HIV pre-exposure prophylaxis (PrEP) is highly efficacious, and yet most individuals indicated for it are not currently using it. To provide guidance for health policymakers, researchers, and community advocates, we developed county-level PrEP use estimates and assessed locality and policy associations.

The Child Care and Development Fund (CCDF) provides child care subsidies to families with low incomes, helping them access affordable child care so that parents can work or participate in education or other approved activities. In Wisconsin, we estimate 175,500 children in 100,300 families are eligible to participate in CCDF in the average month. When we compare the eligibility estimates to the number of families and children who participate in CCDF, we estimate 18 percent of eligible children participate and 19 percent of eligible families participate. The factors that affect CCDF participation—including knowledge of the CCDF program, the availability of other options for obtaining lower-cost care, and the cost of unsubsidized care—are likely not constant across a state. Therefore, a full understanding of the reach of a state’s CCDF program among eligible families and children requires estimates of eligibility at a substate level. We provide these estimates for Wisconsin. In Wisconsin, the majority of the eligible children live in one-parent families (126,500), have monthly family incomes between 100 and 200 percent of the federal poverty guidelines (107,500), and have parents who work at least 35 hours a week (101,400). A little over a quarter of the eligible children (50,100) live in Milwaukee. Next, we describe the methods used to develop the estimates and provide detailed results.

We exploit the spatial and temporal variation of the staggered introduction of interstate banking deregulation across the U.S. to study the relationship between credit constraints and consumption of durables. Using the American Housing Survey from 1981 to 1993, we link the timing of these reforms with evidence of a credit expansion and household responses on many margins. We find robust evidence that households are more likely to purchase new appliances and invest in home renovations and modifications after the deregulation. These durable goods allowed households to consume less electricity and spend less time in domestic activities after the reforms.

1. Sowing the Seeds of Long Run Economic Decline When transportation costs were the dominant economic force determining suc- cess or failure, Ohio made historic investments in canals and rail to lower trans- portation costs and quickly pivoted from agriculture to manufacturing. Ohio rose to the 3rd most populous state in the nation with the first inland boomtowns. Ohio struggled to manage its sudden growth and quality of life in cities began to decline. Public health continues to be an issue for Ohio today. Every metric of success suggests Ohio continues to fall behind. 2. We Face More, not Fewer Challenges in the Decades to Come As transportation costs continued their dramatic decline, industry dispersed from Ohio to the south and eventually around the globe. Both trade and increasing productivity in manufacturing through automation have left Ohio failing to keep pace with the rest of the nation as it has failed to diversify its economy. 3. The Increasing Importance of Quality of Life Job growth increasingly goes to non-footloose jobs (not to footloose export sector jobs) that produce local goods and services, such as health care, education, recreation – goods and services that improve quality of life. Ohio has failed to make meaningful improvements in the amenities that increase quality of life. Quality of life (not the quality of the business environment) is increasingly associated with employment and population growth attracting high-skill workers. 4. Educated Workers are the Engine of Economic Growth Educational attainment may now be the single most important predictor of economic success. Only the most educated workers have experienced net job growth and real wage growth. The dominant economic force in the U.S. economy is a skilled workforce. Highly educated workers are more productive, more innovative, and better able to adapt to the changing economic headwinds. Ohio cannot succeed without a highly skilled, well-educated workforce. 5. Economic Development Policies for Ohio Ohio should focus on developing a skilled workforce by investing in education from early childhood education through higher education instead of focusing on ineffective sector-based economic development incentives designed to attract large manufacturing plants. To keep this skilled workforce (and attract new educated workers), Ohio must focus more on developing its comparative advantage in the amenities that enhance quality of life through local small businesses, increasing industry diversity, while lowering the tax burden on households.

We study the ways in which unemployment insurance (UI) benefits interact with other elements of the social safety net around job losses. We exploit a cutoff for UI eligibility, based on a workers' highest quarterly earnings in the past year, to generate quasi-experimental variation in UI receipt. We find that UI receipt cuts welfare (TANF) receipt by half among low-earning UI applicants, but has no impact on SNAP or Medicaid usage. However, because welfare participation is low in this population, overall crowdout is small. In the quarter following layoff, UI increases total income by 55 percent (including labor earnings and transfers).

Recent scholarship across various disciplines since the U.S. housing crisis of 2008 has deepened our understanding of racial wealth gaps, especially as it pertains to housing. This article focuses on two less-developed dimensions of Black and Latino home ownership, voting and immigration, respectively. The Black home ownership rate has fallen to 41% as of 2019, the lowest level since the 1968 Fair Housing Act. I contend that the continued decline of Black home ownership reduces voting turnout. A multivariate fxed efects analysis of state-level Black voter turnout in presidential elections since 2000 lends support to this contention. In contrast, the Latino home ownership rate has rebounded, climbing to nearly 48% in 2019. I argue that this rise is as much a mirage as sign of progress—an artifact of the deportation of millions of Latin Americans and the end of undocumented Mexican migration. Such changes infate Latino ownership rates by reducing the denominator rather than increasing the numerator of homeowners. Examining state-level data, my multivariate analysis shows that the decline in the undocumented population and, to a lesser extent, the increase of DACA recipients explain the level and change in Latino ownership more than the change in the share of Latino citizens or documented non-citizens. I conclude that the color line has reinforced a new Black/non-Black divide in home ownership that undermines the social mobility and electoral representation of Black Americans. Meanwhile, a tri-racial divide by legal status and race stratifes Latino home ownership. Intra-Latino inequality masquerades as success because of the expulsion of vulnerable Latino immigrants and their US citizen children. The social consequences distort the home ownership rate calculation and pose another threat to multiracial democracy.

To the extent that the current situation may again lead to a difficult recessionary period for Nevada there may be some similarities to the Great Recession we have recently emerged from. Accordingly this report looks back to the beginning of the Great Recession in Nevada and at what happened in the following years with a focus on housing and housing for low income households in order to gauge what Nevada could be facing in the coming months and years.

The COVID-19 pandemic has disrupted nearly every aspect of life in the United States, and elections are no exception. Adaptation to the COVID-19 pandemic has caused a rapid and dramatic shift to voting by mail for the Spring 2020 presidential primaries, in response to both public demands for a “no touch” voting experience and dramatic reductions in polling places due to a lack of willing poll workers. Online voting is sometimes proposed as an alternative to voting by mail, and some states attempted small pilot programs for online voting during the 2020 primaries. However, cybersecurity researchers have found substantial flaws in proposed Internet voting platforms, and public opinion polls find that an overwhelming majority of Americans perceive online voting as a threat to election security (Specter & Halderman, 2020). These problems mean that, for now, voting by mail is the only viable alternative to in-person voting. Assuming trends from the primary season hold through the November 3, 2020, presidential election, a conservative estimate is that more than 80 million ballots will come in by mail. This is an unprecedented level of mail balloting: by comparison, in the November 2016 election, only 33 million people voted by mail. (The 80 million estimate is based on a 70% turnout in November 2020 [an increase of 9% from 2016]; an estimated voting eligible population rate of 71.3% [calculated by using the voting eligible population in November 2016 of 230,931,921, taken from McDonald, 2016, and a total population estimate of 329M at that date, taken from https://www.census.gov/popclock/]; and a vote-by-mail rate of 50%, double the observed number of mail ballots in November 2016. I view the vote-by-mail rate as a conservative estimate of the likely increase, assuming COVID-19 is still at a pandemic state and given the rate of increase in mail balloting in the 2020 primaries [from 44% on the low end to 90% on the high end; Rakich & Skelley, 2020].)

The health and economic crisis like no other in the past 100 years that has been caused by coronavirus disease (COVID-19) has thrown socioeconomic inequalities and unequal access to health and social protection services into even sharper relief. It has also posed socioeconomic challenges that expose the most vulnerable groups in the population to even more severe risks and adversities than they were already facing. One of the most vulnerable groups is older persons, whose quality of life and rights are being directly impacted by the pandemic. Scientific evidence on the evolution of the pandemic and risk factors associated with COVID-19 have shown that people of any age can contract the disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, older persons have a higher probability of severe symptoms, complications and death, especially those aged 80 or over (WHO, 2020a; United Nations, 2020). In addition, studies show that pre-existing chronic or degenerative conditions are also risk factors associated with a higher probability of severe illness and death as a result of COVID-19 (WHO, 2020a), and it is well known that those comorbidities are more frequent among older persons. Hence the importance of protecting the rights of older persons during this health crisis, for which efforts must be made on two fronts. First, the right to health, which must be for all, without age-based discrimination. Second, the right to life and the right to a dignified old age until the end of one’s days. The shift in the age structure of the population in Latin America and the Caribbean is at very different stages in different parts of the region. The timing and intensity of the ageing process vary from one country to another and that process is still far from reaching the magnitude seen in Europe and other developed countries, where the older age structure and the pattern of contagion concentrated in this group have had much to do with the high mortality observed within a short period. In fact, although the region’s population is ageing, today only 13% of the population is aged 60 or over, far below the figure of 25% or more in several European countries. The situation across countries is also quite diverse, with some countries at an advanced or very advanced stage in the process, while it is just beginning in others (United Nations, 2019a). The countries with younger populations are, in most cases, the ones in which the social and economic development process is the least advanced and in which the population faces the greatest structural risks. These countries generally devote less resources to health care and are still in the process of organizing their health care systems. They have less experience in assisting and caring for older adults, and the coverage of their social security and protection systems is more limited and unequal.

In the United States, economic inequality is both racialized and gendered, with Black and Latina women consistently at the bottom of the economic hierarchy. Relative to men (across racial groups) and White women, Black and Latina women often have less-desirable jobs, lower earnings, and higher poverty rates. In this essay, we draw attention to the role of the state in structuring such inequality. Specifically, we examine how public policy is related to racial inequities in economic positions among women. Applying an intersectional lens to the contemporary landscape of economic inequality, we probe the associations between public policies and economic outcomes. We find that policies have unequal consequences across subgroups of women, providing prima facie evidence that state-level decisions about how and where to invest resources have differential implications based on women's race and ethnicity. We encourage scholars to use aspects of our approach as springboards for better specifying and identifying the processes that account for heterogeneous policy effects across racial subgroups of women.

This article utilizes recently published US Census data covering the pre‐and post‐Great Recession period (1990–2015) to identify key determinants of growth among small urban places in the New England Region. We find little evidence of random growth and robust evidence of convergence in growth, indicating that smaller urban areas tend to experience faster rates of growth than larger ones, over both the short and long term. Factors such as distance to large city areas and amenities are found to be particularly relevant to population growth rates. Having a diverse industrial base, high levels of human capital and proximity to large urban areas are factors that positively affect income growth. These results highlight the importance of policies geared to improve cities’ amenities, increase their industrial diversity, and attracting and retaining human capital in urban areas.

Medicaid enrollment increases during economic downturns which imply households using the public health insurance program during coverage gaps due to job loss. However, we provide new evidence demonstrating that the Medicaid program's countercyclical protections against economic downturns are largely concentrated in states with more generous Medicaid eligibility criteria for adults. We exploit the timing of the 2007-2009 Great Recession to compare trends in recession-linked Medicaid enrollment between states with more generous Medicaid eligibility guidelines and states with more restrictive guidelines. For similar effects of the recession, Medicaid enrollment grew larger states in with more generous Medicaid programs. Our work suggests for every 100 people becoming unemployed in states with a restrictive Medicaid program, about 96 would be uninsured, and about 11 would enroll in Medicaid. Conversely, about 49 would be uninsured in a state with more generous Medicaid guidelines and 57 would enroll in Medicaid.

The number of years women spend as mothers of young children likely has implications for women’s lifetime wages, earnings, and time use. Much prior research has pointed to widening education differences in a wide array of family patterns, but none has examined trends in the number of years women spend as mothers of young children. We use retrospective fertility data from the 2014 Survey of Income and Program Participation to show how changes in women’s completed fertility and birth spacing produce trends in years women spend as mothers of children under age six from 1967 to 2017. Despite remarkably parallel declines in completed fertility, growing educational differences in birth spacing produced educational divergence in years spent as mothers of young children. Particularly striking is the finding that increases in birth spacing reversed declines in years spent as mothers for women with less than a high school degree such that they spent more years with young children in the 2010s than in the late 1960s. The increasing prevalence of multiple partner fertility explains some but not all of these trends.

We elaborate a general workflow of weighting-based survey inference, decomposing it into two main tasks. The first is the estimation of population targets from one or more sources of auxiliary information. The second is the construction of weights that calibrate the survey sample to the population targets. We emphasize that these tasks are predicated on models of the measurement, sampling, and nonresponse process whose assumptions cannot be fully tested. After describing this workflow in abstract terms, we then describe in detail how it can be applied to the analysis of historical and contemporary opinion polls. We also discuss extensions of the basic workflow, particularly inference for causal quantities and multilevel regression and poststratification.

Conventional transportation practices typically focus on alleviating traffic congestion affecting motorists during peak travel periods. One of the underlying assumptions is that traffic congestion, particularly during these peak periods, is harmful to a region’s economy. This paper seeks to answer a seemingly straightforward question: is the fear of the negative economic effects of traffic congestion justified, or is congestion merely a nuisance with little economic impact? This research analyzed 30 years of data for 89 US metropolitan statistical areas (MSAs) to evaluate the economic impacts of traffic congestion at the regional level. Employing a two-stage, least squares panel regression model, we controlled for endogeneity using instrumental variables and assessed the association between traffic congestion and per capita gross domestic product (GDP) as well as between traffic congestion and job growth for an 11-year time period. We then investigated the relationship between traffic congestion and per capita income for those same 11 years as well as for the thirty-year time period (1982–2011) when traffic congestion data were available. Controlling for the key variables found to be significant in the existing literature, our results suggest that the potential negative impact of traffic congestion on the economy does not deserve the attention it receives. Economic productivity is not significantly negatively impacted by high levels of traffic congestion. In fact, the results suggest a positive association between traffic congestion and per capita GDP as well as between traffic congestion and job growth at the MSA level. There was a statistically insignificant effect on per capita income. There may be valid reasons to continue the fight against congestion, but the idea that congestion will stifle the economy does not appear to be one of them.

Although public debate ensues over whether parents or nonparents have higher levels of emotional well-being, scholars suggest that being a parent is associated with a mixed bag of emotions. Drawing on the American Time Use Survey for the years 2010, 2012, and 2013 and unique measures of subjective well-being that capture positive and negative emotions linked to daily activities, we “unpack” this mixed bag. We do so by examining contextual variation in the parenting emotions gap based on activity type, whether parents’ children were present, parenting stage, and respondent’s gender. We found that parenting was associated with more positive emotions than nonparenting, but also more negative emotions. This pattern existed only during housework and leisure, not during paid work. Moreover, patterns in positive emotions existed only when parents’ children were present; patterns in negative emotions were primarily observed during earlier stages of parenting. Results were similar for men and women.

The primary health insurance coverage reforms of the Affordable Care Act took (ACA) effect on January 1, 2014. Between 2013 and 2016, the uninsurance rate for nonelderly Americans from birth to age 64 fell every year,1 and 18.5 million more Americans had health insurance coverage in 2016 than in 2013.2 However, between 2016 and 2017, uninsurance increased by 0.2 percentage points.3 Using the American Community Survey, we find that uninsurance increased by an additional 0.2 percentage points between 2017 and 2018, meaning 500,000 more uninsured Americans (Figure ES 1). This increase in uninsurance occurred despite a strong economy and accompanying increases in incomes and employersponsored insurance (ESI) coverage. Recent research suggests that employer-sponsored coverage will decline during the COVID-19 recession, perhaps leaving millions more uninsured.4 This paper serves as a baseline for future measurement of coverage losses during COVID-19.

We observe that database queries can be considered as functions that can be approximated. This allows us to formulate a learning task to learn a single model to answer any query. This is different than many recent studies that learn a model for a specific query type, since we can learn the model for any query type. We formalize this observation, formulate the problem of learning to answer database queries and introduce NeuroDB, a generic neural network framework that can learn to answer different query types approximately. As a proof of concept, we show that NeuroDB can be specifically used to answer distance to nearest neighbour query and range aggregate queries, two important building blocks of many real-world applications. We experimentally show that NeuroDB answers these two query types with orders of magnitude improvement in query time over the state-of-the-art competitions, and by constructing a model that takes only a fraction of data size. NeuroDB achieves this by learning existing patterns between query input and output and by exploiting the query and data distributions. Furthermore, the same neural network architecture is used to answer both query types, bringing to light the possibility of using a generic framework to answer different unrelated query types efficiently.

The United States experienced two major demographic 'booms' during the second half of the twentieth century, in births after the second world war and in divorces 25 years later. This paper argues that the two booms are linked. As the baby-boom generations were entering marriageable age, men in previous cohorts were faced with exceptionally good remarriage prospects motivating them to rematch. The cohorts who ultimately divorced most were the ones with the biggest increase in remarriage opportunities for men. Using cross-state variation in the size of the baby-boom, I show that marriages in the pre-boom generations were more likely to divorce the bigger the relative supply of young women. This conclusion is robust to instrumenting the size of the baby-boom with WWII mobilization rates. Lastly, I construct a simple dynamic marriage market model which can generate a divorce boom caused by a baby-boom, and can account for between a fifth and a third of the rise in divorces in the 1970s.

Using the world’s longest running survey of health data, the National Health Interview Survey, Jona Schellekens shows that the decrease in mortality from cardiovascular disease in the US postponed the decline in disability from the 1970s to the 1980s, whereas better education explains the long-term downtrend in disability that started in the 1980s.