This assessment looks at affordability at the levels of both individual households and communities. In the household analysis, we calculate several affordability indicators using census and utility rate survey data. The data and methods used in developing the indicators are described in Section 2. These indicators, functions of water cost (reported or calculated) and income (plus or minus other expenses), allow us to explore their geographic and demographic characteristics via regression and latent class analysis. Section 3.1 describes our findings at the household level. At the community level, we explore financial capability via funding needs and expenses surveys conducted by the EPA, American Water Works Association (AWWA), and Census of Governments for the whole state. Sections 3.2 and 3.3 describe our findings at the community and utility levels. We compiled work about the affordability of private wells and septic systems in order to provide a more complete picture across the state, from urban to suburban to rural residents. These results are explored in Section 3.4. We also interviewed a range of relevant stakeholders, with the expectation that their experience would provide important context for the technical analyses. We believe this context, provided in Section 3.4, will be valuable to policymakers in developing meaningful and sustainable solutions to the statewide issues documented in the quantitative analyses.

Differential privacy revolutionizes the way we think about statistical disclosure limitation. A distinct feature of differential privacy is that the probabilistic mechanism with which the data are privatized can be made public without sabotaging the privacy guarantee. In a technical treatment, this paper establishes the necessity of transparent privacy for drawing unbiased statistical inference for a wide range of scientific questions. Uncertainty due to privacy may be conceived as a dynamic and controllable component from the total survey error perspective. Mandated invariants constitute a threat to transparency when imposed on the privatized data product through "post-processing", resulting in limited statistical usability. Transparent privacy presents a viable path towards principled inference from privatized data releases, and shows great promise towards improved reproducibility, accountability and public trust in modern data curation.

This paper argues that systemic racial inequalities undermine support for democracy in the United States. Focusing on exposure to information about racial inequalities in the context of a survey experiment, we present causal evidence that support for democracy declines when people are made aware of (or reminded about) systemic inequalities. Then, using observational data we show that negative associations between racial inequality and democratic support are present beyond the context of the survey experiment. We develop and evaluate two theoretical mechanisms linking exposure to systemic inequality and attitudes toward democracy. We find that some respondents see systemic inequality as evidence that democracy is ineffective (poor performance mechanism), while others legitimate the systemic inequalities they encounter and dislike the egalitarian aspirations of democracy (hierarchy enhancement mechanism). Analysis of qualitative data from the survey experiment illuminate these mechanisms at work. Together the findings suggest that dismantling hierarchy could reinvigorate Americans' democratic commitments.

Environmental tobacco smoke (ETS) increases the risk of mortality among nonsmokers. Yet, few studies have examined this association among racial/ethnic minorities or among people with less education or income. We assessed self-reported ETS exposure at home among never smoking participants (n = 110,945) of the 1991–2010 National Health Interview Surveys. Deaths through 2015 were identified by the National Death Index. Hazard ratios (HRs) and 95% confidence intervals (CIs) for all-cause and cause-specific mortality were estimated using Cox proportional hazards regression models with age as the underlying time metric and adjusted for sex, race/ethnicity, education, household income, body mass index, region of residence, and survey year. We further stratified all-cause mortality analyses by race/ethnicity, household income, and education. Relative to no ETS at home, every day exposure was associated with higher risk of all-cause mortality (HR = 1.33, 95%CI: 1.23, 1.45), with similar HRs observed across strata of education and income. HRs were similar among non-Hispanic Black (HR = 1.28, 95%CI: 1.08, 1.53) and non-Hispanic White adults (HR = 1.34, 95%CI: 1.21, 1.48) although somewhat higher among Hispanic adults (HR = 1.65, 95%CI: 1.29, 2.10; P for pairwise comparison = 0.04). ETS exposure at home is an important contributor to mortality across strata of race/ethnicity, education, and income in the US.

Multi-region firms increasingly dominate the U.S. economy. I study the implications of this trend for labor market inequalities. I document that multi-region service firms account for most of the rise in wage inequality since the 1980s, and provide evidence on the uneven nature of their spatial expansion: larger firms operate establishments in more locations, while hiring more skilled labor and paying higher wages in spatially-concentrated headquarters. I integrate this structure into a general equilibrium model, in which (a) firms open branches to serve local markets; (b) the output of headquarters workers is non-rival across branches; (c) firms have wage-setting power. The resulting wage distribution depends on the full network of firm spatial activity, and inequality rises with firms’ geographical scope. The model admits tractable aggregation despite its complex micro-structure. I estimate it for 391 U.S. labor market areas and infer frictions to spatial expansion from the universe of HQ-branch linkages. Quantitatively, the decline in these frictions since the 1980s can account for multiple trends in U.S. labor markets, including rising inequality across establishments – between and within firms – and higher inequality and segregation across space.

Using multiple decrement life tables based on U.S. marriage and mortality rates from 2019, this paper projects a lifetime chance of marrying for non-Hispanic, single-race White and Black women. Projections show 86.2% for White women, and 61.7% for Black women, eventually marrying for a cohort born and living through conditions prevailing in 2019 (before the COVID-19 pandemic). These projected rates represented continued steep declines in marriage, along the lines observed in recent decades. The method described here is applicable to other family events, and may be readily extended to marriage for other populations as well. Although the interplay of historical social, economic, and political factors behind patterns of marriage and family structure are complex, Black-White differences those patterns are best understood as a consequence rather than cause of racial inequality (Bloome and Ang 2020; Williams and Baker 2021). With regard to marriage specifically, Black-White differences in marriage rates among women are associated with unbalanced sex ratios in marriage markets (Cohen and Pepin 2018; Guzzo 2006), the economic prospects of Black men (Lichter, Price, and Swigert 2020; Ruggles 2021), racial intermarriage involving Black men (Crowder and Tolnay 2000), and perceived economic barriers to marriage (Gibson-Davis, Edin, and McLanahan 2005). (For a recent review, see Council (2021).) With those references to related literature above in lieu of a substantial literature review, I move to present a descriptive analysis of recent marriage rates among Black and White women, focusing on the lifetime prevalence of marriage and using a multiple decrement life table approach. The estimates here use 2019 data, from before the COVID-19 pandemic, which is the year of the most recent complete life tables available (see below), with mortality rates from the National Center for Health Statistics and first marriage estimates from the American Community Survey. This updates an analysis conducted in 2015 (Cohen 2015b).

Purpose To examine characteristics associated with disparities in digital access (i.e., access to high-speed Internet via a computer or smartphone) in American rural and urban households given that digital access has a direct impact on access to telemedicine-based services. Methods Using the 2019 American Community Survey, we analyzed the proportions of geographic area, race/ethnicity, and socioeconomic status according to device and high-speed Internet access. Maximum likelihood logit estimators estimated how these factors influenced device and high-speed Internet access. Findings Of 105,312,959 households, 32.29% were without a desktop or laptop computer with high-speed Internet (WDW), 21.51% were without a smartphone with a data plan for wireless Internet (WSW), and 14.02% were without any digital access (WDA). Nonmetropolitan households were significantly more likely to be WDA than metropolitan households (odds ratio [OR] = 1.87; 95% confidence interval [CI]: 1.83-1.91). Relative to non-Hispanic Whites, non-Hispanic Blacks (OR = 1.60; 95% CI: 1.56-1.64), American Indian or Alaska natives (OR = 2.00; 95% CI: 1.82-2.19), or Hispanics (OR = 1.70; 95% CI: 1.66-1.74) were significantly more likely to be WDA. When compared to households with private health insurance coverage, households WDA were significantly more likely to have no insurance (OR = 2.44; 95% CI: 2.36-2.53) or public insurance coverage (OR = 3.78; 95% CI: 3.70-3.86). Households with any digital access reported higher income and more family members living at home. Using the same predictors, similar findings were reported for households WDW or WSW. Conclusions Significant disparities in digital access exist among nonmetropolitan households, racial/ethnic minority households, and lower-income households. The lack of digital access has implications for the accessibility of health care services via telemedicine and thus could exacerbate health disparities.

Agrarian distress—the experience wherein sustaining an agricultural livelihood becomes increasingly challenging—is well documented in South Asia. Another regional trend is the feminization of agriculture or an increase in women's work and decision-making in agriculture. Scholars have recently linked these two phenomena, demonstrating that agrarian distress results in the movement of men out of agriculture, driving women into the sector. Yet what remains underexplored is the relationship between climate change, a contributor to agrarian distress, and the feminization of agriculture. To examine this, we link socioeconomic and demographic data from India, Bangladesh, and Nepal to high-resolution gridded climate data. We then estimate a set of multivariate regression models to explore linkages between recent temperature and precipitation variability from historical norms and the likelihood that a woman works in agriculture. Results suggest that hotter-than-normal conditions in the year prior to the survey are associated with an increased likelihood of working in agriculture among women. This relationship is particularly strong among married women and women with less than primary education. While more research is needed to fully understand the mechanisms between climate change and the feminization of agriculture, our findings suggest a need for gender-sensitive climate change adaptation strategies.

This study analyzed the access to plumbed water and the quality of the water in Native American communities in Nevada. Census microdata were used to assess trends in household water access along with data on household characteristics sourced from the Integrated Public Use Microdata Series. Water quality reports were downloaded from the Environmental Protection Agency’s Enforcement and Compliance History Online website. Individual compliance reports were accessed to identify health-based violations and violations that were not reported or monitored. The nonparametric Spearman’s rho test was used to estimate trends. The analysis of the number of Native American community members with no access to plumbing increased from 1990 to 2019 (rs = 0.56, p = 0.0081). The overall percentage of Native American homes without indoor plumbing in Nevada was 0.67, which is higher than the reported 0.4 for the United States. The population affected by a lack of access to either plumbing, hot water, a shower, or a toilet increased as the number of family members increased. A growing trend (rs = 0.71, p = 0.018) was observed in the number of Safe Drinking Water Act violations registered by the EPA in water facilities serving Native Americans. The health-based violations most often registered were volatile organic chemicals and Revised Total Coliform Rules. The significance of these findings is highlighted not only in terms of the quality of life of the household members, but other health determinants such as the correlation between the access to clean, safe water and dissemination of diseases.

Using data on U.S. adults from the National Health Interview Survey (NHIS), we estimate the causal income elasticity of tanning bed usage conditional upon use. While controlling for individual characteristics , we employ instrumented probit and count data estimation to show that tanning bed usage is a normal good that is a necessity for all adults, women and men alike. Results suggest an income elasticity magnitude of 0.823 for all adults, which implies that a 10 percent increase in instrumented income increases tanning bed usage by 8.23 percent. When examining 18-25 year olds, the magnitude increases to 1.563-a 10 percent increase in instru-mented income causes a 15.63 percent increase in tanning bed usage. The findings add to research on health behaviors and suggest that policymakers wanting to discourage tanning bed usage may have to tax consumption considerably or enhance public health campaigns to prevent and curb usage.

Envisioning a future 100% electrified transportation sector, this paper proposes a model framework that uses socio-economic, demographic, and geographic data to estimate electric energy demand from commuter traffic. Additionally, we explore the possible mode choices of each individual, which allows to create mode-mix scenarios for the entire population. We quantify the electric energy demand for each scenario using technical specifications of state-of-the-art battery and electric drives technology in combination with different charging scenarios. Using data sets for New York City, our results highlight the need for infrastructure investments, the usefulness of flexible charging policies and the positive impact of incentivizing micromobility and mass-transit options. Our model and results are publicly available as interactive Dashboard under tecnyc.herokuapp.com.

Objectives. To provide adjusted rates of self-reported receipt of the influenza vaccine in the 2018–2019 flu season among adults in large metropolitan, medium and small metropolitan, and nonmetropolitan areas of the United States by age group, gender, and race. Methods. We queried the 2019 National Health Interview Survey for respondents aged 18 years and older. To provide national estimates of influenza vaccination coverage, we performed sample-weighted multivariable logistic regressions and predicted marginal modeling while adjusting for age, gender, race/ ethnicity, and urban–rural household designation. Results. After weighting, 48.1%, 46.2%, and 43.6% of adults from large metropolitan, small and medium metropolitan, and nonmetropolitan areas, respectively, received the influenza vaccine. Additionally, there was a trend toward declining influenza vaccination status from large metropolitan to rural areas in all age groups, both genders, and multiple racial/ethnic groups. Conclusions. Self-reported influenza vaccination rates were lower in rural than in urban areas among adults of all age groups and both genders. Using community leaders for health promotion, augmentation of the community health care workforce, and provision of incentives for providers to integrate influenza vaccination in regular visits may expand influenza vaccine coverage.

The Affordable Care Act's Medicaid expansion ushered in substantial increases in enrollment in the public insurance program. I analyzed rural–urban differences in access to health insurance, financial access to primary care providers, use of preventive care, and use of emergency department for medical reasons that did not lead to hospitalization. Low-income rural residents were found to have greater reduction in likelihood of uninsurance than their urban counterparts. While an increase in the likelihood of routine check-ups was found to be significant only among rural residents, a decrease in the likelihood of repeated visits to the emergency departments for nonurgent reasons was only significant among the urban population. I highlight the importance of understanding rural experiences to reduce rural–urban health disparities.

Defined benefit (DB) pensions and Social Security are important resources for financing retirement in the USA. However, these illiquid, nonmarket forms of wealth are typically excluded from measures of net worth. To the extent that these broadly held resources substitute for savings, measures of wealth inequality that do not account for DB pensions and Social Security may be overstated. This article develops an alternative, expanded wealth concept, augmenting net worth data from the Survey of Consumer Finances with estimates of DB pension and expected Social Security wealth. We explore the concentration of wealth among households ages 40–59 and find that (i) including DB pension and Social Security results in markedly lower measures of wealth concentration and (ii) trends toward higher wealth inequality over time, while moderated, are still present. Simulation exercises show that reductions in Social Security benefits significantly increase wealth concentration for the youngest birth-year cohorts.

We investigate the importance of co-ethnic networks and diversity in determining immigrant inventors’ settlements in the US by following the location choices of thousands of them across counties during the Age of Mass Migration. To do so, we combine a unique USPTO historical patent dataset on immigrants who arrived as adults with Census data, and exploit exogenous variation in both immigration flows and diversity induced by former settlements, WWI and the 1920s Immigration Acts. We find that co-ethnic networks play an important role in attracting immigrant inventors. Yet, we also find that immigrant diversity acts as an additional significant pull factor. This is mainly due to externalities that foster immigrant inventors’ productivity.

Using newly digitized U.S. city-level data on hospitals, we explore how pandemics alter preferences for healthcare. We find that cities with higher levels of mortality during the Great Influenza of 1918-1919 subsequently expanded access to hospital care by more than less affected locations. This effect persisted to 1960 and was driven by increases in non-government hospitals. Growth responded most in richer cities, exacerbating existing inequalities in access to healthcare. We do not find evidence that government-run hospitals or other types of city-level spending related to healthcare responded to pandemic intensity, suggesting that large health shocks do not necessarily lead to increased public provision of health services.

Housing costs are key in understanding real income differences across space and time. Standard measures of housing costs do not account for availability differences, where some housing varieties are available in certain cities or time periods but not others. When households have idiosyncratic preferences over housing units, the set of available housing varieties in a city matters. This paper develops theoretically-founded housing price indices to measure housing costs that account for availability differences.

This paper assesses the causal impact of greater market access on demographic transition during the latter half of the 19th century in the United States. We construct new measures of fertility changes and measures of railroad access at the county level from 1850 – 1890. We are able to document market-access-induced changes in fertility due to both extensive margins (shifts in occupations with different average fertility rates) and intensive margins (changes in fertility within each occupation class). Both our theoretical model and empirical results suggest that declining fertility in counties mainly occurred through extensive margins. We further discover that fertility changes occurred mainly through strengthening patterns of specialization, rather than through greater industrialization or urbanization, suggesting that demographics diverged within the United States during this period.

Using data on the value of Federal Housing Administration (FHA) mortgage insurance between 1935 and 1939, I estimate the effect of the agency's program on racial disparities in home ownership and home values. The distance between an FHA office and counties within its jurisdiction is used as an instrument. I find that insurance activity had a negligible effect on the racial gap in home ownership and a sizable effect on the gap in home values. Results suggest that while African American households continued to acquire homes, they may have chosen lower-priced properties, as they lacked the same access to credit as White buyers.

This paper describes a fully customizable open source method to create linked origin-destination data on commuting flows by mode at the Census tract scale by combining LODES and ACS data from the US Census Bureau. With additional work, the method could be scaled to the entire US (with a small number of exceptions) for every year from 2002 to 2019. For demonstration purposes, the paper applies this method to 2015 commuting flows in Cook County, Illinois. At an aggregate scale, the results of this application show that commuting by all modes is dominated by travel to large regional employment centres. However, the pattern is more localised for the walking mode, and focused along corridors of mode-specific infrastructure investment for the cycling and transit modes, as might be expected. The auto and work from home modes demonstrate the most distributed pattern of travel, revealing more instances of commuting to regional sub-centres than the other modes.