Over the past few decades, Hispanic young adults have made impressive gains in educational attainment, but improvements have not been even by gender, with Latinas now averaging more schooling than Latinos. These developments in education have implications for Latinx marital sorting behavior and the marriage conditions that they face. Using data from the American Community Survey, we examine intermarriage patterns of Hispanics ages 25 to 34, focusing on gender differences in assortative mating along ethnic and educational lines. We show that college-educated Latinos are less likely than both their lesser-educated peers and college-educated Latinas to marry partners who are less educated than themselves. We also reveal that highly educated Latinas are more likely than Latinos with comparable levels of education to intermarry. We discuss implications for the intergenerational maintenance of Hispanicity as an ethno-race, and for their ability to transmit the socioeconomic gains obtained via educational improvements to future generations of Hispanics.

This study examines a possible connection between shifting gender and family norms and declining internal migration. Using data from the 1989–1998 and 2009– 2018 Annual Social and Economic Supplements of the Current Population Survey, we examine whether co-breadwinner married couples have become less likely to migrate within the US relative to couples with a sole or primary breadwinner. We find a general U-shaped association between wives’ share of a married couple’s income and that couple’s likelihood of moving across state or county lines; in both time periods, couples were least likely to move when their incomes were roughly equal. However, we find this U-shaped pattern grew more pronounced in the 2010s compared with the 1990s: Over time, co-breadwinner couples became increasingly less likely to move relative to other married couples. Given that family migration decision-making has historically been gendered, this suggests dual-career married couples have become less willing to uproot women’s careers for the benefit of men’s. We argue the most likely reason for this change in behavior is a shift in norms governing the gender division of labor—in particular, a shift away from the cultural model of the male breadwinner. Based on a decomposition analysis, we estimate this change explains about one-third of the overall decline in migration among married couples ages 25–39 between the 1990s and 2010s.

Body weight status misperception, perceiving one’s self to be thinner than one’s body mass index (BMI), is growing in the United States. At risk for lifestyle-related disease, African Americans face more dire consequences with respect to this misperception than others. In a sample of African American Kentuckians, we found a moderate level of body weight status misperception. Educational attainment was the strongest predictor of body weight status misperception, with more education associated with less misperception. These findings suggest that health communication for African Americans should address body weight status misperception and be tailored for individuals’ level of educational attainment.

How did cliometrics in particular, and economic history in general, arrive at this crossroads, where it is at once considered to be a dying discipline and one that is spreading through the economics discipline as a whole? To understand the current status and future prospects of economic history, it is necessary to understand its past.

The nullification of slave wealth after the US Civil War (1861-1865) was one of the largest episodes of wealth compression in history. We document that White Southern households that owned more slaves in 1860 lost substantially more wealth by 1870, relative to Southern households that had been equally wealthy before the war. Yet, their sons almost entirely recovered from this wealth shock by 1900, and their grandsons completely converged by 1940. Marriage networks and connections to other elite families may have aided in recovery, whereas transmission of entrepreneurship and skills appear less central.

A universal child allowance is considered a simple and effective policy to reduce adult poverty, child poverty, and potentially inequality. It is often compared to childcare subsidies. This study investigates the relative efficacy of provision of free childcare (using a transfer payment equal to the household’s expenditure on childcare as a proxy) and of a child allowance with the same fiscal burden (a payment made to each child’s guardian equal in value to the value of the total program divided by the number of children). We use US Current Population Survey data aggregated over the 2018-2020 period to simulate the impact of each policy on measures of poverty and inequality, stratifying results by state. We perform a secondary analysis using state-based cost of childcare estimates from the Center for American Progress to represent necessary expenditure on childcare. We find modest improvements in measures of adult poverty and inequality that are substantially larger for the child allowance. We find relatively large reductions in the child poverty rate that are much larger for the child allowance policy. We find substantial heterogeneous effects by state, though the impact of the child allowance is almost unilaterally greater.

Gender segregation in the labour market is a factor that has been identified in the literature to contribute to the remaining gender wage gap. This paper investigates one of the possible determinants of gender-related labour market choices by investigating the role of parental occupational choices on the occupational choices of young adults. Longitudinal data from the National Longitudinal Survey of Youth 1979 and the National Longitudinal Survey of Youth 1979 Child and Young Adult have been combined into an informative cross-section of mothers and young adults, including information at several points in time. Due to endogeneity concerns regarding parental occupation, the estimator by Klein and Vella (2010) is considered in the empirical analysis. The results imply that mothers who make more gender-stereotypical labour market decisions have children who do so as well. These findings suggest that attempts of policy makers to decrease gender inequality in the labour market might be less successful due to the intergenerational transmission of gender-stereotypical labour market behaviour.

These appendices offer detailed information about the process that we used to develop Oregon Poverty Measure (ORPM) estimates (Rothwell et al., 2020). The ORPM methodology reflects the overall spirit of the federal Supplemental Poverty Measure, while adopting many of the decisions used in recent iterations of selected state-level poverty measures, especially the California Poverty Measure (e.g., Bohn et al., 2017; Mattingly et al., 2019) and the Wisconsin Poverty Measure (e.g.,Isaacs et al., 2010; Marks et al., 2011; Smeeding & Thornton, 2019). Our methodology also reflects the observations and recommendations offered by Renwick (2015). We especially appreciate the sharing of detailed information and insights by other researchers, which greatly facilitated our own development process. Where relevant, we note key differences between our approach and the approach taken by other research teams.

“Rugged individualism”—the combination of individualism and anti-statism—is a prominent feature of American culture with deep roots in the country's history of frontier settlement. Today, rugged individualism is more prevalent in counties with greater total frontier experience (TFE) during the era of westward expansion. While individualism may be conducive to innovation, it can also undermine collective action, with potentially adverse social consequences. We argue that America's frontier culture hampered responses to the COVID-19 pandemic. Across U.S. counties, greater TFE is associated with less social distancing and mask use as well as weaker local government effort to control the virus. We argue that frontier culture lies at the root of several more proximate explanations for the weak collective response to public health risks, including a lack of civic duty, partisanship, and distrust in science.

Background: Police-reported crime data (hereafter “crime”) is routinely used as a psychosocial stressor in public health research, yet few studies have jointly examined (a) differences in crime exposure based on participant race and ethnicity, (b) differences in measures of crime exposure, and (c) considerations for how exposure to police is captured in police-recorded crime data. We estimate neighborhood exposure to crime and discuss the implications of structural differences in exposure to crime and police based on race and ethnicity. Methods: Using GPS coordinates from 1188 participants in the Newborn Epigenetics Study, we estimated gestational exposure to crime provided by the Durham, North Carolina, Police Department within (a) 800 m and (b) the Census block group of residence. We controlled for non-overlapping spatial boundaries in crime, Census, residential, and police data to report crime spatial (crime per km2) and population (crime per 1000 people per km2) density. Results: We demonstrate dramatic disparities in exposure to crime based on participant race and ethnicity and highlight variability in these disparities based on the type of crime and crime measurement method chosen. Conclusions: Public health researchers should give thoughtful consideration when using police-reported crime data to measure and model exposure to crime in the United States, as police-reported data encompasses joint exposure to police and crime in the neighborhood setting.

The rise of interest in urban mobility, along with trends in vehicle electrification and autonomy have led to the development of electric vertical and takeoff landing aircraft to offer Urban Air Mobility (UAM) services. We have quantified the market demand of UAM for 5 U.S. cities considering demand from substitution of ground based transport through UAM services for commutes and airport access. By quantifying the number of travelers in each city who would be willing to pay for the UAM service, we find that the unconstrained market potential demand for a city reaches up to 585,000 daily round trips, but varies for different cities and price points. We considered the market impacts of airspace, weather, and infrastructure constraints. We further couple this market model and a vehicle model with an operations model to optimize for daily profit via a Systems of Systems decomposition. In a case study of the Bay Area, the tilt rotor or autogyro maximize the system top level objective of daily profit, reaching over $20 000 a day with 6-10 vertiports.

With a population of forty million and substantial geographic variation in sociodemographics and health services, California is an important setting in which to study disparities. Its population (37.5 percent White, 39.1 percent Latino, 5.3 percent Black, and 14.4 percent Asian) experienced 59,258 COVID-19 deaths through April 14, 2021—the most of any state. We analyzed California’s racial/ethnic disparities in COVID-19 exposure risks, testing rates, test positivity, and case rates through October 2020, combining data from 15.4 million SARS-CoV-2 tests with subcounty exposure risk estimates from the American Community Survey. We defined “high-exposure-risk” households as those with one or more essential workers and fewer rooms than inhabitants. Latino people in California are 8.1 times more likely to live in high-exposure-risk households than White people (23.6 percent versus 2.9 percent), are overrepresented in cumulative cases (3,784 versus 1,112 per 100,000 people), and are underrepresented in cumulative testing (35,635 versus 48,930 per 100,000 people). These risks and outcomes were worse for Latino people than for members of other racial/ethnic minority groups. Subcounty disparity analyses can inform targeting of interventions and resources, including community-based testing and vaccine access measures. Tracking COVID-19 disparities and developing equity-focused public health programming that mitigates the effects of systemic racism can help improve health outcomes among California’s populations of color.

Approximately 30 million Americans remain uninsured, meaning that they do not have financial protection from the costs of obtaining health services and treatment, and many are eligible for Medicaid or Marketplace coverage. Black, Latino, and Native American persons are more likely to be uninsured, and communities of color have been especially hard hit by both the COVID-19 pandemic and the economic downturn. The Centers for Medicare & Medicaid Services (CMS) determined that the COVID-19 emergency presents exceptional circumstances for consumers in accessing health insurance and provided access to a Special Enrollment Period (SEP) for individuals and families to apply and enroll in the coverage they need. This SEP will be available to consumers in the 36 states served by the federal Marketplace on the HealthCare.gov platform. Consumer access to the 2021 COVID-19 SEP on HealthCare.gov began on February 15, 2021 and will run through August 15, 2021. This SEP is an opportunity for uninsured and underinsured individuals living in the 36 states using Healthcare.gov to enroll in affordable coverage. Some of these individuals may have lost health insurance coverage or income during the COVID-19 pandemic. The SEP also allows individuals currently enrolled in a plan through HealthCare.gov to switch plans. Most of the fifteen states (including the District of Columbia) that run a State-Based Marketplace (SBM) have also made available a COVID-19 SEP with a similar timeframe. Marketplace financial assistance, including advanced premium tax credit (APTC) payments, is essential to making health insurance available to individuals with no alternative for affordable coverage.9 APTCs are generally available to eligible individuals and families with household incomes between 100 and 400 percent of the federal poverty level (FPL) in states that have not expanded Medicaid under the ACA and between 138 and 400 percent FPL in states that have expanded Medicaid. 10 For many individuals, particularly low-income individuals, APTCs on HealthCare.gov are large enough to substantially reduce premiums for consumers, in some cases to zero dollars. These credits are based on the premium of the benchmark plan (the second-lowest cost silver (SLCS) plan) available through HealthCare.gov in a person’s area of residence. These zero-dollar and low-premium plans are more affordable so more people can enroll in health insurance. These plans can provide access to health care coverage and financial protection for millions of Americans who otherwise may be left uninsured and potentially liable for the full costs of their health care utilization. Previous literature has identified affordability and unawareness of subsidy eligibility as common reasons individuals remain uninsured. Zero- and low-premium plans help to directly address this challenge, but many uninsured individuals may not realize they may be eligible to enroll in zero- or low-premium HealthCare.gov plans. Lower costs may also attract more younger and healthier individuals to enroll in Marketplace plans, which in turn can improve the risk pool and lower overall average costs for the broader Marketplace population. This Issue Brief examines the availability of zero- and low-premium plans in states served by the federal Marketplace, Healthcare.gov, based on the premium subsidies available as of March 1, 2021, which does not yet include the enhanced subsidies created by the American Rescue Plan. Those subsidies will become available on Healthcare.gov on April 1, 2021, taking effect for covered enrollees as early as May 1, and are discussed in more detail later in this Issue Brief. Tables in the brief show zero- and low-premium plan availability for HealthCare.gov states overall, subset by demographic and other characteristics, and by state. The purpose of this Issue Brief is to expand understanding and awareness of the availability of low premium health plans, where they may be available, and to whom.

This unique book demonstrates the utility of big data approaches in human geography and planning. Offering a carefully curated selection of case studies, it reveals how researchers are accessing big data, what this data looks like and how such data can offer new and important insights and knowledge.

I study why some cities have strict land use regulation, how regulation affects the U.S. economy, and how policymakers can mitigate its negative consequences. I develop a quantitative spatial equilibrium model where local regulation is determined endogenously, by voting. Homeowners in productive cities with attractive amenities vote for strict regulation. The model accounts for one-third of the observed variation in regulation across cities. Quantitative experiments show that excessive local regulation reduces aggregate productivity, but not necessarily welfare because, unlike renters, homeowners benefit from regulation. I propose federal policies that raise productivity and welfare by weakening incentives to regulate land use.

In this brief, authors Rogelio Sáenz, Corey Sparks, and Asiya Validova report that in April 2020, after the first two months of significant spread of COVID-19 in the United States, nearly 25 million fewer people had a job. In June 2021, there were still 5.9 million fewer people employed, representing a drop of 3.7 percent in workers since before COVID. Workers of color, women, and those with lower levels of education have consistently had the highest unemployment rates, a trend that persisted through June 2021. The recovery of the workforce has not been equal, with dramatic differences based on race/ethnicity, gender, nativity, and level of education. During COVID, working from home has been a highly segregated opportunity, limited mostly to persons with college degrees. White workers are approximately 1.5 times more likely to be able to work from home than are Blacks and Latinos. While the employment situation has improved noticeably since the economic abyss of the shutdown of the economy in April 2020, the United States is still a long way from job recovery. The authors’ findings have important policy implications for the short- and long-term as, and after, the pandemic recedes. Many people are still without employment due to the loss of jobs that have not yet returned, the obligations they have for child care and elder care, and other situations. Many are on the verge of losing their homes as eviction bans expire. Many families continue to face hunger. There is a major need for the creation of policy to ensure that people have their basic necessities met and that they are able to make necessary adjustments, including job retraining, to begin the process of rebuilding their lives in the coming months and years.

Measures of educational assortative mating must contend with the fact that the marginal distributions of education differ by sex and change over time. I propose a new measure of assortative mating, which is based on Spearman’s rank correlation coefficient but instead uses sex-by-birth cohort education ranks. I show that this adjusted measure is more robust than other measures to changes over time in the underlying education distributions.

A definition and equity-minded framework for understanding postsecondary value must consider students’ investment in college, in addition to their returns. Student investment includes costs beyond tuition and fees. In order to be successful in school, students must be able to cover the cost of books, supplies, and transportation to and from class. Additionally, having sufficient resources for housing and food are crucial for allowing students to focus on their coursework without needing to work long hours to cover those expenses. Furthermore, student investment should include costs incurred over the entire length of a student’s enrollment, rather than looking only at costs in one year. There are a number of ways that student investment can be measured, including full cost of attendance (COA, also known as sticker price), net price (COA minus grant aid), and opportunity costs in the form of forgone earnings. This paper explores those options and makes recommendations for how student investment should be measured with ideal data and with data that are currently available, including U.S. Department of Education (ED) data that are available for all colleges and nonpublic data that institutions may be able to access for their own students. The recommendations in this paper are based on an extensive review of research and analyses of publicly available data, as well as discussion with staff members at the Institute for Higher Education Policy (IHEP), the Bill & Melinda Gates Foundation, and members of the Postsecondary Value Commission Research Task Force. The paper also identifies issues that require more research and includes recommendations for improving publicly available data to allow colleges and policymakers to better measure student investment.

Since the turn of the 21st century, the United States has experienced a drastic shift in the number and composition of immigrants entering its borders. Compared to native-born persons, immigrants are disproportionately more likely to become entrepreneurs and start small businesses. Entrepreneurship leads to greater financial gains and economic prosperity for immigrants and is also an important driver of job creation and community development around the United States. As a result of recent immigration restrictions and reduced movement due to the COVID-19 pandemic, there is concern about the long-term impact that decreased immigration will have on small business development and subsequent job creation. The aims of this paper are to: 1) conduct a historical trend analysis of immigrant entrepreneurship and job creation in the United States; and 2) develop projected estimates of immigrant entrepreneurship under alternative assumptions. Data were derived from the American Community Survey (ACS) linked to the United States Citizenship and Immigration Services (USCIS) database. Historical data was displayed graphically to visualize trends in key outcomes over time. Three projection models for entrepreneurship through the year 2031 were developed, with each model testing a different assumption regarding immigration. The first projection allows for a stable level of immigration, the second projection cuts immigration in half, and the third projection eliminates immigration entirely. With stable immigration, a projected 4,106,389 immigrant entrepreneurs will be in the United States in 2031, compared to 3,375,287 immigrant entrepreneurs if immigration is cut to zero. Given that the typical five-year-old firm employs an average of 17.43 people, this drop in entrepreneurship would eliminate 12,743,107 jobs in the United States within the next 10 years. The results shed light on the role of immigrant entrepreneurship in job creation during this decade. Policies that encourage and facilitate immigrant entrepreneurship,

We study how decades-long exposure to individuals of a given foreign descent shapes natives' attitudes and behavior toward that group. Using individualized donations data from large charitable organizations, we show that long-term exposure to a given foreign ancestry leads to more generous behavior specifically toward that group's ancestral country. To shed light on mechanisms, we focus on attitudes and behavior toward Arab-Muslims, combining several existing large-scale surveys, cross-county data on implicit prejudice, and a newly-collected national survey. We show that greater long-term exposure: (i) decreases both explicit and implicit prejudice against Arab-Muslims, (ii) reduces support for policies and political candidates hostile toward Arab-Muslims, (iii) leads to more personal contact with Arab-Muslim individuals, and (iv) increases knowledge of Arab-Muslims and Islam in general.