The wealth gap between African-American and White households has persisted for decades, prompting policymakers and experts to suggest several large-scale interventions. We evaluate the possible impact of five such proposals on the Black-White wealth gap. These interventions include debt-free college, baby bonds, civil rights enforcement in housing markets, credit market regulations enforcement, and a national retirement savings plan. Using simulations anchored in data and the existing literature, we conclude that baby bonds would have the single largest effect. But a large wealth gap would remain, even if all five proposals were promptly enacted. Only targeted cash or liquid asset transfers to African-Americans can overcome the persistent wealth difference with White households.

The aging of larger numbers of Americans will require significant increases in the number of healthcare support workers. During the past years, foreign-born workers are playing a significant role in the direct care workforce in particular. Yet it is not always clear how foreign-born workers fill-in the current gaps. Using ACS (American Community Survey) and LTCFocus (Long-term Care: Facts on Care in the US) data from 2012 to 2016 and measuring quality by facility structures and residents’ health outcomes, this paper explores how shares of foreign-born workers in nursing-related occupations may contribute to the quality of nursing homes by applying a longitudinal model with a fixed effect for each nursing home. The result depends on different measures of quality and types of occupations, such as low-skilled occupations like Home Aides assistants and support workers and more professional occupations like registered nurses. I show that when using outcome measures of nursing home quality, such as long-stay residents with daily pain to measure quality, the estimators are generally insignificant, but in terms of Shares of Home Aides Supports occupations, they lead to an increase in quality. However, when using structural measures of nursing home quality, such as different staff ratios, some of the estimators are significant and although in a small attitude, leading to an increase in the quality. Overall, the effect of shares of foreign-born workers in Nursing-related occupations on nursing home quality remains a mixed picture. The result shows that increasing the shares of foreign-born workers itself may not lead to a better quality of nursing home, more effort shall be done to understand the mechanism behind this. Further studies shall focus on establishing better data and measurement.

Nonprofit organizations are important actors in local communities, providing services to vulnerable populations and acting as stewards for charitable contributions from other members of the population. An important question is whether nonprofits spend or receive additional revenues in response to changes in the populations they serve. Because immigrant populations both receive and contribute to nonprofit resources, changes in immigrant numbers should be reflected in changing financial behavior of local nonprofits. Using data from the National Center for Charitable Statistics and the American Community Survey, we study whether nonprofit financial transactions change in response to changes in the local immigration population, the nature of the change, and the degree to which these changes vary by nonprofit type. Findings suggest that nonprofit financial behavior changes with growth and decline in immigrant populations underscoring the importance of nonprofits as service providers and contribute to an understanding of how organizations respond to external forces.

St. Louis, Missouri, is a case study in America's long legacy of racism and a prominent example of a “shrinking city.” This paper expands the notions of “core” and “periphery” using the highly segregated city and its suburbs to include not just economic exploitation but also racial exploitation. Using historical and contemporary census data and spatial data delineating the boundaries of Home Owner Loan Corporation grades (i.e., “redlining” maps), this paper examines the relationship between historical racism, contemporary segregation, and economic consequences. I find that St. Louis's peripheral areas expanded over the twentieth century, first in the city and then in the county, creating dual zones of exploitation where poverty, segregation, and income inequality remain persistently higher. These findings identify the historical roots of contemporary segregation, and suggest that addressing the long term consequences of both racial and economic exploitation in peripheral spaces remains critical for improving African American families' life chances.

Background: Research has established a strong and positive correlation between substance use and intimate partner violence due to a complex interplay of individual, situational, and contextual factors. This study seeks to further explore this relationship in the context of the recent opioid crisis in which millions of Americans have been diagnosed with an opioid use disorder. Specifically, we analyze how opioid prescriptions relate to intimate partner violence within and between counties over time throughout the rise of the opioid crisis. Methods: This study employs an integrated dataset that merges crime data from the Federal Bureau of Investigation, demographic data from the American Community Survey, and prescription opioid pill counts from the Drug Enforcement Administration to study the relationship between opioid pills prescribed per person and levels of intimate partner violence arrests from 2006-2012. Fixed-effects and mixed-effects techniques are both used. Results: Increases in opioid pill distribution volume within-counties over time are related to increases in intimate partner violence arrest volume (p ≤ .001). Additionally, counties which have higher amounts of opioid pills in circulation tend to experience higher levels of arrests for intimate partner violence than counties with fewer pills (p ≤ .001). Conclusions: Policymakers who are dealing with the effects of the opioid crisis should consider the relationship between opioids and intimate partner violence when attempting to address either of these issues. Based on the results of this study, addressing opioid dependence and mitigating the extent of the crisis may also reduce intimate partner violence.

Internet service is considered by many to be essential, yet many households do not have a home Internet connection. Survey evidence suggests a lack of interest is the primary explanation, but some policymakers and advocates prefer to label price as the dominant factor, thereby laying the groundwork for policy interventions, regulation, and subsidies. Most surveys on the reasons for non-adoption are, however, inherently ambiguous and do not permit useful inferences because the typical questions asked cannot distinguish between “relevance” or “price” as the cause of non-adoption. Exploiting data from latest Census Bureau survey, I show that responses appearing to speak to relevance or price always speak to relevance and price. I then propose a simple modification to the Census Bureau survey that permits the construction of the non-users demand curve for Internet service including its curvature, thereby offering important information to policymakers in addressing the role of price in increasing Internet adoption.

Having access to the right talent is critical to maintaining a competitive edge in artificial intelligence. In the United States, policymakers are actively discussing legislative proposals to grow and cultivate a globally competitive domestic AI workforce. However, little data is available on the U.S. AI workforce and associated talent pipelines outside of the PhD segment. Yet having access to good workforce data is critical to actually “winning” the competition for AI talent. This brief provides two contributions to better understand the U.S. AI workforce: (1) a definition of the AI workforce based on the government occupational classification system, identifying 54 occupations that either participate or could participate in AI product and application development, and (2) a preliminary assessment and characterization of the supply of AI talent, which consisted of 14 million workers in 2018 (about 9% of total U.S. employment). Our definition of the AI workforce enables supply-side analysis that is more comprehensive than other commonly used sources, because it is linked to the federal occupation classification system. While many supply-side analyses of the AI workforce rely on sources such as LinkedIn, we use data from the U.S. Census Bureau. Our definition also enables greater analytic consistency across federal government and other datasets that link to this classification system, such as Burning Glass.

Using US Census data from 1960 to 2000 and American Community Survey data from 2010, this paper analyzes gender differences in the return to education for married couples. Results from this analysis show that the return to schooling has increased over time for both genders; however, the relative return to schooling for females has fallen since the 1990s. In 2010, married women who are under age 35 and are in the top 20 percent of the income distribution had lower returns to schooling compared to men. These results are consistent with several demographic shifts that occurred during the last half of the 20th century.

Suitability modeling is a useful approach for exploring human interactions with their environments (Mitchell 2012; Malczewski 2004). Within a geographic information system (GIS) environment, locations are weighted relative to applied criteria, resulting in a landscape hierarchy that displays regions coded from least to most suitable. Suitability modeling is used in various disciplines, from urban planning to natural resources, but a gap exists in research concerning social human behavior. This method can especially contribute to the investigation of social inequality at archaeological sites by quantitatively assessing multiple attributes at an intra-site level. Examining intrasite spatial association and material distributions can inform on human behavior, including social organization (Earle et al 1984; Carr 1984). In this thesis, I discuss the use of this method for determining social inequality at the historic townsite of Terrace along the Transcontinental Railroad in Utah, focusing on iv historic and archaeological evidence gathered in past research. My analysis shows that Chinese railroad workers lived amongst the least suitable regions of the site while Euroamerican railroad workers lived amongst the more suitable regions. By investigating social inequality at Terrace, I address various overarching questions: First, how does archaeological material within the site indicate segregation between the Chinese and Euroamerican cultural groups, and what is the nature of this segregation (voluntary vs. forced)? Second, how can spatial patterning of residential segregation at Terrace inform on nineteenth century urban planning and ethnic interactions within a larger context of American West expansionism along the Transcontinental Railroad. Due to ongoing research on the Chinese occupation along the Transcontinental Railroad during the late nineteenth century, there is a multitude of historical and archaeological evidence supporting the presence of segregation and social inequality between the Euroamerican and other cultural groups, including Chinese immigrants (Voss 2018; Merritt et al 2012). By developing a spatial analytic method for documenting social inequality at Terrace, I hope that archaeologists can apply this technique in similar settings. In doing so, archaeologists can expand the suite of methods and theory used for analyzing social inequality and social hierarchies at archaeological sites.

Accessible pathways to postsecondary attainment are critical to achieving economic security for families, especially in light of the effects of the COVID-19 pandemic. For parents without post-high school credentials and with incomes at or near the poverty threshold, strengthening support for them to pursue higher education can improve their ability to secure employment, promote their long-term economic security, and improve their children’s chances of success (Carnevale, Rose, and Cheah 2011; Attewell and Lavin 2007; Vilorio 2016).

The recent growing Hispanic population in the Bronx, New York has made this borough highly diverse. The reasons for the boom of Latinos are attributed to the ease of immigration acts, but the changes in immigration policies do not explain this population's concentration in eight community districts. In this paper, we explore the factors that cluster this growing community in one region of the borough and the possibilities of dwindling population in the future. We particularly examine how networking and urban accessibility impact Hispanic’s decision-making on internal migration into the Bronx, New York.

Social and professional networks affect individuals’ labor market outcomes, including career path choice, the propensity to find a job, and job match quality (Ioannides and Datcher Loury, 2004; Jackson, 2008; Loury, 2006). Prior research has documented that gender differences in professional network structure help explain men’s and women’s disparate career trajectories (Lindenlaub and Prummer, 2014; Zeltzer, 2020). In an effort to expand and equalize the networks available to students in their transition to the labor force, colleges and universities have increasingly adopted online student-alumni networking platforms.1 It is an open question whether equalizing network access for male and female students equalizes network usage.

Employment outcomes of Black men worsened significantly relative to White men during the second half of the 20th century. We explore the role of broad sectoral shifts in labor demand over this period in explaining this trend. We first quantify changes in local employment and population in response to local labor demand shifts for both groups of workers. We then combine our estimates with a stylized model that incorporates frictional local labor markets and imperfect mobility across markets. Our framework enables us to aggregate local responses while accounting for geographic mobility and regional employment composition. We find that sectoral reallocation can explain around half of the total exacerbation in the employment-to-population ratio differential between Black and White men over 1970-2000. Out-migration from harder hit markets, while large, does not mitigate the impact of negative labor demand shifts specifically for Black men. We also find that most of the predicted change in the employment differential is due to differential response rather than differential exposure to shifts across two groups.

Racial differences in effort at work, if they exist, can potentially explain race-based wage/earnings disparities in the labor market. The authors estimate specifications of time spent on non-work activities at work by Black and White males and females with data from the American Time Use Survey. Estimates reveal that trivially small differences occur between non-Hispanic Black and non-Hispanic White males in time spent not working while on the job that disappear entirely when correcting for non-response errors. The findings imply that Black–White male differences in the fraction of the workday spent not working are either not large enough to partially explain the Black–White wage gap, or simply do not exist at all.

We use four data sets to study supercommuting in the San Francisco Bay Area and Central Valley of California. We follow previous research in defining supercommuting as commutes longer than 50 miles or 90 minutes one-way. The San Francisco Bay Area has some of the highest housing costs in the United States, and anecdotal evidence has long suggested that households might move from the Bay Area to Central Valley counties, possibly enduring long commutes if they cannot move their job at the same time. Yet evidence on a link between supercommuting and house prices has been limited by data availability. We use the data first to demonstrate that the supercommute is far from uncommon, with some Central Valley counties having supercommuting rates that approach 10 percent of all county commutes. We use data on household moves, from zip code tabulation area to zip code tabulation area (ZCTA to ZCTA), to examine how supercommuting rates at the ZCTA level are linked to flows of in-migration from the Bay Area into the Central Valley. We find evidence that suggests that ZCTAs with higher inmigration flows from the Bay Area have higher supercommuting rates.

The success of transit systems, traditionally gauged through ridership metrics, must also be assessed via transit accessibility because accessibility to destinations indicates the quality of service that transit provides. Using a structural equation modeling approach, we explain transit accessibility and transit ridership in 2017 for 50 large urbanized areas in the United States as dual outcomes dependent upon population size, urban form, and transit service provision. Also, we examine transit accessibility as a factor that influences transit ridership. We find that transit service provision strongly influences both transit ridership per capita and job accessibility provided by transit. Further, we find that transit accessibility, in turn, offers a moderate boost to transit ridership. Population density results in higher transit accessibility directly by making destinations easier to reach and indirectly by increasing the amount of transit services provided. Other built environment and transit service variables were examined but did not improve the models’ explanatory power. Disaggregating the effects of fixed-guideway (i.e., rail) and non-fixed guideway transit (i.e., buses in mixed traffic), we find that fixed-guideway transit has a more substantial effect on transit accessibility, while non-fixed guideway transit has a larger effect on transit ridership per vehicle mile.

Trust for America’s Health (TFAH), a non-profit, nonpartisan policy research and advocacy organization, leads a national Age-Friendly Public Health Systems (AFPHS) initiative to promote the health and well-being of the nation’s older adults as a public health priority. This paper is the first of a series of briefs that focuses on the intersection between public health, aging, and agefriendly communities.

Race/ethnicity is associated with adverse birth outcomes in the United States. However, mostly mother's race/ethnicity has been considered. We examined the associations of mother's and parents' race/ethnicity with low birth weight, small for gestational age, preterm birth and infant mortality among New York City women between 2012 and 2017. We also examined the independent and joint effects of neighborhood racial/ethnic composition. We found that mother's and parents' race/ethnicity are associated with adverse birth outcomes; these associations are outcome-specific; and neighborhood racial/ethnic composition is not only associated with such outcomes but also modifies the association of mother's and parents' race/ethnicity with these outcomes. Our findings underscore the need to consider the race/ethnicity of women's partners and their neighborhoods calling attention to the role of context where individuals reside, and their daily interactions take place. These findings may have implications beyond New York City as our society becomes more racial/ethnic diverse and interracial/ethnic marriage becomes more common in the United States.

Using the latest available U.S. Census Bureau data, LendingTree recently examined the average ages of homeowners and renters across the U.S.’s 50 largest metropolitan areas. The study was conducted analyzing data from the U.S. Census Bureau’s 2019 American Community Survey one-year estimates, as derived from the Integrated Public Use Microdata Series (IPUMS).