Direct care workers assist older adults and people with disabilities with essential daily tasks and activities across a range of long-term care settings. This report explores the three primary segments of this workforce: Home care workers, residential care aides, and nursing assistants in nursing homes.

This study emphasizes the critical role of air conditioning (AC) in preventing heat-related illnesses such as heat exhaustion and heatstroke. The challenge of limited geographic coverage and outdated AC availability data hampers effective heat risk mapping and prevention efforts. We identified areas with significant AC needs and examined factors related to AC ownership in Florida, U.S. Local Indicators of Spatial Association results displayed distinct AC ownership disparities, with high-high clusters in coastal and metropolitan areas and AC-deficient clusters inland. Vulnerable urban communities, predominantly inhabited by marginalized groups, had limited to no AC availability. The Spatial Durbin Model results revealed a significant correlation between AC ownership and socioeconomic and urban factors. Notably, a higher proportion of AC-deficient households were in predominantly African-American neighborhoods, underscoring racial disparities in AC ownership. These findings provide valuable insights for targeted interventions to mitigate heat-related risks and adapt to evolving climate conditions in vulnerable neighborhoods.

We investigate the contribution of socio-behavioral factors to changes in US adult mortality over the period 1997-2019, using National Health Interview Surveys (NHIS) for years 1997-2018 linked to death records through 2019. The variables studied include alcohol consumption, cigarette smoking, health insurance coverage, educational attainment, mental distress, obesity, and race/ethnicity. We evaluate the contribution of each socio-behavioral variable to mortality change by estimating the mortality risks associated with each variable in a hazards model and applying the risks to changes in the variable’s distribution. We find that reductions in cigarette smoking and increases in educational attainment are the largest contributors to recent mortality improvements, accounting between them for 67% of mortality improvements. In a secondary analysis, we compare two subperiods to investigate whether the variables can account for a widely-observed slowdown in the rate of mortality reduction that occurred within the period of study. Rising levels of psychological distress, combined with very high risks associated with distress, were responsible for 13% of the slowdown. However, most of the slowdown remains unaccounted for.

We analyze the role of selection bias in generating changes in the observed distribution of female hourly wages in the United States using CPS data for the years 1975 to 2020. We account for selection bias from the employment decision by modeling the distribution of the number of working hours and estimating a nonseparable model of wages. We decompose changes in the wage distribution into composition, structural, and selection effects. Composition effects increased wages at all quantiles while the impact of the structural effects varied by time period and quantile. Changes in the role of selection only appeared at the lower quantiles of the wage distribution. The evidence suggests that there was positive selection in the 1970s, which diminished until the later 1990s. This reduced wages at lower quantiles and increased wage inequality. Post 2000 there appears to be an increase in positive sorting, which reduced the selection effects on wage inequality.</p>

The National Women's Law Center fights for gender justice-in the courts, in public policy, and in our society-working across the issues that are central to the lives of women and girls. We use the law in all its forms to change culture and drive solutions to the gender inequity that shapes our society and to break down the barriers that harm all of us-especially women of color, LGBTQI+ people, and women and families with low incomes. For more than 50 years, NWLC has been on the leading edge of every major legal and policy victory for women.

We supplement the 'Idea Production Function' (IPF) with measures of R&D capital. We construct the R&D capital stock in the US, and estimate the IPF with patent applications as R&D output, allowing for a flexible treatment of R&D productivity (over 1968-2019). The estimated substitution elasticity between R&D inputs is 0.7 − 0.8. Hence R&D capital is an essential factor in producing ideas, complementary to R&D labor. There is a positive trend in R&D labor productivity (∼ 1%) and cyclical variation of R&D capital productivity. Instead of 'ideas getting harder to find', there is a scarcity of R&D capital needed to find them.

As a racialized pan-ethnic group, Asian Americans exhibit ethnically heterogeneous structural and cultural characteristics, but such heterogeneity and its implications for Asian Americans’ pan-ethnic groupness were seldom explored empirically. Using the American Community Survey and the 2016 National Asian American Survey datasets, this paper examines intra-Asian symbolic and socioeconomic boundaries and boundary processes captured in Asian interethnic marriage. I find prominent intra-Asian boundaries distinguishing exceptionally disadvantaged refugee-origin Southeast Asians, yet intra-Asian marriages still occur across these boundaries. This mismatch between intra-Asian boundaries and marriage patterns reflects loose and often unstable interpretations of ethnic similarities and differences. Together, my findings reveal Asian Americans’ contextually salient interpretations of ethnic heterogeneity behind intra-Asian boundary processes, which further reinforce the socially constructed notion of Asian Americans as a racialized group.

Extreme weather events, such as flooding, are expected to become more severe due to climate change. These impacts are connected to impacts on human systems including economic, social, and political crises. Adding to the challenge, populations have concurrently settled in risky areas that were previously thought to have low, or no, exposure. As such, it is important to understand how population exposure to flooding may change over time. Here, we build on existing research to project future populations with their demographic components under all five Shared Socioeconomic Pathways (SSPs) at the block group level across the US. These projections are evaluated with future flood projections to characterize exposure changes over time. Broadly, across the five SSPs, the most increase in exposure will occur in SSP5 (+470,719), and the least will occur in SSP 3 (+57,189). Across all five SSPs, we find that there will be significant increases in expected annual exposure for populations 80 years and older, with an increase in exposure by approximately 216% under SSP5. By decomposing the contributions from flood and population growth, we find that the population growth induced effect contributed to an increase in the population exposure for all of the SSPs except for SSP3. In SSP5, this effect was the largest (+72.7% more exposure), while in SSP3, the population effect decreased the overall exposure by 83.5%.

Objectives. To estimate social class inequities in US mortality using a relational measure based on power over productive property and workers’ labor. Methods. We used nationally representative 1986–2018 National Health Interview Survey data with mortality follow-up through December 31, 2019 (n 5 911 850). First, using business-ownership, occupational, and employment-status data, we classified respondents as incorporated business owners (IBOs), unincorporated business owners (UBOs), managers, workers, or not in the labor force (NLFs). Next, using inverse-probability-weighted survival curves, we estimated class mortality inequities overall, after subdividing workers by employment status and occupation, and by period, gender, race/ethnicity, and education. Results. UBOs, workers, and NLFs had, respectively, 6.3 (95% confidence interval [CI] 5 28.1, 24.6), 6.6 (95% CI 5 28.1, 25.0), and 19.4 (95% CI 5 221.0, 217.7) per 100 lower 34-year survival rates than IBOs. Mortality risk was especially high for unemployed, blue-collar, and service workers. Inequities increased over time and were greater among male, racially minoritized, and less-educated respondents. Conclusions. We estimated considerable mortality inequities by class, gender, and race/ethnicity. We also estimated that class mortality inequities are increasing, threatening population health. Public Health Implications. Addressing class inequities likely requires structural, worker-empowering nterventions.

Background: More than one-third of children and adolescents consume foods from quick-service restaurants (QSRs) daily, which is associated with an increased risk of diet-related adverse health conditions. Objective: To examine trends in the proximity of top-selling QSR chains to all public schools across the United States between 2006 and 2018 by community-, school-, and student-level characteristics. Design: This longitudinal study examined changes in the number QSRs between the 2006-2007 and 2017-2018 school years using data from National Center for Education Statistics, Infogroup US Historical Business Data, and the US Department of Agriculture's Economic Research Service. Statistical analysis: A mixed-model analysis of variance using census tract as a random effect and accounting for repeated measures by school was used to examine the proximity of QSRs near schools. Models adjusted for demographic characteristics and census tract population density. Data were analyzed in 2021. Results: During 2006, 9% of schools had QSRs within 400 m, and 25% of schools in the most populated areas had at least one QSR within 400 m. There were more QSRs near schools with a high percentage of poverty (12%), and near schools with high school students with the highest population of Black or African American (16%) and Hispanic or Latino (18%) students. By 2018, the percent of all public schools within 400 m of QSRs increased to 12%. The increase over time was greater near schools with a high percentage of poverty (16%) and near schools with high school students with the highest population of Black or African American students (22%) and Hispanic or Latino (23%) students. Conclusions: This is the first nationwide study to examine trends in QSR proximity to all public schools. QSRs were most likely to be located near schools with high school students, near schools with a high percentage of poverty, and near schools with a higher proportion of racial and ethnic minority students. Over time, there were greater increases in QSRs near these schools which may have important implications for children's health and diet-related disparities.

Large and persistent racial disparities in land-based wealth were an important legacy of slavery and Reconstruction. We combine records from the censuses of agriculture and population to observe farmers’ landholdings (acreage and value) in 1880, revealing large racial disparities. To assess how these disparities were transmitted intergenerationally, we link sons from both farmer-headed and other households to the 1900 census records. We find that Black landowners transmitted substantial advantages to their sons, particularly in literacy and homeownership, even in estimates based on within-locality variation. But overall, such advantages were small relative to the racial gaps in economic status.

Machine learning and AI technologies can identify data patterns related to financial misreporting that traditional methods cannot detect. With rising machine readership of corporate financial statements, managers may have less incentive to engage in financial misreporting. This study empirically investigates this possibility and finds a reduction in financial misreporting when machine readership is higher. These results hold after addressing potential identification issues. The impact of machine readership is more pronounced in cases where machine learning offers greater advantages, such as complex financial statements and the availability of alternative data. Notably, for misreporting patterns detectable by traditional linear models, machine readership offers no incremental disciplining, indicating that the strength of machines, instead, lies in recognizing non-linear and high-dimensional patterns. Furthermore, we observe an overall decrease in misstatements, suggesting that machine readership enhances overall financial reporting quality rather than prompting managers to shift misreporting to areas beyond machine detection. This paper highlights the disciplining effect of machine adoption in the capital market on financial reporting.

Exposure to traffic-related air pollutants (TRAPs) has been associated with numerous adverse health effects. TRAP concentrations are highest meters away from major roads, and disproportionately affect minority (i.e., non-white) populations often considered the most vulnerable to TRAP exposure. To demonstrate an improved assessment of on-road emissions and to quantify exposure inequity in this population, we develop and apply a hybrid data fusion approach that utilizes the combined strength of air quality observations and regional/local scale models to estimate air pollution exposures at census block resolution for the entire U.S. We use the regional photochemical grid model CMAQ (Community Multiscale Air Quality) to predict the spatiotemporal impacts at local/regional scales, and the local scale dispersion model, R-LINE (Research LINE source) to estimate concentrations that capture the sharp TRAP gradients from roads. We further apply the Regionalized Air quality Model Performance (RAMP) Hybrid data fusion technique to consider the model’s nonhomogeneous, nonlinear performance to not only improve exposure estimates, but also achieve significant model performance improvement. With a R 2 of 0.51 for PM 2.5 and 0.81 for NO 2 , the RAMP hybrid method improved R 2 by ~0.2 for both pollutants (an increase of up to ~70% for PM 2.5 and ~31% NO 2 ). Using the RAMP Hybrid method, we estimate 264,516 [95% confidence interval [CI], 223,506–307,577] premature deaths attributable to PM 2.5 from all sources, a ~1% overall decrease in CMAQ-estimated premature mortality compared to RAMP Hybrid, despite increases and decreases in some locations. For NO 2 , RAMP Hybrid estimates 138,550 [69,275–207,826] premature deaths, a ~19% increase (22,576 [11,288 – 33,864]) compared to CMAQ. Finally, using our RAMP hybrid method to estimate exposure inequity across the U.S., we estimate that Minorities within 100 m from major roads are exposed to up to 15% more PM 2.5 and up to 35% more NO 2 than their White counterparts.

The labor market and broader economy remain in flux as the U.S. unevenly rebounds from COVID-19 disruptions to health, education, work, prices, and every aspect of life. One silver lining of these disruptions, for job seekers, has been an exceptionally tight labor market with rising wages and expanding job opportunities. The bottom of the pay scale has risen the most in percentage terms, benefitting jobs that are less likely to require a college education. This may be part of the reason why there are over 1 million fewer students enrolled in U.S. higher education than before the pandemic (National Student Clearinghouse, 2023). In Tennessee, the percent of high school graduates going straight to college fell from 61.7 to 52.8 percent between 2019 and 2021 (THEC and TSAC, 2022), the lowest level in at least ten years, before climbing to 54.3 percent in 2022 (THEC and TSAC, 2023). Additionally, worker and skill shortages have led many employers to develop in-house training and credential pathways, leading some to question the value of college in the post-pandemic economy (Fain, 2020; Hufford, 2022; Nietzel, 2022; Wingard, 2022). Is college still “worth it” in this environment? Workers with postsecondary credentials tend to earn significantly more than workers without college. On average, the gap is large enough to make up for the time and expense that a student invests in college. Carnevale et al. (2021) analyze nationwide earnings by education and estimate that a U.S. worker with a bachelor’s degree earns $1.4 million more over their career than someone with a high school diploma, and that an associate’s degree corresponds with $452,000 more in lifetime earnings than a high school diploma.1 Abel and Deitz (2014, 2019) estimate that the internal rate of return to college is 13-14% for an associate’s degree and 14-16% for a bachelor’s degree, both of which compare very favorably to the historic 7% inflation-adjusted return on stocks. Carruthers et al. (2023) replicated these analyses for the post-pandemic U.S. They find a consistent 14-15% return on time and tuition costs of attaining a bachelor’s degree before, during, and after the pandemic. They also estimate that returns to associate’s degrees fell from 15.0% to 9.5% between 2016 and 2022, driven in part by rising relative pay for workers without college, and that returns on attaining some college credit but no degree have fluctuated around 7%. This is consistent with research using pre-pandemic data, which generally finds that college is less likely to pay off for students who do not finish (Webber, 2018; Cooper, 2021). In this note, I add to an extensive body of research on the individual return to college with a more focused analysis of the value of going to college for Tennesseans. Findings append to what Carruthers et al. (2023) showed for the post-pandemic U.S. by drilling down to the state level with further analysis for subgroups of Tennesseans with different demographic profiles, who live in different parts of the state, or who have degrees in different fields. Results are broadly in agreement with Carruthers et al. (2023) and pre-pandemic research on the nationwide returns to college. Tennesseans with bachelor’s degrees earn $1.4 million more over their careers than Tennesseans with high school diplomas, or a 14% return relative to the direct and indirect costs of enrolling in college for four years. Associate’s degrees are worth $417,000 more in lifetime earnings, amounting to an 11% return relative to the costs of enrolling for two years. Workers with some college but no degree earn $258,000 more over their career than high school graduates who did not attend college, which represents a 7% return. Estimates are limited to the individual financial benefits of college and exclude any non-financial or societal benefits of higher education. I also find evidence of inequality by gender and race in the college income gap and return to college. A college degree does not increase lifetime incomes as much for women or Black, Hispanic, American Indian, and Multiracial workers in Tennessee as it does for White, non-Hispanic men. Nevertheless, estimated returns to college are large for all gender and race/ethnicity subgroups in Tennessee: 12-19% for associate’s degrees, and 12-16% for bachelor’s degrees. For Tennesseans with bachelor’s degrees, majoring in business, science, or engineering is associated with higher lifetime incomes than education, arts, humanities, communication, or other fields. Women are over-represented in lower-earning fields, particularly education. About 4 out of 5 Tennesseans with bachelor’s degrees in education are women, and the estimated lifetime return on education degrees is only 7%, the same as the return on enrolling in college without completing a degree.

Background: Despite tremendous progress in improving antiretroviral therapy (ART) access, advanced HIV disease (AHD) still remains a challenge globally. Reasons for delayed presentation to care and ART adherence may be affected by gender. We present qualitative study findings on gender differences in decisions for HIV testing and ART initiation/adherence in adults with AHD in Malawi. Methods: We used a qualitative study design, interviewing 16 men and 16 women aged 18 years and above diagnosed with AHD in sites implementing an optimized package of AHD care, from December 2021-February 2022. We included study participants receiving AHD services for at least two months. We also interviewed 16 lay workers and 16 health care workers supporting people living with AHD. In-depths interviews (IDIs) were conducted in English or Chichewa by trained research assistants using semi-structured interview guides. A short-answer analysis was conducted, and findings were interpreted according to thematic areas. Results: Both men and women reported stigma as a main barrier influencing their decision to test for HIV and to initiate and adhere to ART. Fear of side effects, insufficient food, and the need for more information were other barriers reported among men and women as well as perceived as barriers by HCWs. Men appear to have tested later for HIV and stated that they were waiting until experiencing significant symptoms before testing. According to clients and HCWs, men were also less inclined to initiate ART after a HIV diagnosis, whereas women were motivated to start treatment to remain healthy and care for the family. Both genders reported that treatment could be delayed if they were feeling healthy. Treatment fatigue was reported among all groups as the main reason to discontinue treatment. Conclusions: There were similarities and differences between genders in decision-making about HIV care. Concerns about stigma were important reasons for delay in HIV care in both genders. Motivations for accessing HIV treatment and care were different among men and women, pushing the need for gender-tailored counseling services and community messaging that educate both men and women on the benefits of initiating ART early, in turn reducing the number of people presenting with AHD.

Big data, the “new oil” of the modern data science era, has attracted much attention in the GIScience community. However, we have ignored the role of code in enabling the big data revolution in this modern gold rush. Instead, what attention code has received has focused on computational efficiency and scalability issues. In contrast, we have missed the opportunities that the more transformative aspects of code afford as ways to organize our science. These “big code” practices hold the potential for addressing some ill effects of big data that have been rightly criticized, such as algorithmic bias, lack of representation, gatekeeping, and issues of power imbalances in our communities. In this article, I consider areas where lessons from the open source community can help us evolve a more inclusive, generative, and expansive GIScience. These concern best practices for codes of conduct, data pipelines and reproducibility, refactoring our attribution and reward systems, and a reinvention of our pedagogy.

Purpose: This article aimed to investigate 1) whether electronic cigarette (EC) users are more likely to experience asthma attacks or emergency room (ER) visits due to asthma than non-users and 2) how age and smoking behaviors moderate the effect size of the association. Materials and Methods: We used National Health Interview Survey data from 2016–2019. Multiple logistic regression analysis was performed to identify the association between current EC use and having an asthma attack and ER visitation due to asthma. Interaction terms were included to explore the moderation effects of age and cigarette smoking status. Subgroup analysis was conducted according to age group. Results: Of the 218911 participants, 2.0% of them experienced an asthma attack, and 0.5% visited the ER due to asthma. Current EC use was associated with higher odds of having an asthma attack. In interaction analysis, age and smoking status were identified as a moderator in the relationship between EC use and asthma attacks. Participants in their 20s or 30s showed the highest interaction effect. Conclusion: Our analysis indicates the potential impact of EC use on public health and the moderating effects of smoking behavior.

We study whether the work capacity of the older working population responds to improved pain management therapy access. We use the adoption of state recreational marijuana laws (RMLs) as a large policy shock to access to a non-pharmaceutical pain management option. We focus on workers' compensation cash benefit receipt as a measure of work capacity, finding that receipt declines in response to RML adoption. Workers' compensation cash benefits are awarded to workers who require time away from work to recover from an injury, which arguably captures a policy-relevant aspect of work capacity. We observe similar shifts in complementary proxies for work capacity, including work-limiting disability rates. After considering a range of alternative mechanisms, the evidence suggests that the primary driver of the reductions in workers' compensation benefits is improvements in work capacity.

In this paper, I investigate the joint impacts of top-down targets and social opprobrium on aggregate compliance with government mandates for resource conservation. I use data on urban water usage, local agency enforcement, and reports of water waste by private citizens in California during a period of severe drought in which a year-long mandate for water conservation was imposed. During the mandate, private citizens engaged in opprobrium by “drought shaming” customers engaged in “water waste.” I find that increases in complaints regarding water waste led to increases in follow-up actions by local agencies, increased levels of cumulative water conservation, and increased compliance with state-mandated targets. The findings suggest that private citizen involvement in the form of social opprobrium is an important aspect of local agency compliance.

In Chapter 1 of this dissertation, I study the effect of student debt on the post-schooling migration decisions of high-skill workers in the United States. Over the past 40 years, the U.S. has experienced significant skill-based geographic sorting, with high-skill workers increasingly concentrating in large cities. During the same period, the growth of student debt has far exceeded the rate of inflation. In this chapter, I document a link between these two facts. I first estimate the causal effect of student debt on post-schooling location choices by exploiting an expansion of federal student loan limits. Using a difference-in-differences framework, I find that $10,000 of additional debt increases the probability that individuals locate in large metropolitan counties by 6.5 percentage points. By incorporating student debt into a standard spatial equilibrium model, I find that the rise in student debt from 1980 to 2019 can account for 5-19 percent of the increase in skill-based sorting over this period. Counterfactual simulation of three policy proposals – debt forgiveness, tuition-free college, and income-driven repayment – show that only income-driven repayment can eliminate distortions to location choices while improving welfare.The remaining chapters focus on public-sector employee pension systems in the United States and the over $3 trillion in debt associated with them. In Chapter 2, I consider the political economy problem of setting pension benefit levels, where politicians balance the demands of general voters and public-sector unions. More specifically, I empirically show that expanded collective bargaining rights for public-sector employees significantly increased pension plan generosity in the 20th century, and is associated with higher levels of unfunded liabilities in the 21st century. I also provide descriptive evidence that increased plan generosity resulted in higher levels of unfunded liabilities because local governments shirked their expected contributions to pension funds and made overly optimistic assumptions on investment returns, both of which were made possible by systematic information asymmetries around public pension plans.In Chapter 3, I examine the implications of public-sector pension debt for the local economy. I exploit plausibly exogenous shocks to the reported levels of unfunded pension liabilities in a difference-in-differences framework to investigate the speed and extent to which debt shocks are capitalized into house prices. I find that increases in public debt depress local house prices relatively quickly (within 9 months). Additionally, this effect is driven by responses in the price of single-family homes, owners of which may be more likely to rely on public goods that are subject to cuts following spikes in reported pension under-funding.