Study Objectives: Asian Americans (AAs) report higher rates of insufficient sleep than non-Hispanic Whites (NHWs). It is unclear how sleep outcomes differ among disaggregated Asian subgroups. Methods: The National Health Interview Survey (NHIS) (2006-2018) was used to analyze self-reported sleep duration and quality measures for AA subgroups (Chinese [n=11,056], Asian Indian [n=11,249], Filipino [n = 13,211], and other Asians [n = 21,767]). Outcomes included hours of sleep per day, the number of days reporting trouble falling asleep, staying asleep, waking up rested, and taking sleep medication in the past week. Subsetted multivariate logistic regression was used to assess factors impacting sleep outcomes by ethnicity. Results: 29.2% of NHWs, 26.4% of Chinese, 24.5% of Asian Indians, and 38.4% of Filipinos reported insufficient sleep duration. Filipinos were less likely to report sufficient sleep duration (OR 0.58, [CI95% 0.53-0.63]) and more likely to report trouble falling asleep (1.19, [1.04-1.36]) than NHWs. Chinese and Asian Indians had less trouble staying asleep ((0.66, [0.57-0.76]), (0.50, [0.43-0.58])) and falling asleep ((0.77, [0.67-0.90]), (0.71, [0.61-0.81]) than NHWs, and Asian Indians were more likely to wake feeling well rested (1.71, [1.51-1.92]). All Asian subgroups were less likely to report using sleep medications than NHWs. Foreign-born status had a negative association with sufficient sleep duration in Filipinos, but a positive association in Asian Indians and Chinese. Conclusions: Filipinos report the highest burden of poor sleep outcomes and Asian Indians report significantly better sleep outcomes. These findings highlight the importance of disaggregating Asian ethnic subgroups to address their health needs. Keywords: Asian American; sleep duration; sleep quality; national health interview survey; race/ethnicity; health disparities

Oil supply-side policies—setbacks, excise taxes and carbon taxes—are increasingly considered for decarbonizing the transportation sector. Understanding not only how such policies reduce oil extraction and greenhouse gas (GHG) emissions but also which communities receive the resulting health benefits and labour-market impacts is crucial for designing effective and equitable decarbonization pathways. Here we combine an empirical field-level oil-production model, an air pollution model and an employment model to characterize spatially explicit 2020–2045 decarbonization scenarios from various policies applied to California, a major oil producer with ambitious decarbonization goals. We find setbacks generate the largest avoided mortality benefits from reduced air pollution and the largest lost worker compensation, followed by excise and carbon taxes. Setbacks also yield the highest share of health benefits and the lowest share of lost worker compensation borne by disadvantaged communities. However, currently proposed setbacks may fail to meet California’s GHG targets, requiring either longer setbacks or additional supply-side policies. Understanding how oil supply-side policies affect extraction, emissions and communities is important for the design of decarbonization pathways. Here the authors take a modelling approach to characterizing 2020–2045 decarbonization scenarios from various policies applied to California’s oil extraction.

Climate change poses a persistent and worsening threat to humanity. A key component which will contribute to the transition to sustainable practices is the development and implementation of green technology (GT). Significant research has been conducted investigating the determinants of innovation. One central determinant is immigration and location. While the literature investigating immigration, innovation and location is time-tested and there exists a growing body of studies relevant to the determinants of GT, little has been done to understand the impact of immigration on GT in particular. This paper motivates the construction of a unique cross-sectional dataset using shares of foreign workers and inventors, and patent counts. Negative binomial estimations help to investigate shares of foreign workers as a potential determinant of GT at the U.S. MSA level.

Following the June 24, 2022 Dobbs v. Jackson Supreme Court ruling, which overturned the federal right to abortion established in Roe v. Wade, hundreds of employers publicly announced policies covering out-of-state employee travel for abortions and related care. Leveraging data from Indeed and Glassdoor, we first document that companies with more female and more Democratic-leaning employees and executives were more likely to announce these policies. We then examine the causal impact such announcements had on recruitment, job satisfaction, and pay by introducing a new methodology to recover similar employers who did not make announcements using workers’ revealed preferences in job search. Difference-in-differences estimates reveal that for announcing companies: (i) vacancies received more job seeker interest, particularly in Democratic-leaning states and female-dominated jobs in states with “trigger” laws that outlawed abortion, (ii) satisfaction with management fell amongst existing employees, particularly in male-dominated jobs, and (iii) posted wages increased, especially for companies where employee sentiment declined. These results highlight the complicated trade-off employers face from engaging in sociopolitical dialogue, in particular how signals of company culture can help recruit new workers but alienate current ones.

The evolution of rent sharing is studied. Based upon a panel of the top 300 publicly quoted British companies over thirty-five years and using excess stock market returns to patenting activity as an instrument for economic rents, the paper reports evidence of a significant fall over time in the pass-through from rents to wages. It confirms that wages do respond to firm-level shocks to economic rents, but by significantly less after 2000 than they did during the 1980s and 1990s. The evidence of decline is a robust finding, corroborated with alternative instruments and industry-level analysis for the US and EU.

This paper investigates the relationship between high-skill intensive industries and poverty rates among low-skilled residents in a sample of cities in the United States. We estimate a model of poverty rates among low-skill residents to examine whether cities with higher economic concentrations in high-skill intensive industries tend to have higher poverty rates among their low-skill residents. Our results suggest that there is a statistically significant and positive relationship between the two variables. We interpret our results in the context of previous findings and discuss the policy implications.

Does motherhood diminish women's occupational authority and widen the gender gap among contemporary workers in the U.S.? The current study answers this question using data from the Occupational Information Network and 15 waves of panel data from the National Longitudinal Survey of Youth 1997 (2002–2019). Fixed effects' regressions show that married and unmarried mothers are less likely than their childless peers to have occupational authority. The motherhood penalty is larger for women with two or more children than one child. Men fare differently, as fatherhood is associated with a small increase in married men's likelihood of working in occupations with authority. Fixed effects regressions with individual slopes show that this association for men is not causal. Instead, married men may have additional children in response to an increase in their occupational authority. All told, parenthood widens the gender gap in authority. This study builds on theories of gendered families and gendered organizations to argue that mothers are systematically underrepresented in occupations with high levels of authority. Because people with authority make hiring, promotion, pay, and policy decisions, the underrepresentation of mothers may perpetuate other forms of labor market inequalities.

While oil was first discovered in the Permian Basin in the early 1920s (Vertress, 2019), the most recent production boom began in 2010. Lasting now more than a dozen years, the boom has been driven by changes in production technology that allowed producers to apply unconventional oil and gas (UO&G) technology (horizontal drilling and hydraulic fracturing) with the layered geology of the Permian Basin (Maniloff & Mastromonaco, 2017; Popova, 2020; Popova & Long, 2021). In relative terms, the boom in the Permian, composed of parts of New Mexico (NM) and Texas (TX), represents one of the most cost-effective and productive oil fields in the world. The boom has generated significant in-migration, employment, earnings, and tax revenues. Currently, the oil and gas (O&G) industry constitutes an estimated 8% of U.S. GDP (Pricewaterhouse Coopers, 2021). For TX and NM, the O&G industry contributed 10.8% and 11.1% of each state’s 2022 GDP, respectively, driven significantly by the Permian boom (Bureau of Economic Analysis, 2023). NM is highly reliant on the industry as it contributes approximately 35% of state budget revenue (NMOGA, 2021). Played out over time, the policy context of a boom centers on balancing the benefits of increased earnings, employment, and public revenues against the environmental damages from UO&G development (Maniloff & Mastromonaco, 2017), and whether there is any localized “resource curse” attached to future economic development in the extractive region. As part of that larger context and given that housing markets aggregate and monetize the preferences of buyers and sellers, as well as capitalize present values, changes in housing prices due to UO&G development are important reflections of the community perceptions of these tradeoffs in benefits and damages (Krupnick & Egarthe, 2017). The objective of this analysis is to examine whether and to what degree some of the effects of the boom, such as well drilling and associated environmental effects, are being capitalized into the regional housing market. To econometrically isolate such effects on housing values, while controlling for other factors, the hedonic pricing method (HPM) is employed. A sample of more than 6,000 individual residential properties are collected for a nine-month period in 2022-2023, drawn from both the 55 counties of the Permian, and a set of 18 control counties in eastern NM and western TX. Since both are sales price non-disclosure states, houses listed for sale on Zillow are webscraped to obtain estimated price and structural housing characteristics (e.g., bedrooms, bathrooms). Each residential property is geolocated and paired with location attributes (e.g., population density, public water availability, unemployment rates) from the Census Bureau and other governmental data sources. Spatial data is collected on environmental effects (air quality, and earthquakes) connected to the boom in unconventional (UO&G) development. This includes unique modeling results (Goodkind et al., 2023), to isolate both fine particulate matter (PM2.5) concentrations, as well as the increment attributable to O&G production. Spatially detailed data on more than 220,000 (active) wells is obtained from both NM and TX and used to generate well count density measures for various buffers around each house. Lastly, the analysis is unique in treating the region wholistically (both NM and TX) with a carefully selected set of control counties.

The Economic Policy Institute (EPI) submits this comment on the Center for Medicare & Medicaid Services (CMS) proposed rule on minimum staffing standards for long-term care facilities. EPI is a nonprofit, nonpartisan think tank created in 1986 to include the needs of low- and middle-income workers in economic policy discussions. EPI conducts research and analysis on the economic status of working America, proposes public policies that protect and improve the economic conditions of low- and middle-income workers, and assesses policies with respect to how well they further those goals. In general, the proposed standard would take an important step to improve care and wellbeing for nursing home residents, but there is room for improvement in the rule. Below we submit an analysis documenting the effects of the staffing standard as proposed on the nursing home workforce, and provide additional support for the finding that increased staffing, including by Licensed Practical Nurses, has benefits that far outweigh the costs of such a proposal and is associated with better health and safety outcomes.

The cyclical volatility of hours per worker is lower among college graduates than those without a college degree. I show empirically that accounting for pay type reduces this volatility gap by 44%. Non-college graduates are more than twice as likely to be paid by the hour, and hourly workers have more cyclically volatile hours per worker than salaried workers. The cyclical volatility of employment, by contrast, is higher for salaried workers. Using a model with search and matching in which a matched worker and firm bargain over the intensive hours margin, I show how pay type itself can lead to hours per worker being more volatile among hourly workers. Pay stickiness hinders worker and firm from adjusting hours in response to productivity changes, and a sticky salary is a larger impediment than a sticky wage.

In 2017 Milner Library at Illinois State University received a grant from the Digitizing Hidden Collections program, a national grant competition administered by the Council on Library & Information Resources (CLIR), for a collaborative digitization project of circus route books held by Circus World, Illinois State University, and the John and Mable Ringling Museum of Art. The three institutions house the largest circus collections in the United States and collectively they shared their unique route books to build a digital collection for the Step Right Up: Digitizing Over 100 Years of Circus Route Books project.

Objectives The sociohistorical experiences of Asian American older adults (AAOA) vary, but limited research has examined how immigration status operates as social determinants. This study builds on an existing framework to examine the relationship among social determinants and the differential effects of immigration status on cognitive difficulties among AAOA. Methods Using 5-year estimate data from the 2019 American Community Survey, the study sample consisted of AAOA aged 65 years and older identifying as Chinese, Filipino, Indian, Japanese, Korean or Vietnamese (N=100,584). AAOA were categorized as noncitizens, naturalized, or US-born for their immigration status. Participants who indicated having difficulty concentrating, remembering, or making decisions were categorized as having cognitive difficulties. Results Chinese were the most prevalent ethnic group (30%). Over 70% were naturalized citizens. About 8% endorsed having cognitive difficulties. According to bivariate analyses, there were considerable differences in AAOA’s characteristics (e.g., age, gender, marital status, medical insurance, employment status) by their immigration status. The results from the logistic regressions showed the immigration status was independently associated with poor cognitive difficulties. By AAOA’s immigration status, unique protective and risk factors were presented for cognitive difficulties. Discussion The differential pattern of cognitive difficulties among AAOA reveals a fuller picture of variations within AAOA by the immigration status. The results imply that more research is needed to develop culturally-sensitive practices that account for the racialized differences by AAOA’s immigration status. Further research into the interplay between structural determinants is necessary to formulate practice and policy interventions to address better successful aging for AAOA.

The resume audit literature provides strong evidence of discriminatory practices in hiring, raising critical concerns regarding equitable labor market outcomes. While the impacts of these practices on disparities in labor market levels are better understood, their cyclical effects are less known. In this paper, we research how hiring discrimination affects the volatility of labor market outcomes for disadvantaged groups by integrating empirical findings from audit studies into a search-and-matching model with a modified urn-ball matching function. Intuitively, in recessions, there are more applicants per job opening, which hurts discriminated groups. Applying this model to the U.S. economy, we find that it accounts for approximately 70% of the excess business cycle volatility in the unemployment rates of African Americans, as recorded in CPS data. Our research highlights the broader economic implications of discrimination, stressing the necessity for policy interventions , and offers a novel framework for future studies on labor market inequalities.

The geospatial dataset presented here represents historical middle 19th century built environment features for the Chesapeake Bay Eastern Shore region of Maryland, USA, including present-day Cecil, Caroline, Dorchester, Kent, Queen Anne's, Somerset, Talbot, Wicomico, and Worcester counties. Individual geospatial data layers include roads, landings, ferries, churches, shops, mills, schools, hotels, towns with post offices, and towns with court houses. These data were digitized using Simon J. Martenet's (1866) Map of Maryland: Atlas Edition and contemporary geospatial road network data from the Maryland Department of Transportation.

This infographic provides key highlights for Asian American, Native Hawaiian, and Pacific Islander (AAPI) service members, veterans, and their families. The information and statistics in this document are from various data collection efforts centered on military life, resource and financial needs, employment, entrepreneurship, and higher education. Asian Americans, Native Hawaiians, and Pacific Islanders are one of the most culturally and linguistically diverse racial groups in the U.S. (their heritage traces to over 30 different countries and ethnic groups and include over 100 languages and dialects). Photo Credit: Tech. Sgt. Sarah Corrice

For people who are blind or have low vision (BLV), physical barriers and negative experiences related to using current transportation options can have negative impacts on quality of life. The emergence of levels 4 – 5 automated driving system-dedicated vehicles (L4+ ADS), which will not require human operators to provide any input into the dynamic driving task, could empower the BLV community by providing an independent means of transportation. Yet, the BLV community has concerns that their needs are not being adequately considered by those currently developing L4+ ADSs, which will result in this technology being inaccessible to populations that it would otherwise greatly benefit. The current study sought to address this gap in the literature by explicitly evaluating the information and interactions that BLV riders will require from L4+ ADS. Specifically, we collected focus group and empirical data across three studies on BLV riders’ information and interaction requirements for L4+ ADSs across expected and unexpected driving scenarios as well as pick-up and drop-off tasks (PUDO). Through focus groups with sighted (n = 11) and BLV participants (n = 11; Study 1), we identified similarities and differences between sighted and BLV participants in terms of their user needs for L4+ ADSs across five challenging driving scenarios. Next, we examined BLV participants’ (n = 13; Study 2) information requests in real-world settings to better understand BLV riders’ needs during a simulated L4+ ADS experience. Our findings show that BLV riders want information that helps with (a) orienting to important objects in the environment during PUDO, (b) determining their location while riding in the ADS, and (c) understanding the ADSs’ actions. Finally, we developed an HMI prototype using BLV riders’ feedback in Studies 1 & 2 and had BLV participants engage with it during a simulated L4+ ADS trip (n = 12; Study 3). Our results suggest that BLV riders value information about nearby landmarks in familiar and unfamiliar areas, as well as explanations for ADS’s actions during ordinary and unexpected scenarios. Additionally, BLV riders need information about required walking distances and presence of tripping hazards in order to select a drop-off location. Taken together, our studies show that BLV riders have specific requirements that L4+ ADS must meet in order for this to be an accessible means of transportation. In light of these findings, we generated 28 guidelines and 44 recommendations that could be used by designers to improve the accessibility of L4+ ADSs for BLV riders.

Using CPS data, we examine the occupation mobility rates of individuals who became unemployed within the 3 month period immediately following the onset of the Covid-19 pandemic in March 2020. We define an individual as having undergone an occupation change if their recorded occupation upon re-entering employment differs from the last occupation that they worked in prior to becoming unemployed. While controlling for respondents' demographic characteristics and pre-unemployment occupations, we find that individuals who became unemployed during the first 3 months of the pandemic were approximately 18 percentage points less likely to have changed occupations upon returning to employment than individuals who became unemployed prior to the pandemic. However, this decline is not observed among individuals who became unemployed in later parts of 2020, or in subsequent years. We find that approximately 38% of the decline in mobility following the onset of the pandemic can be accounted for by high rates of expected recall by former employers during the early months of the pandemic. Slightly more than half of the remaining decline in mobility is consistent with poor local macroeconomic conditions, rather than other pandemic-specific characteristics.

The evolving social movement in the United States around creating a healthier and more equitable food system has popularized grassroots initiatives such as farmers markets, community gardens, and farm-to-school projects-just to name a few. We argue that identifying structural inequities, such as housing access, that are intertwined with access to food will provide much needed evidence about how policymakers can best target their efforts. Specifically, the purpose of this research is to investigate the role that mortgage lending bias and historic redlining practices play in inequitable access to food in California. We conclude that without addressing structural inequities, the grassroots initiatives of the food movement will have a diminished effect.

In recent years, an array of political, environmental, and health activists have brought to light the previously overlooked structural inequalities that plague many urban cities and their underserved populations. With a growing population and an increased dichotomy between social classes in the United States, urbanization may be inevitable. However, how urban planners and public agencies choose to build and design these areas is malleable. Provision of safe and equitable living conditions by these individuals is an obligation of utmost importance, and as such, this thesis aims to both provide insight as to how the built environment, development patterns, and land use play a significant role in in morbidity and mortality in urban communities across the nation and world, as well as assist in bridging the divide between disciplines of urban health and urban planning as we look towards creating healthier, greener, more equitable cities. The built environment and health can and should be discussed in the same breath during urban planning and development, and thus, the preservation, presence, and development of urban green space should be prioritized during processes of urbanization, with active engagement and empowerment from the communities in which we seek to build. The existing inverse association between increased urbanization and community health necessitates an induction of change and a call for action from urban planners, city and state officials, health scientists, environmental conservationists, and communities as a whole.

This study identifies the link between women's asset ownership and women's empowerment. Women's empowerment is measured by their decision-making role related to their health, large household purchases, and their social interaction. Using Demographic and Health Surveys data for 18 countries from South Asia, the Middle East, and sub-Saharan Africa, we found that the women who owned assets were 14% more likely to be empowered compared with the women who did not own any asset (odds ratio: 1.14, 95% confidence interval: 1.10–1.185). At a disaggregated country level, asset ownership was positively and significantly associated with women's empowerment in nine countries, negatively associated in one country, and had no significant association in the other eight countries. This study provides important insights into the link between women's asset ownership and empowerment and may inform public policy related to gender equality through women's empowerment.