The geographic concentration and diffusion of crime and deviancy are longstanding criminological inquiries, yet few studies have examined how certain illicit behaviors transcend neighborhood borders and connect neighborhoods in patterns of crime and deviancy. A structural neighborhood interdependence may account for the enduring nature and spread of crime, making it critical to understand how neighborhoods are connected in crime patterns to guide crime prevention and disruption efforts. This study examines neighborhood interdependence through the case of repeat buyers of commercial sex in illicit massage businesses in a metropolitan city in the United States. By frequenting venues for illicit commercial sex in multiple neighborhoods, buyers create inter-neighborhood connections through which the demand for an illicit market can spread across neighborhoods. Using online review data about buyers of commercial sex, this study analyzes this neighborhood interdependence as a network comprised of nodes (“neighborhoods”) and edges (“connections between neighborhoods”). Exponential random graph models were used to analyze how characteristics of neighborhoods, the space between neighborhoods, and the overall network of neighborhoods explain inter-neighborhood connectivity in an illicit market for commercial sex. The implications for research, policy, and practice will be discussed.

The “broken windows” hypothesis has led to millions of citizen/police encounters through aggressive enforcement of minor infractions. Despite extensive research on the relationship between broken windows and crime, there is less research on whether police officers focus on areas with broken windows, and the few studies that exist have mixed findings. Another set of studies finds high levels of policing in gentrifying neighborhoods. On the one hand, then, studies show there is more policing in neighborhoods with visible signs of disorder as police departments that adhere to the tenets of broken windows policing would be likely to send officers to patrol areas with broken windows, litter, and unkempt lawns in an effort to prevent crime in these areas. On the other hand, as high-income people move into these neighborhoods, the signs of disorder should dissipate. This raises the question: Is there more policing in neighborhoods with signs of physical disorder or in neighborhoods with signs of reinvestment? We measure this using three data sources: 1) an original housing survey using Google Street View that evaluates the level of physical disorder; 2) geocoded data from the Washington, DC Metropolitan Police Department on stop and frisks; and 3) Census and ACS data on population characteristics. These data allow us to answer our research questions: Are residents more likely to be stopped and frisked in neighborhoods with high levels of physical disorder? Or, conversely, are residents more likely to be stopped and frisked in neighborhoods experiencing an in-migration of middle-class residents?

Each individual in society experiences an evolution of their income during their lifetime. Macroscopically, this dynamic creates a statistical relationship between age and income for each society. In this study, we investigate income distribution and its relationship with age and identify a stable joint distribution function for age and income within the United Kingdom and the United States. We demonstrate a flexible calibration methodology using panel and population surveys and capture the characteristic differences between the UK and the US populations. The model here presented can be utilised for forecasting income and planning pensions.

Recent studies estimate that the COVID-19 pandemic significantly increases reports of domestic violence in several countries. Using mobile device tracking data, city-level unemployment data, and new data on labor market conditions caused by the coronavirus pandemic, we isolate the effects of unemployment and staying at home on incidents of domestic violence. We find that unemployment decreases domestic violence after controlling for the degree to which people stay at home. We also provide evidence that staying at home increases domestic violence. However, we find that the effects of unemployment and staying at home are concentrated right after an initial shock from mid-March to mid-June 2020. Finally, we find that some labor market conditions linked to COVID-19, such as being prevented from looking for work due to the pandemic, decrease domestic violence, and these labor market effects are often gendered.

This study finds that location matters more for children of parents with low educational attainment than for children of more educated parents. Specifically, children of parents without a high school diploma are statistically more likely to be enrolled in high schools or colleges in metropolitan statistical areas (MSAs) where the college graduate share is higher. The statistical relationship between a child's school enrollment and the MSA's college graduate share becomes weaker as their parents’ educational attainment increases. We also find that the least educated households are significantly less likely to be homeowners and are more likely to pay greater housing costs as a share of income in cities with higher college graduate shares, indicating that these households are paying a high price to live in high-skilled cities. Our results imply that the increasing lack of housing affordability in high-skilled cities makes it more difficult for households with less educational attainment to stay in or move to these places, contributing to intergenerational education inequality.

Monitoring the well-being of children and adolescents is essential for improving overall population health. However, with only a few exceptions, direct measures of well-being are not currently collected at scale in the United States. Multidimensional indices of outcome indicators related to well-being have been proposed as an alternative, but existing indices have several weaknesses. This dissertation implements a novel methodology to derive an improved index of the outcome indicators of child and adolescent well-being that can be applied to existing population data. Using a nationally representative longitudinal panel, model selection and regression techniques are implemented to estimate the relationship between a collection of standard outcome indicators of well-being with several subjective scales collected directly from children and adolescents. This process results in an index methodology based on their actual lived experiences, making it a more child-centric measure. Within the panel, higher scores on the index are associated with improved health and higher earnings in young adulthood. When iii subsequently applying the methodology to population macrodata from 2000 to 2019, we find that the outcome indicators of child and adolescent well-being, as measured by the index, improved consistently throughout the past two decades. This overall advance was accompanied by some convergence in disparities by geography and race/ethnicity, but significant inequities remain. However, the progress exhibited by the outcome indicators of well-being contrasts sharply with recent declines in other measures of child and adolescent mental health. This contradiction suggests that the outcome indicators, which at one point tracked reasonably well alongside the subjective well-being of children and adolescents, are no longer performing as expected. Researchers, policymakers, advocates, and practitioners should therefore collectively recommit to expanding population health monitoring systems to better capture the most essential aspects of child and adolescent well-being.

Why do US states specialize in different sectors? We document that employment specialization is highly persistent, which suggests that specialization may deviate from natural advantage, and reallocation could increase aggregate output. We develop a quantitative spatial model in which workers move across state-by-sector labor markets in response to exogenous changes in local fundamentals and endogenous agglomeration, as well as mobility frictions and labor market-specific idiosyncratic skills. We quantify the model with historical Census microdata that tracks workers’ joint regional and sectoral mobility, which yield novel estimates of regional and sectoral mobility frictions as well as new evidence that workers carry both state- and sector-specific skills. Mobility frictions play a substantial role in the persistence of specialization. Although spatial differences in productivity within a sector are small, the ability of individual workers to reallocate across labor markets is valuable. Migration costs are the main barrier to workers’ reallocation; spatial reallocation facilitates better matching not only across states but also across sectors.

Immigrants tend to display more favorable health outcomes than native-born co-ethnics. At the same time, they face considerable employment instability. It is unclear whether immigrants’ job conditions may compromise their health advantage. Using U.S. National Health Interview Survey data, this study shows that the experience of unemployment reduces immigrants’ health advantage, but unemployed foreign-born Blacks, White women, and Asian women still have lower mortality rates than their native-born employed counterparts. Overall, unemployment is less detrimental to immigrants than to natives, and immigrants’ “survival advantage after unemployment” persists as their duration of residence extends. We further find substantial heterogeneity in the unemployment effect within immigrants. Asian immigrants display a much sharper gender difference in the mortality consequence of unemployment than other immigrants. Asian men's worse general health and substantially higher smoking rate, especially among the unemployed, lead them to fare much worse than Asian women following unemployment.

Under the Americans with Disabilities Act (ADA), workers with disabilities have the legal right to reasonable workplace accommodations provided by employers. Because this legal right is unique to disabled workers, these workers could, in theory, enjoy greater access to the types of accommodations that are desirable to all workers including the ability to work from home, to work flexible hours, and to take leave. This Article compares access to these accommodations, which have become increasingly desirable during the COVID-19 pandemic, between disabled workers and nondisabled workers. Using 2017-2018 data from the American Time Use Survey's Leave and Job Flexibilities Module, I find that disabled workers report far less access to these pandemic-relevant accommodations than do nondisabled workers. I further present evidence that disabled workers' lower rates of access to pandemic-relevant accommodations are due, in part, to occupational segregation. Because disabled workers are more likely to work in jobs that are not amenable to working from home, working flexible hours, and taking temporary leave, the results raise concerns about many disabled workers' ability to maintain their employment during the pandemic. The results further highlight the inherent weaknesses of the ADA and the need for additional supporting legislation including short-term insurance and educational funding programs for disabled workers.

Birth rates provide useful information on population growth, and an above-replacement birth rate is indicative of stability. However, previous research has found that birth rates in industrialized societies such as the U.S have been decreasing in recent years. We use data from the American Economic Association to analyze this by using graphs and tables to observe the trend in birth rates of different demographics, using R (R Core Team 2020) and other packages. We also observe the trends behind changing economic and cultural factors that could affect the birth rates. We find that birth rates of young women of different races have been on a steep decline over the past 20 years, and factors that are known to decrease birth rates have increased. This report shows that the decline in birth rates is the result of cultural and economic changes between two generations of women. While this indicates that the U.S has become more culturally liberated, the declining birth rates showcases systemic effects of the worsening economy and increasing costs on the average American woman.

Background: Physician time is a valuable yet finite resource. Whether such time is apportioned equitably among population subgroups, and how the provision of that time has changed in recent decades, is unclear. Objective: To investigate trends and racial/ethnic disparities in the receipt of annual face time with physicians in the USA. Design: Repeated cross-sectional. Setting: National Ambulatory Medical Care Survey, 1979–1981, 1985, 1989–2016, 2018. Participants: Office-based physicians. Measures: Exposures included race/ethnicity (White, Black, and Hispanic); age (<18, 18–64, and 65+); and survey year. Our main outcome was patients’ annual visit face time with a physician; secondary outcomes include annual visit rates and mean visit duration. Results: Our sample included n=1,108,835 patient visits. From 1979 to 2018, annual outpatient physician face time per capita rose from 40.0 to 60.4 min, an increase driven by a rise in mean visit length and not in the number of visits. However, since 2005, mean annual face time with a primary care physician has fallen, a decline offset by rising time with specialists. Face time provided per physician changed little given growth in the physician workforce. A racial/ethnic gap in physician visit time present at the beginning of the study period widened over time. In 2014–2018, White individuals received 70.0 min of physician face time per year, vs. 52.4 among Black and 53.0 among Hispanic individuals. This disparity was driven by differences in visit rates, not mean visit length, and in the provision of specialist but not primary care. Limitation: Self-reported visit length. Conclusion: Americans’ annual face time with office-based physicians rose for three decades after 1979, yet is still allocated inequitably, particularly by specialists; meanwhile, time spent by Americans with primary care physicians is falling. These trends and disparities may adversely affect patient outcomes. Policy change is needed to assure better allocation of this resource.

I document and investigate life-cycle profiles of skill premiums across cohorts. My empirical analysis shows that younger cohorts have steeper growth in the skill premium before age 40 but flatter growth after 40. I use a human capital investment model to account for the cross-cohort variation in skill premium profiles. The results indicate that the flattened growth after age 40 is caused by the drop in human capital (of high-skill workers) near the end of the life cycle. Besides, the magnitude of life-cycle growth in the skill premium is mainly driven by the relative skill price, which is the log ratio of wage rates between high-skill workers and low-skill workers.

When should policies to encourage new types of products use supply-side tools, like regulations and mandates, and when should they use demand-side tools like consumer incentives? When prices are set nationally but policy varies by state, supply-side and demand-side tools are no longer equivalent. We study an important state-level supply-side policy in the early electric vehicle industry: the zero-emission vehicle mandate in California and nine other states. Focusing on the 2009–17 period, we examine two channels for policy effects: imperfect competition and endogenous product entry. Using a structural model of new vehicle pricing, demand, and product entry, we compare the mandate to a counterfactual demand-side policy that instead uses a consumer subsidy and tax. Holding fixed the regulator’s stated target, electric vehicle sales in regulated states, the demand-side policy creates a weaker incentive for socially beneficial product entry and generates lower consumer and total surplus. When fewer products are introduced, producers avoid entry costs, but forego long-run benefits of entry.

The nonprofit Urban Institute is a leading research organization dedicated to developing evidence-based insights that improve people's lives and strengthen communities. For 50 years, Urban has been the trusted source for rigorous analysis of complex social and economic issues; strategic advice to policymakers, philanthropists, and practitioners; and new, promising ideas that expand opportunities for all. Our work inspires effective decisions that advance fairness and enhance the well-being of people and places.

This report provides a closer look at the well-being of the early care and education (ECE) workforce in California, using data collected by the Center for the Study of Child Care Employment (CSCCE) through the 2020 California Early Care and Education Workforce Study. For decades, low levels of public investment in this sector have kept the ECE workforce—largely women of color and immigrant women—in a grim financial bind. During the first year of the pandemic, the majority of early educators continued to work in person—risking their health and that of their families—while K-12 schools closed for distance learning. This report reveals new details on the economic realities of life as an early educator during the COVID-19 public health crisis.

This report examines the socioeconomic trends and differences among not only the four major racial and ethnic groups in the country (non-Hispanic whites, non-Hispanic blacks, Latinos, and Asians) but also within the Latino population from 1990 to 2017. Methods: This report uses the American Community Survey PUMS (Public Use Microdata Series) data for all years released by the Census Bureau and reorganized for public use by the Minnesota Population Center, University of Minnesota, IPUMSusa, (https://usa.ipums.org/usa/index.shtml). See Public Use Microdata Series Steven Ruggles, J. Trent Alexander, Katie Genadek, Ronald Goeken, Matthew B. Schroeder, and Matthew Sobek. Integrated Public Use Microdata Series: Version 5.0 [Machine-readable database]. Minneapolis: University of Minnesota, 2017. Discussion: The four major racial and ethnic groups within the Latino population present a high variety. The majority of Latinos in the U.S. identify as white (65% in 2017), followed by mixed-race (31.8%); Afro-Latinos (2.2%) and Indigenous Latinos (1.0%) are very few in comparison. Latinos are the youngest racial and ethnic group in the country, but it is Afro-Latinos who are the youngest of them—in 2017, 20.6% of Afro-Latinos were aged 0-9 years old. In terms of education, high-school non-completion decreased significantly between 1990 and 2017 among Latinos in general. A similar decreasing trend was found in terms of the lowest income strata. Finally, while the foreign-born white and mixed-race Latino population decreased slightly in this period (about one percentage point difference), it was the foreign-born Afro-Latinos who experienced the largest drop, from 38.2% to 26.4%. In contrast, the proportion of Indigenous Latinos grew substantially over this period, from 15.4% in 1990 to 27.6% in 2017.

Court ordered desegregation plans were implemented in hundreds of US school districts nationwide from the 1960s through the 1980s, and were arguably the most substantive national attempt to improve educational access for African American children in modern American history. Using large Census samples that are linked to Social Security records containing county of birth, we implement event studies that estimate the long run effects of exposure to desegregation orders on human capital and labor market outcomes. We find that African Americans who were relatively young when a desegregation order was implemented in their county of birth, and therefore had more exposure to integrated schools, experienced large improvements in adult human capital and labor market outcomes relative to Blacks who were older when a court order was locally implemented. There are no comparable changes in outcomes among whites in counties undergoing an order, or among Blacks who were beyond school ages when a local order was implemented. These effects are strongly concentrated in the South, with largely null findings in other regions. Our data and methodology provide the most comprehensive national assessment to date on the impacts of court ordered desegregation, and strongly indicate that these policies were in fact highly effective at improving the long run socioeconomic outcomes of many Black students.

Asian Americans have the highest median household income of the major racial and ethnic groups in the US. But the story of Asian Americans and Pacific Islanders and the US economy is more complicated than might be apparent at first. This article challenges the model minority myth that hides significant numbers within the AAPI population with low incomes that could benefit from government assistance.

Immigrants in economies with a dominant native language exhibit substantial heterogeneities in language acquisition of the majority language. We model partial equilibrium language acquisition as an equilibrium phenomenon. We consider an environment where heterogeneous agents from various minority groups choose whether to acquire a majority language fully, partially, or not at all. Different acquisition decisions confer different communicative benefits and incur different costs. We offer an equilibrium characterization of language acquisition strategies and find that partial acquisition can arise as an equilibrium behavior. We also show that a language equilibrium may exhibit insufficient learning relative to the social optimum. In addition, we provide a local stability analysis of steady state language equilibria. Finally, we discuss econometric implementation of the language acquisition model and establish identification conditions.

The surge in marketization-the purchase of services from the market that would otherwise be produced at home-in the US has been attributed to decreases in the marginal cost of marketable services through increased productivity. In this paper, I show that low-skilled labor is the largest input to the production of these personal services, and thus low-skilled wage movements contribute to marginal cost declines. To illustrate the role that the rising skill premium has played in marketization, I build a model to study the economic forces that shape households' resource allocation in a heterogeneous skill economy. In contrast to the findings in the representative household models, my quantitative exercise shows that changes to the wage structure, rather than a larger growth of productivity of the market service sector relative to the home sector, are the predominant drivers of marketization. Thus, the forces that change the skill premium can entirely account for trends in marketization. This new mechanism suggests that policies and labor market institutions that are responsible for the trajectory of the skill premium can also affect the extent of marketization.