Since 1980, over 2,000 local governments in US Atlantic and Gulf states have been hit by a hurricane. Such natural disasters can exert severe budgetary pressure on local governments' ability to provide critical infrastructure, goods, and services. We study local government revenue, expenditure, and borrowing dynamics in the aftermath of hurricanes. These shocks reduce tax revenues and expenditures, and increase the cost of debt in the decade following exposure. Major hurricanes have much larger effects than minor hurricanes. Our results reveal how hurricanes create collateral fiscal damage for local governments by increasing the cost of debt at critical moments after a hurricane strike. Municipalities with a racial minority composition 1 standard deviation above the sample mean suffer expenditure losses more than 2 times larger and debt default risk 8 times larger than municipalities with average racial composition in the decade following a hurricane strike. These results suggest that climate change can exacerbate environmental justice challenges.

The notion of raising Pennsylvania’s minimum wage—and thereby Philadelphia’s—has been a topic of considerable debate over the past year, both in the state Legislature and elsewhere. As of Jan. 1, 2020, Philadelphia’s minimum wage was $7.25 an hour, where it has remained since 2009. The rate—which is also the federal minimum—is set by the state, and the city has no authority to change it. Responding to a nonbinding ballot question in May 2019, Philadelphia voters voiced overwhelming support for a $15-an-hour minimum. And the city government has raised the minimum for its own workers, as well as for city contractors and subcontractors, to $13.25, with plans to gradually increase it to $15 by mid-2022. To help inform the conversation, The Pew Charitable Trusts set out to determine how Philadelphia’s minimum wage compares with the rate in other major cities and to take a detailed look at how many Philadelphians have been getting paid that amount—and who they are. The research found that a majority of major U.S. cities have higher minimums than Philadelphia’s, some substantially higher, although 14 of the 31 cities studied for this brief also are at $7.25. When the overall level of wages in each of the metropolitan areas that include those cities is taken into account, Philadelphia has what is effectively the lowest minimum of any of those cities. This is the result of Philadelphia’s low minimum, the relatively high wages paid throughout the region, and a higher cost of living than in many of the other cities with the same $7.25 hourly rate. According to data from the U.S. Census Bureau’s American Community Survey (ACS), an estimated 9% of all Philadelphians age 16 or older working in Pennsylvania and receiving wages or salaries from private employers or state or local government—about 44,000 individuals—were earning an hourly average of $7.25 or less in the five-year period ending in 2018, the most recent years with detailed data available. Of that number, approximately 21,000, or 4% of Philadelphia workers, worked full time and year-round at that rate. These estimates likely include some workers who are not covered by the minimum wage or whose employers did not comply with the law. Relative to the city’s overall workforce, residents earning $7.25 or less were disproportionately nonwhite or Hispanic, young, and lacking a college degree. Sixty-three percent of all Philadelphians earning the minimum wage or less worked in four sectors: accommodation and food services, retail trade, health care and social assistance, and educational services. As the inflation-adjusted value of the minimum wage has declined over time, the share of those earning $7.25 or less has fallen from roughly 11% of Philadelphians working in Pennsylvania in 2010 to about 8% in 2018. An additional 7% made $7.26 to $9.50 per hour. With many low-wage workers and the sectors that employ them being hit hard by the COVID-19 pandemic and its economic fallout, it remains to be seen what shape the minimum wage conversation will take once it resumes in earnest.

Immigration may put a strain on the health care system, adversely impacting the health of the native population. At the same time, recent studies have documented the role of immigration in nudging native workers from risk-intensive, physically demanding jobs towards occupations that require more communication and interactive ability, potentially improving their health. In this article, I examine the relationship between immigration and the health of the native population in the United States. The results of the analysis fail to show that immigration adversely affects the health of U.S. natives. Instead, the findings suggest that the presence of low-skilled immigrants may improve the health of low-skilled U.S.-born individuals. (PDF) Immigration and the Health of United States Natives.

Jackson’s famous Crabgrass Frontier: The Suburbanization of the United States (1985) argues that when American cities suburbanized in the early nineteenth century, the richest households moved from the core to the periphery, the poorest stayed in the core, and the households that moved to the periphery were richer than those who were there before them. I study the gradual process of prewar suburbanization in America’s biggest city, New York City, between 1870 and 1940. During this time there were huge transportation infrastructure improvements at both intra- and inter-city level, and there was gradual suburbanization, just as in Jackson (1985). I construct a historical longitudinal database that follows individuals to analyze how the migration patterns differ across workers with different income (skills). Rich people on average did not leave the core and poor people on average did not stay. New suburbanites to the city periphery were not richer than the people who already lived at the periphery. Jackson’s fundamental claim about the growth of high income at the edge relative to the center still holds true for my study period. However, I show the mechanism behind this change and show that this relative change in income growth at the edge did not result from a simple shuffling of rich and poor. Up until the Great Depression, flows of migrants from and to outside ⇤sunkyoung.lee@yale.edu 1 the metropolitan area were the dominant force in changing average income. Richer people from outside NYC metropolitan area migrated to the periphery and poorer people from outside NYC metropolitan migrated to the core. The people from the city core who left the metropolitan area were far richer than the people from the periphery who left the metropolitan area. Furthermore, people who stayed at the periphery got richer as the metropolis grew. Many readers have interpreted Crabgrass Frontier as the story of America’s suburbanization always and everywhere, and so my finding that two of the major propositions in that book and the mechanism behind income growth at the edge do not apply to 1870-1940 New York has implications beyond local history

The increase in population pressure and external influences, such as economic growth, urbanization have accelerated the urban sprawl within the Houston-Galveston metropolitan region along the Texas gulf coast resulting in substantial changes in land cover. Increase in human activities along with natural changes have impacted the water quality in the bayous and their associated watersheds which drain into Galveston Bay. The specific objectives of the study are (1) To analyze and monitor the soil and water characteristics along the urban and rural fringes in the Houston/Galveston region; (2) Monitor and map the spatial and temporal land cover changes in the identified watersheds;(3) Identify and analyze the impact of land cover on flooding in the region. A total of 236 Soil and 138 water samples were collected from at least three locations in the selected watersheds over 3 years. Samples were processed and analyzed for elemental concentrations using the Inductive Coupled Plasma Mass Spectrometer (ICP-MS), Milestone Direct Mercury Analyzer (DMA) 80 and a Total Carbon and Nitrogen (TCN) Analyzer. Spatial analysis was conducted using the Geographic information systems (GIS) and satellite remote sensing. Chemical analysis results indicate that TN and P exceeded the EPA criteria limit in water samples. The concentrations of Pb, Cu and Zn exceed the critical limits across 2 all bayous in both soil and water samples. Landsat satellite imagery of over four decades (1980-2019) were processed and analyzed for the land cover changes. The remote sensing analysis revealed that the Buffalo Bayou watershed (BBW), Brays Bayou watershed (BrBW), Lower Cypress Creek watershed (LCCW), Mustang Bayou watershed (MBW) & Dickinson Bayou watershed (DKBW) lost about 18.6%, 27%, 33.8%, 29.6% and 2.16% of vegetation respectively and 23%, 40%, 58%, 65% and 2% increase in impervious surface respectively. The vegetation loss in area statistics resulted in the increase of impervious surface areas in all the watersheds. This research is significant as it shows the impact of the natural and human activities on the Texas Bayous and the long-term consequences on the environmental health of the HoustonGalveston Region.

The spread of COVID-19 among “essential” crop workers is a source of major concern for growers and policy makers. COVID-19 risk factors for Florida crop workers vary across counties and legal status groups. These differences suggest the need for tailored prevention and mitigation plans for COVID-19 infections among crop workers.

Exposure to conflict is associated with multiple impacts on youth populations in developing countries, predominantly in the areas of health and nutrition. Where many previous works have examined large-scale impacts of exposure to conflict on the civilian population, this study will analyze the effects of exposure to conflict specific to the experiences of children under the age of five. Where experiences of armed conflict are often indiscriminately destructive to individual well-being, West African conflicts have been characterized by disproportionately high levels of violence, with their most extreme consequences forced upon women and children. Research has suggested that accepted gender norms and levels of women’s agency may be strongly associated with children’s health responses to exposure to increased violence and conflict. To test this association this thesis assumes a critical analysis of reduced educational attainment and low marital age among women in relation to the effects of conflict on measures of childhood food security. Through the use of high-resolution conflict data from the Armed Conflict Location and Event Database (ACLED) and the Demographic and Health Survey (DHS), this thesis examines the effects of armed conflict on children under five years of age across seven West African nations. Along with previous works exploring the relationship between conflict and childhood nutrition, this study finds a negative, albeit small and statistically insignificant, impact on measures of weight-for-height (WFH). Surprisingly, there is a significant and positive response in children’s height-for-age (HFA) associated with exposure to conflict during one’s lifetime.

In March of this year, COVID-19 was declared a pandemic, and it continues to threaten public health. This global health crisis imposes limitations on daily movements, which have deteriorated every sector in our society. Understanding public reactions to the virus and the non-pharmaceutical interventions should be of great help to fight COVID-19 in a strategic way. We aim to provide tangible evidence of the human mobility trends by comparing the day-by-day variations across the U.S. from January 2020 to early April 2020. Large-scale public mobility at an aggregated level is observed by leveraging mobile device location data and the measures related to social distancing. Our study captures spatial and temporal heterogeneity as well as the sociodemographic variations and teleworking trends regarding the pandemic propagation and the non-pharmaceutical mobility interventions. All metrics adapted capture decreased public movements after the national emergency declaration. The population staying home has increased in all states before the stay-at-home mandates implemented and becomes more stable after the order with a smaller range of fluctuation. The public had been taking active responses, voluntarily staying home more, to the in-state confirmed cases while the stay-at-home orders stabilize the variations. As the estimated teleworking rates also continue to incline throughout the study period, the teleworking trend can be another driving factor for the growing stay-at-home population. We confirm that there exists overall mobility heterogeneity between the income or population density groups. The study suggests that public mobility trends are in line with the government message urging to stay home. We anticipate our data-driven analysis offers integrated perspectives and serves as evidence to raise public awareness and, consequently, reinforce the importance of social distancing while assisting policymakers.

COVID-19 substantially decreased employment, but the effects vary among demographic and socioeconomic groups. We document the employment losses in April 2020 across various groups using the U.S. Current Population Survey. The unemployment rate understates employment losses. We focus on the percentage of the civilian population that is employed and at work. Young persons experienced the largest employment losses. Individuals with less education and lower family income experienced much larger employment losses than their more educated and higher income counterparts. Hispanics and blacks were more adversely affected than whites.

We contribute to literature exploring the socioecological impact of urban development as a multidimensional project, one in which changes to landscape features complement changes in demographic and administrative measures to co-constitute the socioecological impact of urbanity. We use a random coefficients modeling approach to examine U.S. relationships between the intensity of impervious surface within a county, population density in impervious areas, and carbon intensity of well-being (CIWB)—here constructed using industrial emissions. We then explore the moderating association that another component of social settlement patterns, household median income, has on the impervious surface–population density–CIWB nexus. Findings suggest that landscapes featuring greater development of impervious surface are associated with increased CIWB. Further exploration indicates that income acts to attenuate the association of urban space and CIWB. Ultimately, we argue that such attenuation indicates that more affluent areas are able to shift production-based processes associated with urban forms to less affluent areas.

We offer a brief review of the use of distributional mixture models with a finite number of components for the study of the distribution of income. In general, finite mixture models find a number of applications across fields, but they usually arise from theoretical considerations. Applications to the distribution of income present a joint inference about the number and types of components to include in a mixture, corresponding to how different income generating mechanisms’ statistical signatures are represented in the observed data. Many of the contributions in this area rest on an implicit (and sometimes explicit) information theoretic approach to this inference problem. Our review concludes with new illustrative findings from the US based on restricted-access Census data.

Suburbs are currently the focus of much research because they are the arena for many contemporary social, economic, and political issues. Yet definitions of what constitutes a suburb remain elusive, and there is no consensus in the literature on best practice approaches. This article presents a side-by-side comparison of four methods of defining suburbs for quantitative research (Cooke and Marchant 2006; Hanlon and Vicino 2007; Kneebone and Berube 2013; Anacker, Niedt, and Kwon 2017). The comparison was conducted with data from the one hundred largest metropolitan areas in the United States using multivariate analysis of variance. The four methods were evaluated based on how well they capture the racial, ethnic, and socioeconomic variability between urban and suburban areas and within suburban areas themselves. The results indicate that political boundaries of the inner city and regional variation in metropolitan structure are important characteristics that need to be considered when selecting a suburb definition for quantitative, comparative research on suburbs. This article highlights the strength and weaknesses of each method and recommends which method works best in various geographical contexts.

The justification and targeting of conservation policy rests on reliable measures of public and private benefits from competing land uses. Advances in Earth system observation and modeling permit the mapping of public ecosystem services at unprecedented scales and resolutions, prompting new proposals for land protection policies and priorities. Data on private benefits from land use are not available at similar scales and resolutions, resulting in a data mismatch with unknown consequences. Here I show that private benefits from land can be quantified at large scales and high resolutions, and that doing so can have important implications for conservation policy models. I developed high-resolution estimates of fair market value of private lands in the contiguous United States by training tree-based ensemble models on 6 million land sales. The resulting estimates predict conservation cost with up to 8.5 times greater accuracy than earlier proxies. Studies using coarser cost proxies underestimate conservation costs, especially at the expensive tail of the distribution. This has led to underestimations of policy budgets by factors of up to 37.5 in recent work. More accurate cost accounting will help policy makers acknowledge the full magnitude of contemporary conservation challenges and can help improve the targeting of public ecosystem service investments.

Acute respiratory infection (ARI) and diarrhoea are two major causes of child morbidity and mortality in Bangladesh. National and regional level prevalence of ARI and diarrhoea are calculated from nationwide surveys; however, prevalence at micro-level administrative units (say, district and sub-district) is not possible due to lack of sufficient data at those levels. In such a case, small area estimation (SAE) methods can be applied by combining survey data with census data. Using an SAE method for the dichotomous response variable, this study aims to estimate the proportions of under-5 children experienced with ARI and diarrhoea separately as well as either ARI or diarrhoea within a period of two-week preceding the survey. The ARI and diarrhoea data extracted from Bangladesh Demographic and Health Survey 2011 are used to develop a random effect logistic model for each of the indicators, and then the prevalence is estimated adapting the World Bank SAE approach for the dichotomous response variable using a 5% sample of the Census 2011. The estimated prevalence of each indicator significantly varied by district and sub-district (1.4–11.3% for diarrhoea, 2.2–11.8% for ARI and 4.3–16.5% for ARI/diarrhoea at sub-district level). In many sub-districts, the proportions are found double of the national level. District and sub-district levels spatial distributions of the indicators might help the policymakers to identify the vulnerable disaggregated and remote hotspots. Particularly, aid industries can provide effective interventions at the highly vulnerable spots to overcome the gaps between micro and macro level administrative units.

Using data on a sample of small Iowa towns consistently collected over two decades, we investigate how agglomeration economies, social capital, human capital, local fiscal policy, and natural amenities affect new firm entry. We find that human capital and agglomeration are more conducive to new firm entry than are natural amenities, local fiscal policy, or social capital. The impact of local fiscal policy is too small to overcome the locational disadvantages from insufficient endowment of human capital and agglomeration. A rural development approach that encourages firm entry in rural towns with the largest endowments of human capital and market agglomeration would be more successful than trying to raise firm entry in every town.

There are large disparities in COVID-related unemployment, with the largest proportional losses among Latinx and less-educated workers. The effects have been particularly felt among children. In our original research based on very recent data, we find that one-in-five children in the United States experienced the job loss of an adult in their household between February and April of 2020 and one-in-twelve experienced the job loss of all adult earners in their household, including one-in-seven children living with single parents. Our analysis also points to striking disparities by race, ethnicity, and income, with higher shares of Latinx, Black, and lower-income children losing all adult earners in their households. While there was some job recovery between April and May, the pattern of job losses appears to be exacerbating inequality.

Working in a discrete location choice framework, we develop a model of migration that allows the identification of heterogeneity in state‐of‐birth effects across states. We employ a novel method for using aggregate data to estimate the role of birth state on migration choices. This approach reveals considerable heterogeneity and some regional clustering in birth‐state inertia effects across states, with strong attachments in California, the Southwest, and the upper Midwest. The weakest attachments are in the mountain states and New York.

This research establishes the influence of linguistic traits on human behavior. Exploiting variations in the languages spoken by children of migrants with identical ancestral countries of origin, the analysis indicates that the presence of periphrastic future tense and its association with long-term orientation has a significant positive impact on educational attainment, whereas the presence of sex-based grammatical gender, and its association with gender bias, has a significant adverse impact on female educational attainment.

Sociologists have long struggled to explain the minority mental health paradox: that racial-ethnic minorities often report better mental health than non-Hispanic whites despite social environments that seem less conducive to well-being. Using data from the 2008–2013 Medical Expenditure Panel Survey (MEPS), this study provides a partial explanation for the paradox rooted in a very different disparity. Evidence from MEPS indicates that non-Hispanic whites consume more pharmaceuticals than racial-ethnic minorities for a wide variety of medical conditions. Moreover, non-Hispanic whites consume more pharmaceuticals that although effective in treating their focal indication, include depression or suicide as a side effect. In models that adjust for the use of such medications, the minority advantage in significant distress is reduced, in some instances to statistical nonsignificance. Although a significant black and Hispanic advantage in a continuous measure of distress remains, the magnitude of the difference is reduced considerably. The relationship between the use of medications with suicide as a side effect and significant distress is especially large, exceeding, for instance, the relationship between poverty and significant distress. For some minority groups, the less frequent use of such medications is driven by better health (as in the case of Asians), whereas for others, it reflects a treatment disparity (as in the case of blacks), although the consequences for the mental health paradox are the same. The implications of the results are discussed, especially with respect to the neglect of psychological side effects in the treatment of physical disease as well as the problem of multiple morbidities.

In many communities throughout the country with high housing costs and significant senior populations, intergenerational homeshare programs have matched overhoused seniors with younger tenants who live in a spare bedroom for below-market rent. This thesis investigates the interest in such a program in the Tufts community by examining how many Tufts students and Tufts-affiliated seniors are interested in participating in an intergenerational homeshare program and what their potential motivations, benefits, and challenges would be. Through surveys from 268 students and 28 seniors, and focus groups with 8 and 6 respectively, I find that more than 150 students are at least moderately interested in participating, with an additional nine seniors feeling similarly, and over 60% having at least one unused spare bedroom. While participants discussed many challenges associated with such a program, this interest should encourage further investigation in Somerville and Medford into implementing such a program in cooperation with Tufts.