Rising water bills across the U.S. underscore the need to understand the factors that contribute to disparities in local system bills. In this paper, we examine residential water bill amounts from 1,720 systems in four states in different regions of the U.S. (Arizona, Georgia, New Hampshire and Wisconsin) to (1) examine how local system bills at a constant consumption level (4,000 gallons per month or 15.14m3) for drinking water vary within and across states, as well as within combined metropolitan statistical areas (MSAs), and (2) study the relationship between local system bills and system-level characteristics. We find a high degree of similarity in median bill amounts between states but substantial variation within them at the MSA and local system scale. Our multivariate analysis suggests that municipally-owned systems are more likely to have lower water bills relative to for-profit systems, while factors such as purchasing water and having neighboring systems with high bills significantly correlate with higher water bills. Though we find that water systems with high levels of poverty tend to have higher water bills, our results also suggest that local systems that serve populations with higher levels of income inequality and higher proportions of non-White population tend to have lower water bills. These findings point to future research and data needs to better inform federal, state and local water affordability policy and underline the importance of examining and addressing water affordability at local scales.

A number of recent papers have investigated the impact of hurricanes on economic growth. However, there is limited understanding of the investment component of local growth after hurricanes. Using hand collected and web-scraped statutory property tax rate data in the U.S., I find that local governments respond to hurricane impact by raising tax rates. I find the hike in tax rates is persistent for 3-4 years after hurricane impact. The response is four times larger for major hurricanes compared to minor hurricanes. However, the increase in tax rates is not expected to be large enough to cause significant out-migration after the average hurricane. I supplement these findings with a novel data set of firm facility-level hurricane impact. I find that firms initially decrease investment in the quarter following hurricane impact and increase it in the final quarters of the second year after impact. Taken together, my paper presents a novel set of stylized facts on government and firm mitigation investment response that can be interpreted in light of recent general equilibrium models with disaster risk.

The number of well-off households deciding to rent rather than buy has exploded across the Triangle, according to a new study from RentCafe. In Raleigh, the number of “rich” renter households — those with annual incomes over $150,000 — skyrocketed by 178% between 2015 and 2020, going from 1,877 to 5,224, the study found. Cary, meanwhile, saw its number of affluent renters grow by 90%. The city reached a high of 2,388 well-off renter households in 2020 compared to 1,258 just five years prior. Durham followed with a 76% jump, adding 937 rich renter households, going from 1,226 to 2,388.

As the U.S. marriage rate has decreased over the past few decades (Schweizer, 2020), the share of those who have never married has increased, reaching 31% in 2020 (Marino, 2023a). Additionally, the median age of unmarried men and women, including those who are divorced, widowed, or never married, has increased over the past few decades (Marino, 2023b). These trends suggest the need to examine patterns among a specific subset of this growing share of Americans: adults who have yet to or may never marry. Using data from the 1940 to 1990 U.S. Decennial Census the American Community Survey 1-year estimates from 2000, 2010, and 2020, this family profile examines trends in the median age of adults (aged 18 and older) in the U.S. who reported they had not been married. We also describe differences in the median age of never married adults by gender, race and ethnicity, and educational attainment. The share of the population that was unmarried has changed according to these characteristics (Marino, 2023a), and may be a factor in driving these age patterns. Changing patterns in the median age of never married adults signal that those who marry may be doing so at later ages or that more adults are forgoing marriage.

In Chap. 1 we described spaces as planes with mathematical properties that allow us to identify objects located in those planes. We further identified these objects as places with meaning that we may experience, live, and remember. Subsequently, we defined splaces as the intermingling of spaces and spaces that may enrich our understandings of processes, mechanisms, and the explanations of the outcomes observed. From this view, splaces then, eased our discussion of geographies of opportunity and disopportunity, feedback loops, sorting or self-selection, and multicollinearity issues. We, however, have so far limited these discussions to conceptual understandings and have yet to discuss and showcase how to operationalize these splaces. Accordingly, the purpose of this chapter is to introduce and apply these concepts into practical applications using real and publicly available data. To this end, we will discuss how to delimit and operationalize splaces with particular emphasis on data format structures and sources. We will also discuss tradeoffs associated with zooming in (i.e., going from higher level areas [counties] to lower level areas [census tracts]) into splaces, which, although may result in data points gains, may be computationally expensive. Finally, we close this chapter with examples of attributes readily available at the American Community Survey (ACS) that can be used to operationalize concentrated disadvantages.

Background: The objective of this study was to examine the association between racialized economic segregation, allostatic load (AL), and all-cause mortality in patients with breast cancer. Patients and Methods: Women aged 18+ years with stage I–III breast cancer diagnosed between 01/01/2012 and 31/12/2020 were identified in the Ohio State University cancer registry. Racialized economic segregation was measured at the census tract level using the index of concentration at the extremes (ICE). AL was calculated with biomarkers from the cardiac, metabolic, immune, and renal systems. High AL was defined as AL greater than the median. Univariable and multivariable regression analyses using restricted cubic splines examined the association between racialized economic segregation, AL, and all-cause mortality. Results: Among 4296 patients, patients residing in neighborhoods with the highest racialized economic segregation (Q1 versus Q4) were more likely to be Black (25% versus 2.1%, p < 0.001) and have triple-negative breast cancer (18.2% versus 11.6%, p < 0.001). High versus low racialized economic segregation was associated with high AL [adjusted odds ratio (aOR) 1.40, 95% confidence interval (CI) 1.21–1.61] and worse all-cause mortality [adjusted hazard ratio (aHR) 1.41, 95% CI 1.08–1.83]. In dose–response analyses, patients in lower segregated neighborhoods (relative to the 95th percentile) had lower odds of high AL, whereas patients in more segregated neighborhoods had a non-linear increase in the odds of high AL. Discussion: Racialized economic segregation is associated with high AL and a greater risk of all-cause mortality in patients with breast cancer. Additional studies are needed to elucidate the causal pathways and mechanisms linking AL, neighborhood factors, and patient outcomes.

The aim of this paper is to explore whether the implementation of the restrictive abortion policy House Bill 2 (HB2) in Texas 2013 impacted the abortion- and birth rates within the state, and whether the policy was associated with a change in the socioeconomic and demographic composition of women giving birth. For the first-stage regressions, state-level yearly panel data and a difference-in-difference framework are used to examine the impact of the policy on abortion- and birth rates. For the second-stage regressions, where we examine whether the establishment of HB 2 had an effect on the socioeconomic and demographic composition of women giving birth, repeated cross-sectional data of mothers in fertile ages in Texas is used, together with a Before- and-after Ordinary Least Squares regression. The results indicate that the implementation of HB 2 was associated with a decrease in the abortion rate, and a slight increase in the birth rate. Moreover, the results from the second-stage regressions imply that women giving birth after the establishment of HB 2 were less likely to be within the labor force, more likely to be below the poverty line and more likely to be teenagers. This paper provides insightful findings concerning which groups of women were more heavily affected by the implementation of HB 2 and a broader understanding of how restrictive abortion policies might unevenly affect specific groups of women, not least in the light of the recent overturning of Roe v. Wade in 2022.

In 2020, an estimated 8 to 12 million Americans started an online fundraising campaign to cover the cost of healthcare. In this paper, we study the causes and consequences of medical crowdfunding using data from GoFundMe, one of the largest online fundraising platforms. First, we show that the ACA Medicaid expansion had a statistically meaningful effect in reducing the number of health-related GoFundMe campaigns. This suggests that the demand for crowdfunded medical care could be driven, in part, by lack of health insurance coverage. Next, we show that the growth of medical crowdfunding can exacerbate group-level inequality by reinforcing existing disparities in health access. Specifically, we document that GoFundMe campaigns organized by individuals with distinctively African-American or Hispanic surnames and first-names are significantly less likely to meet their fundraising target and raise less funds overall than those organized by individuals with neutral or distinctively White names. We conclude by investigating the channels underlying these racial disparities in crowdfunding success.

This article will examine the trends and patterns in Nigeria-U.S. relations, while tracing the features of development of the relations between citizens of both countries, starting from the export of slaves in the previous centuries to the Nigerian students in the U.S. in the mid-1940s and 1950s up till the attainment of independence in 1960. The section will also x-rays the development of political relationship between the two countries, from independence in 1960 to the era of emerging economic alliances from 1960 to 1967; the era of Nigeria-Biafra war between 1967 and 1970; the era of the oil boom 1970 to the early 1980s; the era of the Structural Adjustment Programme and economic dependence of 1983 to 1993; the era of embargo on Nigerian oil, 1993 to 1999. It will go forward to surveying the importance of the period between 1999 and 2015, which was the era which attempted to deepen democratic institutions in Nigeria. Each of these periods in NigeriaU.S. relations have shown to have a unique character in the behavioural pattern of policy makers in both countries as determined by the prevailing circumstances on ground during such periods.To this end therefore, the study has attempted to ascertain the extent of the challenges that have characterized the many years of relationship between the regional powers, and to achieve this,the research has adopted both the quantitative and qualitative approaches of research methodology.This will enable the interpretation of the data generated from both primary and secondary sources. Some of the findings and conclusions drawn from the study show that political, social, economic and security challenges responsible for the fluctuations that were observed in the bilateral relations between the two countries. The study therefore recommends that Nigeria should strengthen its foreign policy attention and resources in the bilateral relations with the US in areas that are potentially strategic to its national transformation and security.

With 52% of Millennials owning a home, the largest generation in the nation transitioned from renter-majority to owner-majority in 2022. The number of Millennial homeowners increased by 7 million in the last five years, more than triple the number added by Gen X, who came in second. Millennials remained the dominant renter generation, with 17.2 million renter households. Gen Z is now the only renter-majority generation with a 74% share and 4.5 million renters added in the last five years, more than any other age group. Of the nation’s top 50 largest metros, Richmond, VA, saw the highest jump in Millennial owners — 234%.

This is our last conceptual chapter. In this chapter we formally discuss three topics with important practical implications for SSEM: spatial data formats (vector and raster), coordinate reference systems (projected and unprojected), and data privacy or projection frameworks (data swapping, differential privacy, and jittering). Accordingly, the purpose of this chapter is to provide readers with the set of practical elements and understandings required to start reading spatial data files and building, visualizing, and analyzing splace datasets while being aware of the relevance of protecting our participants’ privacy. From this perspective, we begin the chapter with a presentation of spatial data formats that include: (a) raster or grid data files which represent units in space based on a matrix or grid, and (b) vector data format which stores and represents geographical features (or geometries) as points, lines, or polygons. As part of this presentation, we illustrate how to move from raster to vector data and vice versa, along with the implications of these transformations for SSEM. Subsequently, we introduce coordinate reference systems (CRSs) and discuss similarities and differences between projected (flattened) and unprojected (spherical) spatial data representations, once again while highlighting similarities, differences, and the implications of each CRS form for SSEM. Finally, we close this chapter with a discussion of Differential Privacy Frameworks implemented by the United States Census Bureau as a response to the conundrum of presenting as accurate counts of inhabitants as possible, while protecting the identity and privacy of the respondents. From this view, although differential protection was developed and implemented with the goal of protecting participants’ place-based anonymities based on their personal attributes, this framework may pose challenges with respect to modeling accuracy. Our presentation will discuss the implications of these data protections for SSEM and will also illustrate instances where the preservation of accurate spatial mapping and analyses is paramount.

n this paper, we introduce the R package mcmsupply which implements Bayesian hierarchical models for estimating and projecting modern con-traceptive method supply shares over time. The package implements four model types. These models vary by the administration level of their outcome estimates (national or sub national estimates) and dataset type utilised in the estimation (multi-country or single-country contraceptive market supplydatasets). mcmsupply contains a compilation of national and subnationallevel contraceptive source datasets, generated by IPUMS and Demographicand Health Survey microdata. We describe the functions that implement the models through practical examples. The annual estimates and projections with uncertainty of the contraceptive market supply, produced by mcmc-supply at a national and subnational level, are the first of their kind. These estimates and projections have diverse applications, including acting as an indicator of family planning market stability over time and being utilised in the calculation of estimates of modern contraceptive use.

A large literature shows that the children of immigrants have high upward mobility. However, immigrants vary vastly in how they are selected: while economic immigrants are chosen based on skill and education, refugees migrate at times of conflict and war. In this paper, we study the mobility of immigrants by admission class. Using administrative data linking the universe of immigrant landing documents with tax records in Canada, we estimate intergenerational mobility outcomes by refugee status. We find that for immigrant parents at the 25th percentile of the income distribution, refugee children have an expected rank of 47 percentiles, while the corresponding estimate for non-refugee children is 51 percentiles. Approximately 60% of this gap can be explained by differences in parental attributes upon arrival, indicating that selection contributes to higher mobility. Finally, we show that when correcting for the underplacement of immigrant parents, the absolute upward mobility of refugees at p25 is largely unaffected while that of non-refugees falls by around 2 percentiles.

Urban housing markets are characterized by racial sorting, but equilibrium prices respond to marginal buyers and thus may mask underlying preferences for segregation. Large migration shocks can make visible these otherwise infra-marginal preferences. We study the effects of Hurricane Katrina-induced displacement on housing markets in receiving neighborhoods in Texas, where 1 in 5 New Orleanians relocated. Using an event study design, we find that the relocation of 100 additional Katrina survivors to a receiving ZIP code is associated with a 2.2% decline in relative house prices five years after the storm. This effect is driven by responses to movers from predominantly Black origin blocks. We argue that our findings are best explained by a preference for segregation on the part of incumbent White residents. In this case, racial stratification in the effect of a disaster is followed by racial stratification in economic responses.

The majority of people with HIV live in sub-Saharan Africa, where HIV epidemics are generalized. For these epidemics to develop, populations need to be mobile. However, population-level mobility has not yet been studied in the context of the development of generalized HIV epidemics. Here we do so by studying historical migration data from Botswana which has one of the most severe generalized HIV epidemics worldwide; in 2021, HIV prevalence was 21%. The country reported its first AIDS case in 1985 when it began to rapidly urbanize. We hypothesize that, during the development of Botswana's epidemic, the population was highly mobile and there were substantial urban-to-rural and rural-to-urban migratory flows. We test this hypothesis by conducting a network analysis using a historical time series (1981 to 2011) of micro-census data from Botswana. We found 10% of the population moved their residency annually, complex migration networks connected urban with rural areas, and there were very high rates of rural-to-urban migration. Notably, we also found mining towns were both important in-flow and out-flow migration hubs; consequently, there was a very high turnover of residents in towns. Our results support our hypothesis, and together, provide one explanation for the development of Botswana's generalized epidemic.

As Latinos settle in new locations across the U.S., Republican members of Congress (MCs) are increasingly faced with adapting their behavior to incorporate this ideologically variant group. I argue that Republican MCs adapt to changing district demographics through vigilant assessment of the makeup (percent Latino) and preferences (white racial threat attitudes) of their reelection constituency. Using data from 1971 to 2015, I demonstrate that Republican MCs roll-call behavior is increasingly conservative until the district Latino population reaches 37%, where they begin to incorporate Latino interests and reduce their extreme conservative fervor. Between 30-35% Latinos, Republican MCs exhibit the lowest level of dyadic district congruence, illustrating that they are cross-pressured by conservative whites and liberal Latinos within this range. These findings suggest that Republican members of Congress are already adapting to the growing Latino population in their districts in an unexpected manner and will only incorporate Latinos when electorally necessary.

The future of work is a daunting landscape. It is a picturesque route dotted with technologies such as automation, artificial intelligence, and robotics that are reshaping how we work. The specter of Automation leading to joblessness has been haunting us for centuries, although. Automation has been a net creator of jobs. And then, there is the issue of the “gig” economy, where everyone works without being “employed.” The pandemic-induced work from home (WFH) has been mainstreamed.

Previous research documented that midwifery service quality improvements lead to improving maternal and infants' health outcomes. However, little is known about its influence for later-life outcomes including disability. This paper explores the potential effects of early-life exposure to the establishment of midwifery laws across US states on later-life disability outcomes. Midwifery laws were enacted during the late 19 th and early 20 th century and required midwives to gain formal education and training to obtain a license in order to legally practice. We use decennial census data over the years 1970-2000 and implement a difference-indifference method and show that being born in a reform state is associated with significant reductions in various measures of disability, including work disability, cognitive difficulty, ambulatory difficulty, self-care difficulty, and a proxy for severe mental health. We also find significant increases in education, socioeconomic scores, housing wealth, and income. We further discuss the policy implications of the results.

Many Illinois households are eligible for safety net benefits that can help to improve their economic well-being. However, many of those eligible for benefits do not receive them. Program changes and new outreach strategies could help safety net programs reach more families and children, but designing the best interventions requires knowing more about who receives and does not receive assistance. Further, answering that question at the national level isn’t sufficient, because every state has a unique set of policies and implementation approaches, as well as a different starting point in terms of the portions of eligible families currently receiving various benefits. This analysis provides a snapshot of safety net eligibility and program participation rates in Illinois, combining estimates of the numbers of people eligible for benefits in Illinois with actual data on benefit recipients.We provide eligibility and participation rate estimates for seven programs—Temporary Assistance for Needy Families (TANF), Supplemental Security Income (SSI), the Supplemental Nutrition Assistance Program (SNAP), the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC), Public and Subsidized Housing, the Child Care and Development Fund (CCDF), and the Low Income Home Energy Assistance Program (LIHEAP)—and we provide eligibility data for an additional program, the Earned Income Tax Credit (EITC). The analysis rests on detailed estimates of program eligibility produced by the Urban Institute’s ATTIS (Analysis of Transfers, Taxes, and Income Security) microsimulation model.

In recent years, Hispanics in the United States have experienced greater declines in fertility, on the one hand, and sustained higher fertility rates, on the other hand, compared to non-Hispanic groups. Despite considerable attention in the literature, efforts to understand these aggregate trends are hindered by the complex heterogeneity in the Hispanic population. Prior work demonstrates the importance of disaggregating the Hispanic population by nativity and marital status, among other dimensions, in the context of fertility. Yet data constraints create challenges for correctly estimating yearly population counts by nativity, marital status, and other factors not included in U.S. Census population estimates but essential for providing an accurate assessment of Hispanic fertility rates based on vital registration systems. In this chapter, we first discuss important sources of heterogeneity in Hispanic fertility identified in prior literature as well as challenges and potential solutions to correctly estimating variation in Hispanic fertility. Next, we use birth counts from the U.S. vital statistics system and population distributions from the American Community Survey (ACS) adjusted to U.S. Census population totals to estimate Hispanic age-specific fertility rates (ASFR) from 2006–2016 by nativity, region of origin, and marital status. Finally, we demonstrate how decomposition analysis can be applied to Hispanic fertility rates cross-classified by multiple factors over time to better understand the extent to which observed changes in fertility are due to changes in the composition of population sub-groups that have differential childbearing risk.