I compile and disseminate novel panel data sets measuring county-level travel distances to abortion facilities and resident abortion rates. Using these data and exploiting temporal and spatial variation in distances, I implement difference-in-difference research designs measuring the causal effects of distance to the nearest abortion facility. The results indicate large and non-linear effect: An increase in travel distance from 0 to 100 miles—a level that courts have generally treated as not unduly burdensome for women seeking abortions—is estimated to prevent 20.5% of women seeking an abortion from reaching a provider, and in turn to increase births by 2.4%.

Purpose: Previous research has shown a significant association between psychological distress (PD) and all-cause mortality. However, this association is not fully explored, and life expectancy by PD is unknown. Methods: We used the pooled 1997–2014 data from the National Health Interview Survey linked to National Death Index (n = 513,081) to examine the association of the Kessler 6-item PD scale with life expectancy and all-cause mortality. Life expectancy by PD was computed using the standard life table method. Cox regression was used to model survival time as a function of PD and sociodemographic, behavioral, and health characteristics. Results: The age-adjusted mortality rate for adults with serious PD (SPD) was 2632 deaths per 100,000 person-years, compared with 1428 for those without PD. Life expectancy was inversely related to PD. At age 18, those with SPD had a life expectancy of 45.0 years, compared with 55.6 years for those without PD. The age-adjusted relative risk of all-cause mortality was 125% higher for adults with SPD (hazard ratio = 2.25; 95% confidence interval = 2.14, 2.37) than those without PD. Mortality risk associated with SPD remained (hazard ratio = 1.14; 95% confidence interval = 1.08, 1.20) after covariate adjustment. Conclusions: U.S. adults with SPD had significantly higher mortality risk and lower life expectancy.

This report provides data and information to help state and community leaders make progress in their equity, diversity, and inclusion efforts. Gov. Spencer Cox’s One Utah Roadmap, the Utah Legislature’s policies to extend opportunity to all, and business and community leaders’ Utah Compact on Equity, Diversity, and Inclusion provide three significant examples in the past year of Utah’s commitment. The data and context provided in this report shed light on existing disparities; help people understand the complexities of these measures; and help provide a starting point for evaluating future progress.

The purpose of this study is to describe population-level trends in intentions to remain childless (ITRC) among men and women in the United States in the first decades of the twenty-first century. We use a sample of 31,739 women and 24,524 men aged 18–44 from a cross-sectional and nationally representative survey, the National Survey of Family Growth. Our analyses utilize five of the survey's cycles: from 2002 through 2015–2017. Trends in the unadjusted proportions of men and women who report ITRC are presented, along with predicted probabilities of reporting ITRC from multivariate regressions. At the beginning of the twenty-first century, the prevalence of ITRC increased in the general population of men and women in the United States as well as among the youngest adults aged 18–24. If ITRC are realized, permanent childlessness rates could increase in the near future, contributing to the ongoing fertility decline in the United States. Further analyses uncover similarities and differences in the ITRC trends and correlates between men and women. Increases in ITRC among women are connected to changes in the socio-demographic composition of the population but ITRC increases among men are not connected to population composition changes. In addition, a positive education gradient is observed in ITRC among women but not among men. These variations in ITRC prompt a call for further research into gender and intentions for childlessness.

Urban trees play a key role in alleviating elevated summertime land surface temperatures in cities. However, urban landscape influences the capacity of urban trees to mitigate higher temperatures. We propose that both developed land characteristics and tree cover should be considered to accurately estimate the mitigation effects of canopy cover. We subclassified original land cover based on the canopy cover ratio to capture the within-land cover heterogeneity. We selected two coastal cities with different summertime climatic conditions: Seattle, Washington, USA, and Baltimore, Maryland, USA. We used Landsat-based grid cells (30 m × 30 m) as our spatial analytical unit, with corresponding land surface temperature, canopy area, canopy compactness, population size, and National Land Cover Database (NLCD)-based land cover group. We first used grouped boxplots, Kruskal–Wallis H tests, and post-hoc multiple comparison tests to detect the distribution of land surface temperatures by the land cover group. We then introduced statistical models to test the group effects on the relationship between land surface temperatures and canopy cover variables. We found: (1) land surface temperature increases with level of development, (2) land surface temperature decreases with canopy cover level, (3) the magnitude of the mitigation effects from canopy area differs based on development level and current canopy cover, (4) the differing efficacies of canopy area in decreasing land surface temperature follows a nonlinear threshold relationship, and (5) compactness of canopy cover was not significant in reducing the land surface temperature. These findings suggest the importance of considering heterogeneous canopy cover within developed land cover classes in urban heat island research. Tree planting strategies need to consider the nonlinear relationships between tree canopy cover and land surface temperature alongside environmental equity concerns.

How does demographic and religious context relate to interracial relationships among same-sex and different-sex couples? Using couple data from the 2012 to 2014 American Community Surveys matched to aggregate data from the 2010 Census and 2010 Religious Congregations and Membership Study, we test how heterogamy patterns for same-sex and different-sex couples vary by the demographic and religious makeup of cities, using multinomial logistic regressions to compare interracial and same-race couples. We find that same-sex couples are more likely to be in a White/Black interracial pairing than different-sex couples. White partners are more likely to be in an interracial relationship if they are in a city with a large minority group population. In addition, context is differently associated with interracial unions for same-sex and different-sex couples, varying for each racial combination.

The coronovirus disease 2019 (COVID-19) pandemic has prompted many school districts to turn to distance or at-home learning. Studies are emerging on the negative effects of distance learning on educational performance, but less is known about the socio-economic, geographic and demographic characteristics of students exposed to distance learning. We introduce a U.S. School Closure and Distance Learning Database that tracks in-person visits across more than 100,000 schools throughout 2020. The database, which we make publicly accessible and update monthly, describes year-over-year change in in-person visits to each school throughout 2020 to estimate whether the school is engaged in distance learning. Our findings reveal that school closures from September to December 2020 were more common in schools with lower third-grade math scores and higher shares of students from racial/ethnic minorities, who experience homelessness, have limited English proficiency and are eligible for free/reduced-price school lunches. The findings portend rising inequalities in learning outcomes.

We study a labor market characterized by search frictions in which firms choose between posting non-negotiable wage offers and bargaining wages with individual workers. We use the model to study the positive and normative implications of heterogeneous wage-setting strategies in labor markets, as well as the potential effect of policies that seek to regulate wage-setting. We analytically derive-and empirically validate-a testable prediction from the model regarding the cross-sectional prevalence of bargaining and renegotiation of wages among workers. We then estimate the model and use it to evaluate counterfactuals in which either wage-setting procedure is mandated. We find that eliminating bargaining reduces the overall gender gap in wages by 6%, the education gap by 3%, and residual wage dispersion by 12%, while leading to welfare losses for workers. Similar numbers are observed when bargaining is mandated, with ensuing welfare gains for workers. Either policy raises output by 1-3% by eliminating inefficient job mobility, but accounting for firm responses in vacancy creation can overturn these effects.

The 2010 Affordable Care Act (ACA) included two provisions, the Employer Shared Responsibility Provision (the “employer mandate”) and the Small Business Health Options Program (“SHOP”), aimed at increasing the availability of employer-sponsored health insurance (ESI) among workers at small firms. To examine whether these provisions led to greater ESI availability, I use 2011–2017 Medical Expenditure Panel Survey (MEPS) data in a difference-in-difference framework that compares changes in ESI availability among workers at small and large firms before and after the ACA's provisions come into effect. My estimates show that there is a 3.5 percentage point increase in ESI availability among workers at smaller firms after 2013. When focusing on workers most likely to be affected by the employer mandate, I find a larger 5.2 percentage point increase in ESI availability, amounting to a 39% decline in the proportion who do not have ESI available. However, I find no evidence that greater ESI availability led to increases in ESI coverage rates. Instead, descriptive estimates suggest that gains in health insurance coverage after 2013 consist of significant increases in the number of working adults who report having Medicaid coverage, including among workers who are offered ESI. I use MEPS data for my analysis because, along with employment, firm size, and health insurance details, MEPS also provides health status and healthcare access/utilization information. Looking at changes in these health measures, I find only limited evidence to suggest that the ACA's provisions improved access to care or measures of health status for workers.

The collection, processing, and analysis of remote sensing data since the early 1970s has rapidly improved our understanding of change on the Earth s surface. While satellite-based Earth observation has proven to be of vast scientific value, these data are typically confined to recent decades of observation and often lack important thematic detail. Here, we advance in this arena by constructing new spatially explicit settlement data for the United States that extend back to the early 19th century and are consistently enumerated at fine spatial and temporal granularity (i.e. 250m spatial and 5-year temporal resolution). We create these time series using a large, novel building-stock database to extract and map retrospective, fine-grained spatial distributions of built-up properties in the conterminous United States from 1810 to 2015. From our data extraction, we analyse and publish a series of gridded geospatial datasets that enable novel retrospective historical analysis of the built environment at an unprecedented spatial and temporal resolution. The datasets are part of the Historical Settlement Data Compilation for the United States

Using data for nearly 40 cohorts of American college graduates and exploiting regional variation in economic conditions, we show robust evidence of a positive relationship between the unemployment rate at the time of college enrollment and subsequent annual earnings, particularly for women. This positive relationship cannot be explained by selection into employment or by economic conditions at the time of graduation. Changes in major field of study account for only about 10% of the observed earnings gains. The results are consistent with intensified effort exerted by students who experience bad economic times at the beginning of their studies.

BACKGROUND Between 1964 and 2019, the percentage of people in the United States who had moved in the previous year decreased from 20.3% to 9.8%. It is unclear whether this trend was driven by period-specific factors that gradually diminished the prospects of moving for the population as a whole or whether distinct features of birth cohorts differentially contributed to the migration slowdown. OBJECTIVE The present study assesses whether the migration slowdown in the United States was primarily driven by period effects or by cohort effects. METHODS Using 46 waves of data across the 1964–2019 Annual Social and Economic Supplements to the Current Population Survey, I estimate a series of mixed-effects models predicting the probability of moving and a linear model with age x period interaction terms predicting the probability of moving. RESULTS Cohort effects are more salient in slowing the rates of migration than are period effects. The migration slowdown occurred in part because members of the Silent and Baby Boom generations, who had a higher probability of moving at all ages, matured out of their prime years of geographic mobility in young adulthood and were replaced successively by members of Generation X, the Millennial generation, and Generation Z, who comparatively have a lower probability of moving. CONCLUSION The findings suggest that migration measures and subnational population projections that rely on period-level inputs might potentially mischaracterize current and future demographic trends in the United States. CONTRIBUTION This study is the first age-period-cohort analysis of the contemporary migration slowdown in the United States.

County of residence is not observed in the public-use 1970 and 1980 Decennial Census data, to preserve respondent confidentiality. Instead, the metro 1% samples delineate 'county groups' for each year. This prevents researchers from conducting research with these Decennial Census data at the level of any time-consistent geographic unit smaller than commuting zones-and that is only possible using probabilistic crosswalks written by other researchers (Autor and Dorn, 2013). I provide and detail new population-based crosswalks which allow researchers to probabilistically distribute individuals to their counties-of-residence, enabling research with these data at the county level. To demonstrate the accuracy of the crosswalks, I compare the results to a variety of county-level data from the Census Bureau.

Data on COVID-19 cases by town show that the post-holidays surge is here. Daily new cases for all age groups have also spiked following Christmas and New Year’s Eve. Hospitalizations have remained relatively flat since Thanksgiving, but there is no reason to believe that infection rates will return to summertime levels. In fact, Connecticut appears to be caught in a cycle of community transmission that may not slow down for months. As reported in a previous analysis of cases by age group, Working-age people, those between 20 and 39 years old, have been testing positive at higher rates than any other age category since September. By the beginning of October, daily new cases began to surge and case rates have remained high for the last few months.

Using a newly assembled data set of US patents, we show that innovation activity is less concentrated in high-density locations than commonly believed. Yet, inventions based on atypical combinations of knowledge are indeed more prevalent in high-density urban centres. To interpret this relation, we propose that informal interactions in densely populated areas help knowledge flows between distant fields, but are less relevant for flows between close fields. We build a model of innovation in a spatial economy that endogenously generates the pattern observed in the data: specialised clusters emerge in low-density areas, whereas high-density locations diversify and produce unconventional ideas.

A large body of sociological research has shown that racial minorities and women experience significant disadvantages in the labor market. In this visualization, the author presents evidence from the Current Population Survey examining the effects of the coronavirus disease 2019 crisis on racial and gender inequalities in employment in the United States among prime-age workers. The author shows that the white-nonwhite gap in employment increased significantly during the post-outbreak period. Results from individual fixed-effects regression models show a strong white male advantage in the likelihood of being laid off for post-outbreak months compared with women, black men, Hispanic men, and Asian men.

In recent years, higher education researchers and practitioners have increasingly recognized that socioeconomic gaps in degree attainment are of utmost concern. Yet, despite the rise in attention relating to these socioeconomic gaps, the field of higher education continues to face challenges in assessing college access and success for students from less-privileged socioeconomic backgrounds, often relying on narrow socioeconomic metrics such as the Pell grant status, firstgeneration status, and school lunch status. Additionally, scholars must contend with the challenge of generating more accurate socioeconomic metrics while using data which is already available. In other disciplines, such as sociology, psychology, and public health, numerous studies have examined the use of neighborhood-based variables as proxies for socioeconomic status, demonstrating that they may serve as reliable indicators for individuals’ backgrounds. However, in the field of higher education, neighborhood-based variables are rarely utilized, and considerations of place and space are only recently being given their due acknowledgement. This study attempts to fill this gap by examining the use of neighborhood-based socioeconomic variables as predictors of individuals’ retention, success, and status changes in higher education. This study draws on theories that seek to explain factors that impact college student retention/attrition for understanding any possible differences between individuals from different type of neighborhoods. Additionally, sociological theories pertaining to segregation and capital accumulation underlie key assumptions of this study. The site for this study included a large, public, four-year state flagship institution, referred to as Midwest University. This study utilizes the incoming Autumn 2012, in-state undergraduate cohort – a sample of nearly 6,000 individuals – and a series of analyses – including binomial regression and survival analyses – in order to examine how students’ neighborhood-based socioeconomic variables may be correlated with their retention, success, and status changes over a six-year period. As a result of these analyses, I demonstrate neighborhood socioeconomic context (as measured at the census tract and block group levels) to be a valuable indicator of students’ retention and success after enrolling in college and provide implications for future research, policy, and practice.

The objective of this study is to examine young adults’ perceptions of the pandemic. This study is based on a content analysis of memes posted on one of the most popular emerging–adult-focused Facebook groups established during the pandemic. It finds that three themes emerged: pandemic humor, generational identity humor, and generational conflict humor. Memes about the pandemic include sub-themes of a coming apocalypse, adults who deny the seriousness of COVID-19, and a more general expression of negative feelings, particularly anger and fear, through humor. Posts also emphasize the existence of a shared generational identity through humor, with commonly understood references to issues like online learning, productivity, and mental health. Finally, generational conflict humor emphasizes antagonism with older generations, including mistrust of government and political leaders, professors, and universities.

Do higher-paying firms offer more favorable work, or compensate for less favorable work? Using matched employee-employer data for the United States, this paper estimates the joint distribution of wages, amenities, and job satisfaction across firms. Forty-eight amenities are captured by applying topic modeling to workers' free-response descriptions of their jobs. There are three main findings. First, high-paying firms are high-satisfaction firms because they offer better amenities: 81-92 percent of the rise in job satisfaction from moving to a higher-paying firm reflects improved non-wage aspects. Second, workers, especially high-earners, are willing to pay for job satisfaction, gaining in amenity value at least 54-101 percent of the average wage when moving from the worst-to the best-amenity firms. Third, since the elasticity of amenity value to wages across firms is positive (1.0-1.8), incorporating non-wage amenities nearly doubles the variance in total compensation across firms. Wages therefore understate firm-level inequality.

When the novel coronavirus began to spread in the United States in March 2020, most child care centers and home-based providers across the country shuttered their doors. From February to April of 2020, more than 370,000 members of the child care workforce left the field.1 Although workers slowly began to return to work as the country reopened, as of December 2020, the workforce is still 17 percent smaller than it was before the pandemic began.2 And those in the child care/early childhood education (CC/ECE) workforce who have returned to work are facing harsher working conditions and greater stressors than ever before. In this report, the term “child care/early education workforce” is defined to include center-based staff (including directors, teachers, and aides) and family child care and home-based providers (including legally operating unlicensed providers and family, friend, and neighbor caregivers). CC/ECE workers must now contend with more stringent cleaning, health, and safety requirements,3 while caring for young children who may be unable to understand the severity of the moment. Providers are facing increased operating costs and decreased enrollment, and centers must try to maintain staff through a period of serious fiscal uncertainty (Workman and Jessen-Howard 2020). Every child care worker serving families during this pandemic is risking their own health and the health of their family to provide the care needed to keep our economy open.4 These concerns compound the challenges the 6 SUPPORTING THE CHILD CARE AND EARLY EDUCATION WORKFORCE child care workforce, especially many Black, Latina, ∗ and Native American providers, have faced for decades: low pay, inadequate benefits, high turnover rates, and challenging work (Austin et al. 2019). Women of color have most acutely felt the impacts of COVID-19 on the child care workforce.5 Child care workers are more than two and a half times more likely to be either Black or Latina compared with the overall workforce (Austin et al. 2019).6 And following the disturbing pattern shown for communities of color across the country, Black, Latina, and Native American child care providers are more likely to test positive for COVID-19 than their white counterparts—a pattern attributed to structural inequities in access to health care (Gilliam et al. 2020). Without efforts to stabilize the child care field and address the particular challenges of the COVID-19 crisis, we risk permanent job loss and damage to a field dominated by women of color. The pandemic has exposed many of the structural challenges facing this group of workers; this may be a unique opportunity for policymakers to take significant action to improve working conditions, compensation, and benefits for and stabilize the child care and early childhood workforce. In this report, we aim to provide policymakers with concrete, feasible policy solutions that could be implemented in the near term to better support the CC/ECE workforce. Laying out these strategies is critical to informing several possible policy opportunities, including how to allocate new funding available in the coronavirus stimulus package passed in late December 2020 or from other congressional actions in the coming year, inform policy actions of the incoming Biden administration, and inform investments and strategies of state policymakers and the philanthropic community as they consider ways to shore up the CC/ECE workforce in these complex times.