We study how the rise in cross-city joint productions (or "geographic fragmentation")-facilitated by advancements in communication technologies-shapes the spatial skill distribution in the United States. Motivated by observations that large cities became disproportionately skill intensive and that industries more likely to fragment underwent greater increases in spatial skill dispersion between 1980 and 2013, we propose a spatial equilibrium model with cross-city production and heterogeneous skills to study how geographic fragmentation affects spatial skill distribution. In addition to delivering the observed facts, the model predicts that reductions in bilateral communication frictions increase skill shares in large cities and reduce them in smaller ones. Through a novel instrumental variable approach, we provide empirical validation of the model's prediction. We then use the model to explore the quantitative consequences of counterfactual changes in internet qualities on skill redistribution and real wages.

Health insurance is a primary driver of rising medical expenditures. Economic theory suggests that insurance induces an increase in risky behaviors, but previous empirical evidence is mixed. I use a mandate in the Affordable Care Act in which contraceptives were covered at zero cost to consumers to test for unintended effects of insurance on risky sex. Leveraging mandated zero cost‐sharing for contraception and pre‐policy insured rates as a measure of treatment intensity, I provide evidence that this 2012 policy reduced fertility but caused unintended consequences: a decline in condom use and a subsequent increase in sexually transmitted infections (STIs). I discuss shortcomings of controlling for nonparallel pre‐trends using state‐trends, and I suggest an alternative to control for pre‐trends directly in the context of dose‐response difference‐in‐differences. Finally, estimates based on the 2010 dependent coverage mandate indicate health insurance provides an overall net positive effect on insurance and STI prevention.

Our healthcare industry currently relies on skilled immigrant workers. According to an analysis of the Census Bureau’s 2018 American Community Survey data by New American Economy [1], 24.3% of all healthcare workers, 48.9% of physicians, and 29.0% of registered nurses in the Houston Area for example, are immigrants.

Objective: To examine whether work-limiting disability may modify intergenerational economic mobility in the United States. Methods: Using the Panel Study of Income Dynamics, common metrics of intergenerational mobility are estimated by parent work-limiting disability. These include rank slope coefficients capturing persistence of socioeconomic status and absolute upward economic mobility capturing expected child outcomes. Results: Parent–child pairs with work-limiting disability experience 5–12 percentiles lower absolute economic mobility at the 25th percentile of parent income. More severe and/or chronic conditions have larger disparities and higher parent income is associated with smaller disparities. Women may experience larger mobility differences, while non-Hispanic black children may face a higher likelihood of parents experiencing work limitations. Conclusions: Work-limiting disability appears to modify children's economic opportunity. This contributes to the understanding of disparate access to opportunity in the United States while also identifying economic disadvantages associated with disability for subsequent generations.

This policy brief examines two employment sectors of the San Francisco Bay Area economy that have been heavily impacted the COVID-19 shut down. These two employment sectors are service workers in hospitality industry and sales workers in the retailing industry.8 These two sectors account for 1 in 8 workers of the SF Bay Area work force. As both sectors rely on faceto-face provision of services, both sectors have been largely shut down since shelter in place began on March 17, 2020. These workers clearly experience severe furlough, layoff, and unemployment. Employees in the retailing sector who continue to work in essential businesses also face potential exposure to the corona virus given the face-to-face nature of their work place through interactions with both customers and co-workers. This brief consists of two parts. The first part analyzes the socioeconomic characteristics of the workers in the two employment sectors compared to workers in other occupations and industries. Employees in the “Other”9 occupations and industries are expected to be less at risk to job loss and coronavirus exposure. This analysis is carried out at the level of the entire San Francisco Bay Area level.10 The second part examines the neighborhoods in the San Francisco Bay Area by identifying census tracts with the highest concentration of at-risk workers in the two employment sectors.

We introduce a novel test of racial assignment that has significant implications for how racial categories are popularly understood, even among the populations for whom they purportedly apply. We test whether the U.S. Census Bureau’s definition of Asian corresponds with Americans’ understanding of the category, and find a disjuncture between those groups the U.S. government assign as Asian, and those that Americans include in the category. For White, Black, Latino, and most Asian Americans, the default for Asian is East Asian. While South Asians – such as Indians and Pakistanis – classify themselves as Asian, other Americans are significantly less likely to do so, reflecting patterns of “South Asian exclusion” and “racial assignment incongruity”. College-educated, younger Americans, however, are more inclusive in who counts as Asian, indicating that despite the cultural lag, the social norms of racial assignment are mutable. We discuss how disjunctures in racial assignment bias narratives of Asian Americans.

We study the effect of return migration from the U.S. to Mexico on the economies of Mexican cities. In principle, returnees increase the local labor supply and therefore put pressure on wages and employment rates of locals. However, having worked in the technologically more advanced US economy, they may also possess skills that complement the skills of local workers or even bring in new organizational and technological know-how that leads to productivity improvements in Mexico. Using an instrument based on involuntary return migration due to deportation by US authorities, we find evidence in support of both effects. Returnees affect wages of locals in different ways: whereas workers who share the returnees’ occupations experience a fall in wages, workers in other occupations see their wages rise. However, the latter, positive, effect is easily overlooked, because it is highly localized: it only affects coworkers within the same city-industry cell. Moreover, both, positive and negative, wage effects are transitory and eventually disappear. In contrast, by raising the employment levels of the industry in which they find jobs, returnees permanently alter a city’s industry composition.

The number of student-parents in higher education is increasing substantially, yet their graduation rates continue to decline. I focus on the barriers and privileges that student-parents with different socioeconomic backgrounds experience through the theoretical framework of intersectionality. I examine the lived experiences of Rio Hondo and Santa Monica community college student-parents using detailed interviews that asked open-ended questions about their educational experiences. Their counterstories exposed their perceptions of both institutional barriers and privileges. This study illuminates how local forms of racial disparities have been the underlying reasons why student-parents in Los Angeles lack institutional resources. Such disadvantages, especially the lack of awareness about resources, hinders them in postsecondary pathways. Still, student-parents share motives to push through structural barriers and remain resilient during their educational trajectory. Policymakers, college administrators, and faculty could practice equity and inclusion for student-parents by offering services that specifically address their needs as parents and those that arise from racial inequality. I suggest this could be implemented by providing more available times for students to access tutoring, counseling, and childcare services.

Studies document large differences in the amount of time mothers spend in childcare by maternal education, even when controlling for characteristics such as income, employment hours, and work schedules. One possible explanation for this observed difference is that highly educated mothers find time in childcare to be more enjoyable. To inform this hypothesis, we examine education-based differences in mothers’ average feelings during their time in childcare using pooled data from the 2010, 2012, and 2013 Well-being Modules of the American Time Use Survey. Among all mothers, spending time in childcare is associated with higher positive feelings than is spending time in other activities. However, highly educated mothers do not enjoy their time in childcare more than less-educated mothers. Findings are robust to controls for mother fixed effects.

Joblessness is highly seasonal. To analyze how households adapt to seasonal joblessness, we introduce a measure of seasonal work interruptions premised on the idea that a seasonal worker will tend to exit employment around the same time each year. We show that an excess share of prime-age US workers experience recurrent separations spaced exactly 12 months apart. These separations coincide with aggregate seasonal downturns and are concentrated in seasonally volatile industries. Examining workers most prone to seasonal work interruptions, we find that these workers incur large earnings losses during the off-season. Lost earnings are (i) driven mainly by repeated separations from the same employer; (ii) not recouped at other firms; (iii) partly offset by unemployment benefits; and (iv) amplified by concurrent drops in partners' earnings. On net, household income falls by about 80 cents for each $1 lost in own earnings.

The phrase “affordable housing” is so ubiquitous, and applied to so many different types of homes, that it sometimes feels like it’s lost any clear meaning. When we say we want to build and preserve affordable housing, what do we mean? This primer will help policymakers, public officials, advocates, and other stakeholders answer this question — to better understand the many different types of affordable housing, what they accomplish, how they’re regulated, and who they serve. In turn, we hope that knowledge will be used to develop better-informed, more effective housing policy that improves affordability and protects against displacement. So what is “affordable housing”? Virtually everyone agrees that homes built with public funds and reserved for low income households qualify as affordable housing. In privately financed developments, units set aside for low income (and perhaps even middle-class) residents — usually mandated by density bonus or inclusionary zoning programs — are affordable housing, too. But what about rent-controlled housing, where rents can be high or low but only increase by a small percentage each year? Or micro-units, where total rents are low but per-square-foot rents are high? In less expensive cities should a new, unsubsidized, for-profit townhome sold for $250,000 be considered “affordable,” or should the term be reserved only for below-market housing? What distinguishes low income housing from extremely low income housing? And how about workforce housing? What even is workforce housing? In this primer we will discuss five (5) affordable housing categories, including details about who builds them, how they’re built, who pays, and how rents are set and can change over time. We will also review six (6) affordability levels — that is, the restrictions on household income and other conditions that determine who can reside in a given affordable unit and how much they pay.

This chapter explores Open Data through a historic lens, reviewing public history projects in the United States that are visualising historic mechanisms for maintaining racial segregation in U.S. cities during the first half of the twentieth century. The layering of data (housing covenants, demographic data, historic maps) reveals the relationship of these mechanisms—specifically racial covenants and federal government “redlining” maps—to current inequality and segregation. These projects not only serve to increase the transparency of private and governmental housing policies that have served to racially segregate American cities but also demonstrate how historic data, provided openly to the public, can inform contemporary discussions around equitable urban development.

Suicide is one of the leading causes of death in the United States. The rise in suicide rates is contributing to the recently observed decline in life expectancy. While previous research identified a solid association between economic strain and suicide, little attention has been paid to how specific welfare policies that are designed to alleviate economic strain may influence suicide rates. There is a growing body of research that is using an institutional approach to demonstrate the role of welfare-state policies in the distribution of health. However, this perspective has not been applied yet to the investigation of suicide. In this study, I combine these approaches to analyze the association between two specific policies, Supplemental Nutrition Assistance Program (SNAP) and Earned Income Tax Credit (EITC), and overall and gender-specific suicide rates across the 50 U.S. states between 2000 and 2015. I estimate two-way fixed-effects longitudinal models and find evidence of a robust association between one of these policies – SNAP – and overall and male suicide. After adjusting for a number of confounding factors, higher participation in SNAP is associated with lower overall and male suicide rates. Increasing SNAP participation by one standard deviation (4.5% of the state population) during the study period could have saved the lives of approximately 31,600 people overall and 24,800 men.

Houston, Texas is a major U.S. urban and industrial area where poor air quality is unevenly distributed and a disproportionate share is located in low-income, non-white, and Hispanic neighborhoods. We have traditionally lacked city-wide observations to fully describe these spatial heterogeneities in Houston and in cities globally, especially for reactive gases like nitrogen dioxide (NO2). Here, we analyze novel high-spatial-resolution (250 m × 500 m) NO2 vertical columns measured by the NASA GCAS airborne spectrometer as part of the September-2013 NASA DISCOVER-AQ mission and discuss differences in population-weighted NO2 at the census-tract level. Based on the average of 35 repeated flight circuits, we find 37 ± 6% higher NO2 for non-whites and Hispanics living in low-income tracts (LIN) compared to whites living in high-income tracts (HIW) and report NO2 disparities separately by race ethnicity (11-32%) and poverty status (15-28%). We observe substantial time-of-day and day-to-day variability in LIN-HIW NO2 differences (and in other metrics) driven by the greater prevalence of NOx (NO + NO2) emission sources in low-income, non-white, and Hispanic neighborhoods. We evaluate measurements from the recently launched satellite sensor TROPOMI (3.5 km × 7 km at nadir), averaged to 0.01° × 0.01° using physics-based oversampling, and demonstrate that TROPOMI resolves similar relative, but not absolute, tract-level differences compared to GCAS. We utilize the high-resolution FIVE and NEI NOx inventories, plus one year of TROPOMI weekday-weekend variability, to attribute tract-level NO2 disparities to industrial sources and heavy-duty diesel trucking. We show that GCAS and TROPOMI spatial patterns correspond to the surface patterns measured using aircraft profiling and surface monitors. We discuss opportunities for satellite remote sensing to inform decision making in cities generally.

Introduction. Student active commuting to school is an important component to student achievement and student health, yet this form of physical activity has significantly declined in the U.S. Distance between the school and student residence is often reported as a barrier for student walking, thereby increasing street and trail connectivity between and within residential developments and schools could foster student walking. The purpose of this study is to evaluate the potential benefits of increased thoroughfare connectivity on student walking within school walking zones. Methods. This study conducts a cost-benefit analysis of increased thoroughfare connectivity around elementary and middle schools in a U.S. school system that serves sixty thousand students. Benefits, which include the increased time of physical activity from student walking and the potential cost-savings to a school system if they had fewer students to bus to school, are compared to the financial costs of the new connections. Advanced network optimization techniques were applied to several suburban and rural schools from a representative the school system to locate the optimal new thoroughfare connections that maximize student walking to a school and minimize the length of the new thoroughfare. Results. Results from this case study showed that short and inexpensive new thoroughfares could increase the potential number of student active commuters and provide a significant increase of physical activity for those potential student walkers. Conclusions. This work can foster the integration of student walking and student health in residential planning decisions around schools.

Immigration policies have been increasingly targeting the undocumented population in the United States, potentially elevating employer prejudice against this group and inducing labor market discrimination. Using ACS data and reports from ICE, I test whether Secure Communities (SC), a deportation program initiated in 2008, had spillover effects on labor market outcomes of Hispanic male citizens and legal immigrants. Using a difference-in- difference regression, I estimate the effect of SC between the pre-treatment period (2007) and the post-treatment period (2010) on annual earnings of my treatment group. The latter consists of Hispanic male citizens and legal immigrants working in SC counties, and my control group consists of Hispanic male citizens and legal immigrants working in non-SC counties. I consider any negative change in wages or annual earnings as evidence in support of labor market discrimination. I find that Hispanic men working in treated counties witnessed a decline in their annual earnings of 3.4% in magnitude as a result of the implementation of SC. I find no significant effect of SC on employment of Hispanic men, and no significant gender or border (states that border Mexico versus those that do not) differences in my treatment group.

During the 1910s, twelve U.S. states passed and implemented the country's first minimum-wage laws. They covered only female employees, often in a subset of industries. We study the impact of this regulation using full-count Census data. Our identification strategy compares county-industry trends in county-pairs that straddle state borders. We find that female employment decreased by at least by 3.1% at the county-industry level. Across counties, we find that the own-wage elasticity of labor demand varies from around-1.6 to 0.8 as a function of the local cross-industry concentration. Affected female workers switch industries or drop out of the labor force. The latter channel is driven exclusively by married women. We document a rise in male labor demand, and we investigate the channels of substitutions between men and women. While on average men and women are gross substitutes, we find evidence that the margin of substitution is driven by the replacement of women in low-rank occupations with men in middle-or high-rank occupations.

This chapter concerns postfascist suburbanism, in which policies are manifested in ethnic cleansing. Grounded in white anxiety over demographic displacement and a mythologized past, Trumpian fascism, or at least the 21st century form of reactionary populism that it has assumed, is the latest manifestation of racialized neoliberalism. The authors examine how this revanchism plays out at the local scale through a case study of Marietta, Georgia, where rapid population growth was accompanied by growing economic distress, where ethnic cleansing took the form of eliminating “urban blight” in areas populated by African Americans.

Background: Individuals with serious psychological distress (SPD) are significantly more likely to be uninsured or covered by Medicaid, and less likely to have private insurance than individuals with no psychological distress (NPD). They are in worse health and have greater health care needs relative to individuals with NPD, and they are more likely to have difficulties accessing all types of health care. The Affordable Care Act (ACA) sought to improve access to health care primarily through expanding health insurance coverage, which individuals with SPD often lack. Few studies have examined changes in health insurance status, health services use and access to health care among the SPD population during the time of ACA implementation. Specific aims: The goal of this dissertation is to observe changes to health insurance, health services use, and barriers to health care among individuals with serious psychological distress (SPD) during the time frame of the implementation of the Affordable Care Act (ACA) using the Medical Expenditure Panel Survey. This study aims to answer the following questions: 1a.) “How did health insurance coverage among individuals with SPD shift during ACA implementation?” 1b.) “Did health insurance coverage among individuals with mild-to-moderate psychological distress (MMPD) and no psychological distress (NPD) shift in a similar manner?” 2.) “How did the use of health services shift during ACA implementation among those with SPD and NPD?” 3a.) “How did need for health care and barriers to access of health care change during ACA implementation for individuals with SPD?” 3b.) “Did individuals with MMPD and NPD observe similar changes?”. Methods: Mental illness is measured using the Kessler 6 (K6) scale of non-specific psychological distress scale. A score of ≥13 is severe psychological distress (SPD), 12 to 8 is mild to moderate psychological distress (MMPD), and ≤7 is no psychological distress (NPD). Pooled cross-sectional data from the 2011-2016 Integrated Public Use Microdata Series IPUMS Medical Expenditure Panel Survey is analyzed. Individuals included in the sample had a score on the K6, an income ≤399% of the federal poverty level and are between the ages of 27 and 64. Descriptive statistics were conducted using 2-sided t-tests for differences in proportions in categorical variables, and adjusted Wald tests for continuous variables. To address study aims 1a & 1b, multinomial probit regression was performed to assess differences in the proportion of individuals in each insurance category in each year of ACA implementation. To address specific aim 2, four health service outcomes were assessed in each year of ACA implementation (2011- 2016) including emergency room use, hospitalizations, outpatient/office-based visits, and prescriptions. Analysis of health service use was conducted using a two-part hurdle model, where the first part of the model predicted the likelihood of utilizing each type of health service (i.e. emergency room, hospital discharges, outpatient/office-based visits or prescriptions), and the second part predicted the amount of health service use conditional upon any utilization. The combined model predicted expected utilization based on the likelihood of service use and the amount. To address specific aims 3a and 3b, access to health care outcomes include the need for health care, the unmet need for health care, and having a usual place of care. The probability of accessing health care in each year during ACA implementation (2012-2016) was compared to the reference year (2011) within each psychological distress group using logistic regression models, and marginal effects were reported. Results: Individuals with SPD did not see significant changes in enrollment in private insurance in any year relative to 2011, although they did observe a 3 and 3.4 percentage point increase in enrollment in private insurance in 2014 and 2015, respectively. Individuals with SPD do not have a higher likelihood of enrollment in Medicaid until 2015 (8.6 percentage points, p<0.001) relative to 2011 and this remains elevated in 2016 (9 percentage points, p<0.001). However, the uninsured rate for these individuals began to decline in 2014 and was 14.9 percentage points lower relative to 2011 by 2016 for those with SPD (p<0.001). Among individuals with SPD, the likelihood of having an ER visit is higher in the 2014-2016 time period than in 2011, with a 7.7 percentage point increase by 2016 (p<0.05). Similarly, the likelihood of having a prescription medication is higher in 2015 than in 2011 (4 percentage points, p<0.05). The number of hospital discharges for individuals with SPD, conditioned upon having any, increased in 2016 relative to 2011 (0.6 discharges, p<0.01). Outpatient/office-based visits, conditioned on having any, increased in 2014 & 2015 relative to 2011 (2014: 2.6 visits, p<0.1; 2015: 2.5 visits, p<0.1). Among individuals with SPD, the expected utilization is statistically significant and higher for hospital discharges in 2016 (0.12 discharges, p<0.1), outpatient/office-based visits in 2014 (2.4 visits, p<0.05) & 2015 (2.6 visits, p<0.1), and prescriptions in 2015 (4.4 prescriptions, p<0.1) relative to 2011. Each year during the time frame of ACA implementation (2012-2016) is associated with a lower probability of needing health care relative to 2011 for individuals with SPD, although this association is only statistically significant in 2013 (-6.6 percentage points, p<0.05). The unmet need for health care seems to have increased during ACA implementation for individuals with SPD. They experience a significant increased unmet need in 2013 (5.8 percentage points, p<0.05) and 2015 (5.1 percentage points, p<0.1). Not having a usual place of care is generally higher in each year relative to 2011. For individuals with SPD, there are only statistically significant increases in not having a usual place of care in 2012 (4.2 percentage points, p<0.1) and 2013 (8.1 percentage points, p<0.01).

The phrase “affordable housing” is so ubiquitous, and applied to so many different types of homes, that it sometimes feels like it’s lost any clear meaning. When we say we want to build and preserve affordable housing, what do we mean? This primer will help policymakers, public officials, advocates, and other stakeholders answer this question — to better understand the many different types of affordable housing, what they accomplish, how they’re regulated, and who they serve. In turn, we hope that knowledge will be used to develop better-informed, more effective housing policy that improves affordability and protects against displacement. So what is “affordable housing”? Virtually everyone agrees that homes built with public funds and reserved for low income households qualify as affordable housing. In privately financed developments, units set aside for low income (and perhaps even middle-class) residents — usually mandated by density bonus or inclusionary zoning programs — are affordable housing, too. But what about rent-controlled housing, where rents can be high or low but only increase by a small percentage each year? Or micro-units, where total rents are low but per-square-foot rents are high? In less expensive cities should a new, unsubsidized, for-profit townhome sold for $250,000 be considered “affordable,” or should the term be reserved only for below-market housing? What distinguishes low income housing from extremely low income housing? And how about workforce housing? What even is workforce housing? In this primer we will discuss five (5) affordable housing categories, including details about who builds them, how they’re built, who pays, and how rents are set and can change over time. We will also review six (6) affordability levels — that is, the restrictions on household income and other conditions that determine who can reside in a given affordable unit and how much they pay