Our estimates compare employment numbers if the policy were to be adopted to employment numbers if the policy is not adopted. Other factors that may affect employment by 2019 are therefore outside the scope of our analysis. We have successfully tested our model with a set of robustness exercises. Our analysis does not incorporate the recent state minimum wage law passed in April 2016. Since the San Jose and Santa Clara County scenarios are on a faster timeline, the number and demographics of workers affected would be similar if we had included the scheduled statewide increases. However, the size of the average wage increase and the effect on firms compared to the new baseline established by the state would be somewhat smaller.