Background: The rise of contingent work arrangements in the U.S. has generated unease about the American workforce. A recent study estimated that healthcare now accounts for more than one in five contingent workers. Unfortunately, little is known about the extent contingent work arrangements may be occurring in fast-growing, low-wage supportive health occupations in long-term care such as, home health aides and home care aides. As the U.S. population ages and the healthcare sector becomes the largest employment, it is important to understand how these employment arrangements may jeopardize or support the health workforce Objective: This descriptive study focuses on identifying occupations in long-term care with the highest proportion of contingent workers. We compare home health aides and home care aides in contingent and traditional work arrangements to determine predictors of being in a contingent work arrangement. Methods: We used data from the Current Population Survey (CPS) March 2016 Annual Social and Economic Supplement (ASEC). Two occupational categories (nursing, psychiatric, and home health aides and personal and home care aides) were restricted by work setting (home health care services) to identify home health aides and home care aides. We identified workers in contingent work arrangements as those who identified as self-employed. Other responses were coded as workers in traditional employment. Descriptive and regression analyses were conducted to compare workers in different employment arrangements within the same occupation. Population weights provided by the U.S. Census Bureau and Bureau of Labor Statistics were used to extrapolate the findings. Results: Of the estimated 564,528 home health aides, 11.18% were in contingent work arrangements. Similarly, 11.22% of the estimated 385,973 home care aides are in contingent work arrangements 11.22% were contingent workers. Home health aides were 15.4% (p < 0.05) less likely to be in a contingent work arrangement if they had a child in the household and 20.9% (p < 0.01) and 15.6% (p < 0.05) less likely to be in a contingent work arrangement if they were between the ages of 35 and 44 or between the ages of 55 and 64. In contrast, home care aides were 28.5% (p < 0.01) more likely to be in a contingent work arrangement if they were between the ages of 55 and 64. Conclusion: This study identified home health aides and home care aides as occupations in longterm care settings with the highest proportion of contingent workers. Our results contribute to a growing body of evidence describing contingent workers in specific industries and occupations and what characteristics influence entry into alternative work arrangements. Our focus on two of the fastest growing occupations in the U.S. labor force show that contingent work arrangements affect workers who are already vulnerable to low wages and limited benefits. Our findings warrant future research on these types of arrangements among long-term care occupations.

The Integrated Urban Metabolism Analysis Tool (IUMAT) is a system-based computational platform for quantifying the environmental impacts of urban development scenarios. IUMAT's EWM module is a bottom-up approach to generate energy, water, and material resources demand profiles based on building and neighborhood characteristics. This paper presents the EWM approach using national and regional datasets to identify the relationships between environmental impacts and resource use determinants within a simulation platform for urban metabolism analysis. We focus on residential energy consumption, which serves as a template for how the EWM module will be used to simulate commercial and industrial demand profiles. Quantile regression methods are applied to Residential Energy Consumption Survey (RECS) 2009 data to describe the impacts of physical and socio-economic parameters on end use residential energy profiles and create a modeling framework for residential energy prediction. Also, a method for quantifying CO2 emissions and water consumption associated with energy production is outlined.

We estimate the location and population served by domestic wells in the contiguous United States in two ways: (1) the “Block Group Method” or BGM, uses data from the 1990 census, and (2) the “Road-Enhanced Method” or REM, refines the locations by using a buffer expansion and shrinkage technique along roadways to define areas where domestic wells exist. The fundamental assumption is that houses (and therefore domestic wells) are located near a named road. The results are presented as two nationally-consistent domestic-well population datasets. While both methods can be considered valid, the REM map is more precise in locating domestic wells; the REM map has a smaller amount of spatial bias (Type 1 and Type 2 errors nearly equal vs biased in Type 1), total error (10.9% vs 23.7%), and distance error (2.0 km vs 2.7 km), when comparing the REM and BGM maps to a calibration map in California. However, the BGM map is more inclusive of all potential locations for domestic wells. Independent domestic well datasets from the USGS, and the States of MN, NV, and TX show that the BGM captures about 5 to 10% more wells than the REM. One key difference between the BGM and the REM is the mapping of low density areas. The REM reduces areas mapped as low density by 57%, concentrating populations into denser regions. Therefore, if one is trying to capture all of the potential areas of domestic-well usage, then the BGM map may be more applicable. If location is more imperative, then the REM map is better at identifying areas of the landscape with the highest probability of finding a domestic well. Depending on the purpose of a study, a combination of both maps can be used.

Violence against women declined with other forms of violence during the 1990s. Nevertheless, the most popular macro-level theory regarding violence against women, which suggests that changes in gender inequality are associated with changes in the level of violence against women, has been studied primarily cross-sectionally and with mixed findings. In fact, the nature of the relationship between gender inequality and violence against women is undecided. One hypothesis, amelioration, suggests that as gender inequality decreases, and the genders become more equal, violence against women will also decrease (the inverse is also true that as gender inequality increases, violence against women will also increase). Another hypothesis, backlash, suggests that as gender inequality decreases, and the genders become more equal, violence against women will increase. Amidst the mixed findings have been notable conclusions that have found that the relationship may be race-specific and/or dependent on the victim-offender relationship. This project uses the intersectionality perspective, as introduced by Black Feminist scholars to take into account these important findings and thoroughly investigate the relationship between gender inequality and violence against women. I use multiple datasets, investigate fatal and non-fatal forms of violence against women, investigate the relationship at the national- and state-level, incorporate race-specific . . .

There has been a well-documented retreat from marriage among less educated individuals in the U.S. and non-marital childbearing has become the norm among young mothers and mothers with low levels of education. One hypothesis is that the declining economic position of men in these populations is at least partially responsible for these trends. That leads to the reverse hypothesis that an increase in potential earnings of less-educated men would correspondingly lead to an increase in marriage and a reduction in non-marital births. To investigate this possibility, we empirically exploit the positive economic shock associated with localized fracking booms throughout the U.S. in recent decades. We confirm that these localized fracking booms led to increased wages for non-college-educated men. A reduced form analysis reveals that in response to local-area fracking production, both marital and non-marital births increase and there is no evidence of an increase in marriage rates. The pattern of results is consistent with positive income effects on births, but no associated increase in marriage. We compare our findings to the family formation response to the Appalachian coal boom experience of the 1970s and 1980s, when it appears that marital births and marriage rates increased, but non-marital births did not. This contrast potentially suggests important interactions between economic forces and social context.

In his first week in office, President Donald Trump issued an executive order directing the Department of Homeland Security to deport most illegal immigrants who come in contact with law enforcement. His order is based on the widespread perception that illegal immigrants are a significant source of crime in the United States. This brief uses American Community Survey data to analyze incarcerated immigrants according to their citizenship and legal status. All immigrants are less likely to be incarcerated than natives relative to their shares of the population. Even illegal immigrants are less likely to be incarcerated than native-born Americans.

Using nationally representative data from the 2010-2014 American Community Survey, this paper provides updated disability rates for working and retirement age Hispanics in the United States. Crude and age standardized rates, disaggregated by gender, national origin group and nativity, are calculated for six measures of disability. The older foreign-born Mexican population is also disaggregated by year and age at arrival. Once age structure is controlled for older foreign-born Mexican males have higher rates of disability than non-Hispanic White males, and older foreign-born Mexican females have higher rates than both US-born Mexicans and non-Hispanic White females - findings that are at odds with immigrant health advantage theories. Further, there is limited impact of either selection on age at migration or era of migration among retirement age foreign-born Mexicans. These updated estimates are critical for researchers and policymakers and shed light on a growing population at risk for an immigrant health disadvantage.

Introduction: We analyzed workers' compensation (WC) data to identify characteristics related to workers' compensation claim outcomes among janitorial service workers in Washington State. Method: We analyzed WC data from the Washington State Department of Labor & Industries (L&I) State Fund (SF) from January 1, 2003 through December 31, 2013, for janitorial service workers employed in the National Occupational Research Agenda (NORA) Services Sector. We constructed multivariable models to identify factors associated with higher medical costs and increased time lost from work. Results: There were 2,390 janitorial service compensable claims available for analysis. There were significant differences in injury type and other factors by gender, age, and language preference. Linguistic minority status was associated with longer time loss and higher median medical costs. Women were estimated to account for 35% of janitorial service workers but made up 55% of the compensable claims in this study. Conclusions: Janitorial service workers comprise a large vulnerable occupational group in the U.S. workforce. Identifying differences by injury type and potential inequitable outcomes by gender and language is important to ensuring equal treatment in the workers' compensation process. Practical applications: There were significant differences in injury and individual characteristics between men and women in this study. Women had twice the estimated rate of injury to men, and were more likely to require Spanish language materials. Improving communication for training and knowledge about the workers' compensation system appear to be high priorities in this population of injured janitorial service workers.

We examine the heterogeneous determinants of knowledge production across 5 manufacturing sectors of the US metropolitan counties. In addition to the traditional knowledge inputs, we capture knowledge spillovers based on an innovative matrix of patent creation-patent citation separating intra-regional from short- and long- distance interregional effects. Furthermore, we identify the singular role of MAR vs. Jacobian externalities. Our results show that an aggregated approach would mask the variation in the marginal effects detected across sectors and highlight the key role of specialization and of university R&D in innovation production. Intersectoral and long- distance interregional spillovers, usually ignored in the literature, display a significant impact too.

New York City’s remarkable population growth over recent decades has heightened concerns about gentrification and displacement. In this paper, SIAP uses census data drawn from the annual American Community Survey (ACS) to identify patterns of geographic mobility common in New York City Public Use Microdata Areas (PUMAs) during the past decade. Major findings include: 1) New York City residents tend to move less frequently than those of other major cities; 2) the city displays two distinct dimensions of geographic mobility—one associated with high population turnover (number of residents moving in and out of a neighborhood) and a second associated with net population change (shifts in the ethnic and educational composition of the area); and 3) the presence of cultural assets in the neighborhood is associated with high turnover, but not with shifts in the ethnic and educational composition of the area. The paper concludes with observations about how these different patterns might affect residents’ experience of rapid neighborhood change.

Background: Due to the reliance on administrative records in firearm injury research, individual studies do not present an integrated picture of firearm injuries. Non-fatal and fatal injuries are frequently studied separately, as are injuries of different intents. Certain risk factors for assault-related firearm injuries, like characteristics of the neighborhoods where they occur, the injured person’s involvement with criminal activity, or their mental health may also indicate an increased risk of self-inflicted, unintentional, or legal intervention firearm injury. However, identifying differences or similarities between intent-specific firearm injury groups requires the inclusion of all intent-specific firearm injuries, fatal and non-fatal, in a single study, using all available data, to present a more integrated picture of firearm injury. Clarifying the specific associations between firearm injury risk factors and assault-related, self-inflicted, unintentional, and legal intervention firearm injuries can inform targeted interventions. Methods: This study clarifies risk markers for intent-specific firearm injury both at the neighborhood level and the individual level. . .

Contemporary societies are in the midst of major demographic changes, such as the aging of populations. According to CEPAL, Latin America and the Caribbean will have an increase of 57 million older people between 2000 and 2025. This is the beginning of the old age of the generations that were born in the first half of the 20th century. One of the consequences of the aging of the population is the change in the residential arrangements of 1he elder1y. Their homes in Colombia diversified during the 20th century. Although the extended family is still common, since the 1970s the country has seen an accelerated increase in the number of elderly people living alone and as a couple exclusively. The research explains the changes observed in the homes of the elderly between 1973 and 2005, in Colombia. The methodology combines statistical, historiographic and qualitative sources. These are the 1973 and 2005 censuses, historiographical and institutional documents, and interviews with public officials and academic researchers. The results are presented from different logistic regression models, the reconstruction of the historical contexts of the generations that were born between 1874 and 1945, and the analysis of the current conditions of public institutions for the elderly population.

While there is an abundance of research examining the relationship between colleges and the students who eventually graduate, there is one topic that is lacking in literature. The relationship between colleges and the students is a very important and even relevant one, but the role of large universities in the towns that they inhabit is a relationship that deserves to be examined more. It would make sense, that such large institutions which attract so many people semester after semester would have an impact on the community as a whole. This paper compares and contrasts multiple college towns to multiple non-college towns to find if the presence of a college has any sort of significant impact on the town it is present in. This paper answers questions such as: Does the existence of a college or university in a town have a significant effect on the local economy? Is there a positive relationship between having a college or university in town and higher earnings. What factors would cause this to be the case? Finding answers for these questions can be very beneficial for many reasons. Understanding the economic benefits of living in a college town can help recent graduates decide where they want to live after finishing school. Town officials who have a lot of influence can make more educated and overall better strategic decisions when deciding how they want to interact with the college or university in their town. This can also help business owners figure out how profitable it would be to open up shop in a college town. The research question at hand is an important one that can aid many different types of people with making strategic decisions.

This paper considers a new class of robust estimators in a linear instrumental variables (IV) model with many instruments. The estimators are generalized method of moments (GMM) estimators, and the class includes the limited maximum likelihood estimator (LIML) as a special case. Each estimator in the class is consistent and asymptotically normal under many instruments asymptotics, and this paper provides consistent variance estimators that are of the sandwich type and can be used to conduct asymptotically correct inference. Furthermore, this paper characterizes an optimal robust estimator among the members of the class. Compared to LIML, the optimal robust estimator is less influenced by outliers and more efficient under thicktailed error distributions. In an empirical example (Angrist and Krueger, 1991), the optimal robust estimator is approximately 80% more efficient than LIML.

Despite the historical highs for age at first marriage, little is known about the causal relationship between marriage delay and wages, and more importantly, the mechanisms driving such relationship. We attempt to fill the void. Building on an identification strategy proposed in Dahl (Demography 47:689718, 2010), we first establish the causal wage effects of marriage delay. We then propose ways to distinguish among competing theories and hypotheses, as well as the channels through which marriage delay affects wages. Specifically, we take advantage of their different implications for causal relationship, across gender and sub-populations. We reach two conclusions. First, we find a positive causal impact of marriage delay on wages, with a larger effect for women. Comparison of IV and OLS estimates suggests that the observed relationship between marriage delay and wages is attributed to both selection in late marriages and true causal effects. Second, we find strong evidence that the positive, causal effects are almost exclusively through increased education for both men and women.

Immigrant children in the US tend to perform worse in reading, mathematics, and science compared to native children. This paper explores how much of such differences in achievement can be accounted for by a lack of English proficiency. To identify the causal effect of English proficiency on cognitive test scores, I use the fact that language proficiency is closely linked to age at arrival, and that migrant children arrive at different ages from different countries of origin. In particular, I instrument English proficiency by comparing children from English-speaking countries to children from non-English-speaking countries who migrated to the US at different ages. Using data from the New Immigrant Survey, I find that speaking English very badly or badly can explain 27–33% of the achievement gap between native and immigrant children in standardized language-related tests. However, I find no significant language effects for applied maths problems or calculations.

We study the effect of state medical marijuana laws (MMLs) on Social Security Disability Insurance (SSDI) and Workers' Compensation (WC) claiming among working age adults. We use data on benet claiming drawn from the 1990 to 2013 Current Population Survey coupled with a differences-in-differences design to study this question. We nd that passage of an MML increases SSDI claiming. Post-MML the propensity to claim SSDI increases by 0.31 percentage points, which translates to 11.3% relative to SSDI claiming propensity in our sample (2.7%). Point estimates for WC are imprecise.

Natural disasters can jeopardize human capital investments, especially in developing countries. Few empirical studies have analyzed interventions that build resilience to negative shocks and protect youth human capital. Using super-typhoons geographic variation combined with age- cohort exposure and the spatial variation of a secondary school infrastructure program in the Philippines, we estimate a triple difference model to analyze whether children who were exposed to typhoons and were fully exposed to the infrastructure program have better long-term human capital outcomes. Using census data, more than ten years after the natural disaster and program, we find that children affected by the super-typhoons and later benefited from the program, accumulated more years of schooling and were more likely to complete high school. We also find that these protective effects of the infrastructure program to the natural disaster are differentiated by gender. For men, these gains in education are associated with a higher likelihood of high-skilled employment and migrating overseas while for women these benefits are associated with a lower likelihood of being married.

Don’t Blame Us traces the reorientation of modern liberalism and the Democratic Party away from their roots in labor union halls of northern cities to white-collar professionals in postindustrial high-tech suburbs, and casts new light on the importance of suburban liberalism in modern American political culture. Focusing on the suburbs along the high-tech corridor of Route 128 around Boston, Lily Geismer challenges conventional scholarly assessments of Massachusetts exceptionalism, the decline of liberalism, and suburban politics in the wake of the rise of the New Right and the Reagan Revolution in the 1970s and 1980s. Although only a small portion of the population, knowledge professionals in Massachusetts and elsewhere have come to wield tremendous political leverage and power. By probing the possibilities and limitations of these suburban liberals, this rich and nuanced account shows that—far from being an exception to national trends—the suburbs of Massachusetts offer a model for understanding national political realignment and suburban politics in the second half of the twentieth century.