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Research has made clear that neighborhoods impact the health and well-being of their residents. A related strand of research shows that neighborhood disadvantage is geographically clustered. Because the neighborhoods of low-income and minority populations tend to be more disadvantaged, neighborhood conditions help explain racial and socioeconomic inequalities. These strands of research restrict processes of neighborhood influence to operate only within and between geographically contiguous neighbors. However, we are underestimating the role of neighborhood conditions in explaining inequality if disadvantage extends beyond the residential and extralocal environments into a network of neighborhoods spanning the urban landscape based on where residents move within a city. I use anonymized mobile phone data to measure exposure to air pollution among residents of poor and minority neighborhoods in 88 of the most populous US cities. I find that residents from minority and poor neighborhoods travel to neighborhoods that have greater air pollution levels than the neighborhoods that residents from White and nonpoor neighborhoods visit. Hispanic neighborhoods exhibit the greatest overall pollution burden, Black/White and Asian/White disparities are greatest at the network than residential scale, and the socioeconomic advantage of lower risk exposure is highest for residents from White neighborhoods. These inequalities are notable given recent declines in segregation and air pollution levels in American cities.

The Sustainable Development Goals (SDGs) represent a central framework for guiding sustainable urban development. However, it is not clear how and where SDG 11 (Sustainable Cities and Communities) is being implemented, and how such implementation might be improved. We investigate this subject by analyzing United Nations (UN) SDG Good Practices data from 2018 to 2021, using content analysis, classification, and descriptive statistics. The resulting analysis and classification is new in this field. We applied five criteria to the 336 SDG 11 responses: (1) geography; (2) actors; (3) progress toward targets; (4) areas of implementation; and (5) scale of action. Overall, 86 of the 193 countries that adopted the 2030 Agenda submitted at least one SDG 11 good practice. Thirty-three countries contributed 73.8% of the total, and most developing countries did not make submissions. A very small number of responses (between 2.6 and 9.1%) addressed equity-related targets. Good practices from developed countries were usually more technology-oriented and system-forming; developing countries typically focused on issues of day-to-day concern. This analysis points to the need for better and more systematic reporting on SDG 11 implementation, a more active public sector role in SDG implementation and reporting, more focus on dimensions related to social equity, and better formulation of urban sustainability targets and indicators.

Ridehailing services such as Uber have been promoted as viable interventions for curbing alcohol-involved driving fatalities. However, evidence of ridehailing's impact has been mixed, with some studies finding no association but others finding either an increase or a decrease in fatalities. We contribute to this literature by examining more recent years of data, which capture a period during which Uber ridership has grown substantially and alcohol-involved fatalities have increased. Furthermore, we test whether the relationship between Uber availability and traffic fatalities depends on local characteristics. We employ multivariate regression models to test the association between Uber availability and total, alcohol-involved, and weekend and holiday-specific traffic fatalities in the 100 most populated metropolitan areas in the United States between 2009 and 2017. We find that Uber availability is not associated with changes in total, alcohol-involved, and weekend and holiday-specific traffic fatalities in aggregate, yet it is associated with increased traffic fatalities in urban, densely populated counties.

Ride-hailing businesses, including Uber and Lyft, have reshaped road traffic since they first began operating in the United States approximately a decade ago. It follows that ride-hailing may also alter the incidence and distribution of road traffic crash injuries and deaths. The available evidence relating ride-hailing to crashes is critically reviewed in this article. We present a theoretical model that synthesizes the hypothesized mechanisms, and we identify common methodological challenges and suggest priorities for future research. Mixed results have been reported for the overall incidence of road traffic crash injuries and deaths, likely due to heterogeneous impacts on vehicular traffic flow (e.g., increasing the volume of vehicles); on vehicle-, person-, and event-level characteristics (e.g., reducing alcohol-impaired driver crashes); on road-user types (e.g., increasing pedestrian crashes); and on environmental conditions (e.g., reducing crashes most substantially where public transit access is poorest). The lack of a well-developed theory of human mobility and methodological challenges that are common to many ecological studies impede exploration of these sources of moderation. Innovative solutions are required to explicate ride-hailing's heterogeneous impacts, to guide policy that can take advantage of the public health benefits of ride-hailing, and to ensure that research keeps pace with technological advances that continue to reshape road traffic use.

Exposure to heat is a growing public health concern as climate change accelerates worldwide. Different socioeconomic and racial groups often face unequal exposure to heat as well as increased heat-related sickness, mortality, and energy costs. We provide new insight into thermal inequities by analyzing 20 Southwestern U.S. metropolitan regions at the census block group scale for three temperature scenarios (average summer heat, extreme summer heat, and average summer nighttime heat). We first compared average temperatures for top and bottom decile block groups according to demographic variables. Then we used spatial regression models to investigate the extent to which exposure to heat (measured by land surface temperature) varies according to income and race. Large thermal inequities exist within all the regions studied. On average, the poorest 10% of neighborhoods in an urban region were 2.2 °C (4 °F) hotter than the wealthiest 10% on both extreme heat days and average summer days. The difference was as high as 3.3-3.7 °C (6-7 °F) in California metro areas such as Palm Springs and the Inland Empire. A similar pattern held for Latinx neighborhoods. Temperature disparities at night were much smaller (usually ~1 °F). Disparities for Black neighborhoods were also lower, perhaps because Black populations are small in most of these cities. California urban regions show stronger thermal disparities than those in other Southwestern states, perhaps because inexpensive water has led to more extensive vegetation in affluent neighborhoods. Our findings provide new details about urban thermal inequities and reinforce the need for programs to reduce the disproportionate heat experienced by disadvantaged communities.

Exposure to heat is a growing public health concern as climate change accelerates worldwide. Different socioeconomic and racial groups often face unequal exposure to heat as well as increased heat-related sickness, mortality, and energy costs. We provide new insight into thermal inequities by analyzing 20 Southwestern U.S. metropolitan regions at the census block group scale for three temperature scenarios (average summer heat, extreme summer heat, and average summer nighttime heat). We first compared average temperatures for top and bottom decile block groups according to demographic variables. Then we used spatial regression models to investigate the extent to which exposure to heat (measured by land surface temperature) varies according to income and race. Large thermal inequities exist within all the regions studied. On average, the poorest 10% of neighborhoods in an urban region were 2.2 °C (4 °F) hotter than the wealthiest 10% on both extreme heat days and average summer days. The difference was as high as 3.3-3.7 °C (6-7 °F) in California metro areas such as Palm Springs and the Inland Empire. A similar pattern held for Latinx neighborhoods. Temperature disparities at night were much smaller (usually ~1 °F). Disparities for Black neighborhoods were also lower, perhaps because Black populations are small in most of these cities. California urban regions show stronger thermal disparities than those in other Southwestern states, perhaps because inexpensive water has led to more extensive vegetation in affluent neighborhoods. Our findings provide new details about urban thermal inequities and reinforce the need for programs to reduce the disproportionate heat experienced by disadvantaged communities.

Exposure to heat is a growing public health concern as climate change accelerates worldwide. Different socioeconomic and racial groups often face unequal exposure to heat as well as increased heat-related sickness, mortality, and energy costs. We provide new insight into thermal inequities by analyzing 20 Southwestern U.S. metropolitan regions at the census block group scale for three temperature scenarios (average summer heat, extreme summer heat, and average summer nighttime heat). We first compared average temperatures for top and bottom decile block groups according to demographic variables. Then we used spatial regression models to investigate the extent to which exposure to heat (measured by land surface temperature) varies according to income and race. Large thermal inequities exist within all the regions studied. On average, the poorest 10% of neighborhoods in an urban region were 2.2 °C (4 °F) hotter than the wealthiest 10% on both extreme heat days and average summer days. The difference was as high as 3.3-3.7 °C (6-7 °F) in California metro areas such as Palm Springs and the Inland Empire. A similar pattern held for Latinx neighborhoods. Temperature disparities at night were much smaller (usually ~1 °F). Disparities for Black neighborhoods were also lower, perhaps because Black populations are small in most of these cities. California urban regions show stronger thermal disparities than those in other Southwestern states, perhaps because inexpensive water has led to more extensive vegetation in affluent neighborhoods. Our findings provide new details about urban thermal inequities and reinforce the need for programs to reduce the disproportionate heat experienced by disadvantaged communities.

The purpose of this dissertation is to examine the effects of environmental conditions on graduation and dropout rates in the United States. Neighborhood effects studies are not uncommon, however they typically fail to account for serious selection issues that potentially bias results. The contribution of this dissertation is to offer an alternative approach, natural experiments, to deal with such methodological problems. The dissertation consists of one theoretical chapter and two analytical chapters. In chapter one, I establish the econometric difficulties of estimating neighborhood effects and outline how a natural experiment can obviate these problems if applied correctly. This chapter sets up the rest of my dissertation, which includes two empirical chapters using major urban riots and county mass layoffs as natural experiments.In chapter one, I describe the econometric difficulties of estimating neighborhood effects within the context of youth educational well-being. I outline the three levels of selection bias, individual, family and school, that researchers normally confront when attempting to examine the effects of community conditions on education outcomes. While most studies attempt to minimize individual and family level bias, they often neglect to account for school level context. Doing so will lead to biased results because model parameters will fail to reflect the lack of independence between units due to clustering within schools and the deep selection issues caused by the interwoven relationship between neighborhoods and schools. I then outline the conditions under which a natural experiment can solve these problems. This chapter sets the stage for the two empirical articles that make up the rest of my dissertation.In the first analytical chapter, I examine the effects of large urban riot shocks to city wide conditions on aggregate dropout rates. Using decennial census data, I examine the 1960s civil rights riots on city level school non enrollment

The purpose of this dissertation is to examine the effects of environmental conditions on graduation and dropout rates in the United States. Neighborhood effects studies are not uncommon, however they typically fail to account for serious selection issues that potentially bias results. The contribution of this dissertation is to offer an alternative approach, natural experiments, to deal with such methodological problems. The dissertation consists of one theoretical chapter and two analytical chapters. In chapter one, I establish the econometric difficulties of estimating neighborhood effects and outline how a natural experiment can obviate these problems if applied correctly. This chapter sets up the rest of my dissertation, which includes two empirical chapters using major urban riots and county mass layoffs as natural experiments.In chapter one, I describe the econometric difficulties of estimating neighborhood effects within the context of youth educational well-being. I outline the three levels of selection bias, individual, family and school, that researchers normally confront when attempting to examine the effects of community conditions on education outcomes. While most studies attempt to minimize individual and family level bias, they often neglect to account for school level context. Doing so will lead to biased results because model parameters will fail to reflect the lack of independence between units due to clustering within schools and the deep selection issues caused by the interwoven relationship between neighborhoods and schools. I then outline the conditions under which a natural experiment can solve these problems. This chapter sets the stage for the two empirical articles that make up the rest of my dissertation.In the first analytical chapter, I examine the effects of large urban riot shocks to city wide conditions on aggregate dropout rates. Using decennial census data, I examine the 1960s civil rights riots on city level school non enrollment

Estimating the effects of international migration on left-behind children's educational attainment is complicated by the potential offsetting effects of fathers' absences and household remittances. Most research has not separated these aspects of international migration on children's human capital outcomes. We address this deficiency by using instrumental variables to isolate the effects of fathers' international migration absences from international household remittances on student enrollment and grade progression in Guatemala. Results indicate that fathers' absences and household international remittances are negatively related to enrollment, providing evidence for a culture of migration effect. For students who remain in school, household international remittances neutralize the harmful influence of fathers' absences on grade progression.

Historically, Guatemalans have suffered high rates of poverty and malnutrition while nearly ten percent of their population resides abroad. Many Guatemalan parents use economic migration, mainly international migration to the United States, as a means to improve the human capital prospects of their children. However, as this investigation shows, the timing of migration events in relation to left-behind children's ages has important, often negative and likely permanent, repercussions on the physical development of their children. To illustrate these dynamics, this investigation uses an instrumental variables framework to disentangle the countervailing effects of Guatemalan fathers' absences due to migration from concomitant remittances on left-behind children's growth outcomes. Based on national-level data collected in 2000, the investigation reveals that the international migration of a father in the previous year is correlated with a 22.1% lower length/height-for-age z-score for the average left-behind child aged ≤ 3. In contrast, the receipt of remittance income has no influence on the physical stature of a child, which may indicate that migrant fathers with young children are not able to achieve economic success soon enough during their ventures abroad to fully ameliorate the harmful effects caused by their absences.

BackgroundEmpirical research describes retirement migration to Mexico as a viable option for some older Americans. However, far less research examines this phenomenon among Mexican immigrants in the United States. The literature that does address this topic treats international migration as a singular occurrence and does not examine the possibility of return and subsequent reentry between countries. This omission creates an important gap in our knowledge of international retirement migration considering the strong transnational ties that Mexican immigrants maintain to the home and destination countries.ObjectiveUsing a multistate life table approach, this study examines the rate of return to Mexico and reentry back into the United States among Mexican males aged 50 and older with U.S. migration experience, as well as the number of years spent in both countries.ResultsResults show that the rate of reentry from Mexico into the United States declined from 3.33% at age 50-54 to less than 1% at age 70 and older (p-value<0.05). In contrast, the rate of return to Mexico from the United States increased from 3.19% at age 50 to 54 to 4.44%at age 65 to 69 and dropped to less than 2% at age 70 and older (p-value<0.05).ConclusionsWhile rates of return and reentry among this population are relatively low, they provide insight on the potential life course factors driving the migration patterns of a population of increasing size and relevance in the United States.