In this paper, I examine the relationship between patrilocal norms that dictate elderly coresidence between parents and sons, and the sex ratio at birth. I argue that concerns over old age support are critical in explaining excess mortality among daughters. First, I demonstrate that sex ratios and coresidence rates are positively correlated when looking across countries, within countries across districts, and within districts across ethnic groups. Second, in a series of case studies where I exploit natural experiments, I find that sex ratios decline in response to expansions in the availability of pensions but increase when pensions become less reliable.

Over the past several decades, marriage has been increasingly postponed or forgone, while childbearing outside of marriage has become more common (FP-21-24, FP-21-17, FP-21-12). The current profile uses data from the 1979 and 2020 Fertility Supplement of the Current Population Survey to examine differences in the share of women who ever married and the share who ever had a birth by the end of their childbearing years (defined as ages 40-44). This represents the experiences of women born between 1935 and 1939 (part of the Silent Generation) and women born between 1976 and 1980 (part of Gen-X). We consider overall trends and disaggregate by race/ethnicity and by educational attainment.

Most U.S. cities have defined-benefit pensions for their public workers, creating an obligation that exposes sponsoring cities to shortfall risk. Large funding gaps in recent years have required increased pension payments and generated fiscal stress for cities. To analyze the effect of this "pension pressure", I assembled a novel dataset which captures the universe of cities and their pensions in California from 2003 to 2016. I focus on the changes in city unfunded liability contributions. These mandatory, externally determined payments are plausibly exogenous to cities' year-to-year spending needs. Using a first differences empirical specification, I find that cities primarily reduce non-current expenses, specifically capital investment. I also show that cities cut payrolls and employment, with police employment declines specifically. Further, there are accompanying increases in crime rates. These estimates imply that pension pressure impairs local public service provision, with contributions displacing other spending.

Rising inflation in the past year has eroded some of the recent gains nurses in the United States have made in their salaries, according to a study carried out by Simple Nursing. Pay for nursing went up only 1.3% over the past year, while inflation has surged 4.7%. This followed a period in which there was a steady rise in real wages for the profession – between 2012 and 2021 salaries for nurses went up by 27% in the U.S. to more than $76,000, including a 4.2% increase during the first year of the coronavirus pandemic.

In recent years, Topological Data Analysis (TDA) has been used to analyze complex data and provide insights that other research techniques cannot. TDA is a newer form of data analysis which analyzes trends of data from a topological perspective by way of the main visualization tool of persistence diagrams. TDA has been used to measure breast cancer transcriptional DNA, voting patterns in precincts, gerrymandering, and even texture representation. In this paper, we apply TDA to geospatial data from the census to more accurately describe racial segregation among the Black and Hispanic demographics across one hundred cities in America. Our goal was to complete city to city comparisons in 2010 and 2020 as well as compare city similarities over the course of ten years for each race and note the respective trends. Generally, we were able to conclude that larger cities were more likely to exhibit racial shifts in demographic data, while smaller cities did not. However, it was also noted that both demographics contained large city representatives which behaved as smaller cities indicating little shift in racial demographics. In summary, this project represents a first step in uncovering trends in demographic data using TDA. We hope to continue exploring this data set in an effort to expand our understanding of racial segregation in America.

Over the past several decades, marriage has been increasingly postponed or forgone, while childbearing outside of marriage has become more common (FP-21-24, FP-21-17, FP-21-12). The current profile uses data from the 1979 and 2020 Fertility Supplement of the Current Population Survey to examine differences in the share of women who ever married and the share who ever had a birth by the end of their childbearing years (defined as ages 40-44). This represents the experiences of women born between 1935 and 1939 (part of the Silent Generation) and women born between 1976 and 1980 (part of Gen-X). We consider overall trends and disaggregate by race/ethnicity and by educational attainment.

The United States witnessed an unprecedented crime wave in the second half of the twentieth century, with the total index crime rate more than tripling between 1960-1980. Little is known about the causes of this surge in criminal activity across the country. This paper investigates the role played by the Interstate Highway System (IHS), an ambitious federal government project that led to the construction of over 40,000 miles of highways between 1956-1992. Using a staggered difference-in-differences design and a county-byyear panel dataset spanning all US counties between 1960-1993, we find that a highway opening in a county led to a 5% rise in the local index crime. This effect is driven by property crime (namely larceny and motor vehicle theft), while violent crime remained unaffected. Exploring potential mechanisms, we show that the increase in crime could be explained by the positive effect of IHS on local economic development. At the same time, we find that increases in the local law enforcement size and presence in the affected communities mitigated any substantial crime surge induced by the highway construction.

We combine individual data from the 1940 full-count census with death records and other information available on the Family Tree at familysearch.org to create the largest individual dataset to date (17 million) to study the association between years of schooling and age at death. Conditional on surviving to age 35, one additional year of education is associated with roughly 0.4 more years of life for both men and women for cohorts born 1906-1915 and smaller for earlier cohorts. Focusing on the 1906-1915 cohort we find that this association is identical when we use sibling or twin fixed effects. This association varies substantially by place of birth. For men, the association is stronger in places with greater incomes, higher quality of school, and larger investments in public health. Women also exhibit great heterogeneity in the association, but our measures of the childhood environment do not explain it.

The United States has a highly decentralised system of schools, rooted in the nation’s rural beginnings, and there has never been a central governmental agency regulating teachers’ professional status (Sedlak, 1989; Ingersoll & Collins, 2018). This has had important implications for the expansion of its teaching force, and for patterns of segmentation and differentiation within it. In this chapter, we examine these aspects of the teaching profession during the period from the mid-twentieth century to beyond the year 2000. We utilise data from the decennial national census and government publications. In this manner, we are able to identify key steps and stages in the development of teaching as a distinctive profession in the United States, and the manifold ways that it has been segmented. Segmentation has been discernible in multiple dimensions among American teachers, and it has changed over time. Its various facets have included regional differences in professional standing and social status; urban-rural distinctions in the same; distinctions between primary and secondary teachers; and different degrees of professional stature between men and women, and between different racial and ethnic groups. Furthermore, the salience of such lines of segmentation has shifted, largely in response to economic development, market forces in the demand for teachers, and historical patterns of discrimination along lines of gender, race and ethnicity. Altogether, a general process of convergence has made regional differences less important, along with gender distinctions, while urban-metropolitan-rural and racial/ethnic lines of segmentation have become somewhat more noteworthy. These changes reflected larger shifts in the regional and metropolitan organisation of the American economy and its education system since the nineteenth century (Saatcioglu & Rury, 2012).

Background: Numerous studies have documented PM2.5’s links with adverse health outcomes. Comparatively fewer studies have evaluated specific PM2.5 components. The lack of exposure measurements and high correlation among different PM2.5 components are two limitations. Methods: We applied a novel exposure prediction model to obtain annual Census tract-level concentrations of 15 PM2.5 components (Zn, V, Si, Pb, Ni, K, Fe, Cu, Ca, Br, SO42−, NO3−, NH4+, OC, EC) in Massachusetts from 2000 to 2015, to which we matched geocoded deaths. All non-accidental mortality, cardiovascular mortality, and respiratory mortality were examined for the population aged 18 or over. Weighted quantile sum (WQS) regression models were used to examine the cumulative associations between PM2.5 components mixture and outcomes and each component’s contributions to the cumulative associations. We have fit WQS models on 15 PM2.5 components and a priori identified source groups (heavy fuel oil combustion, biomass burning, crustal matter, non-tailpipe traffic source, tailpipe traffic source, secondary particles from power plants, secondary particles from agriculture, unclear source) for the 15 PM2.5 components. Total PM2.5 mass analysis and single component associations were also conducted through quasi-Poisson regression models. Results: Positive cumulative associations between the components mixture and all three outcomes were observed from the WQS models. Components with large contribution to the cumulative associations included K, OC, and Fe. Biomass burning, traffic emissions, and secondary particles from power plants were identified as important source contributing to the cumulative associations. Mortality rate ratios for cardiovascular mortality were of greater magnitude than all non-accidental mortality and respiratory mortality, which is also observed in cumulative associations estimated from WQS, total PM2.5 mass analysis, and single component associations. Conclusion: We have found positive associations between the mixture of 15 PM2.5 components and all non-accidental mortality, cardiovascular mortality, and respiratory mortality. Among these components, Fe, K, and OC have been identified as having important contribution to the cumulative associations. The WQS results also suggests potential source effects from biomass burning, traffic emissions, and secondary particles from power plants.

Faculty and students will receive training in data administration, software platforms for data visualisation and analysis, and identifying data resources at the Data Services workshops. Please use the links provided with each event to register for these sessions. Participants will learn about the various U.S. Bureau of Census surveys and how to use the census.data.gov data platform to access the available demographic data from the surveys. Participants will also learn how to use the library’s Geographic Information System (GIS) tool, Social Explorer, for demographic mapping and IPUMS to collect public use microsample data samples (PUMS).

Coethnics often work in the same industries. How does this ethnic clustering affect individuals’ political loyalties amid industrial growth and decline? Focusing on migrant groups, I contend that ethnic groups’ distribution across industries alters the political allegiances of their members. When a group is concentrated in a growing industry, economic optimism and resources flow between coethnics, bolstering migrants’ confidence in their economic security and dissuading investments in local political incorporation. When a group is concentrated in a declining industry, these gains dissipate, leading migrants to integrate into outside groups with greater access to political rents. Analyses of immigrants near U.S. coal mines in the early 20th century support this theory. This work shows how ethnic groups’ distribution across industries shapes the evolution of group cleavages and illuminates how decarbonizing transitions away from fossil fuels may reshape identity conflicts.

Urban air pollution disproportionately harms communities of color and low-income communities in the U.S. Intraurban nitrogen dioxide (NO2) inequalities can be observed from space using the TROPOspheric Monitoring Instrument (TROPOMI). Past research has relied on time-averaged measurements, limiting our understanding of how neighborhood-level NO2 inequalities co-vary with urban air quality and climate. Here, we use fine-scale (250 m × 250 m) airborne NO2 remote sensing to demonstrate that daily TROPOMI observations resolve a major portion of census tract-scale NO2 inequalities in the New York City-Newark urbanized area. Spatiotemporally coincident TROPOMI and airborne inequalities are well correlated (r = 0.82-0.97), with slopes of 0.82-1.05 for relative and 0.76-0.96 for absolute inequalities for different groups. We calculate daily TROPOMI NO2 inequalities over May 2018-September 2021, reporting disparities of 25-38% with race, ethnicity, and/or household income. Mean daily inequalities agree with results based on TROPOMI measurements oversampled to 0.01° × 0.01° to within associated uncertainties. Individual and mean daily TROPOMI NO2 inequalities are largely insensitive to pixel size, at least when pixels are smaller than ∼60 km2, but are sensitive to low observational coverage. We statistically analyze daily NO2 inequalities, presenting empirical evidence of the systematic overburdening of communities of color and low-income neighborhoods with polluting sources, regulatory ozone co-benefits, and worsened NO2 inequalities and cumulative NO2 and urban heat burdens with climate change.

This paper analyzes the impact of skill-biased technological change (SBTC) on intergenerational education mobility. I set up an SBTC model with an overlapping generations framework, where heterogeneously-skilled households invest in their children's education to make them skilled. Technology incentivizes these investments by creating both pecuniary (higher skill-premium) and non-pecuniary (improved life skills) benefits; it constrains investments among low-income households by increasing inequality. I show there is a critical technology range within which SBTC shocks can increase investments by both high-income and low-income households, improving absolute education mobility. Moreover, the relative increase in transfers can be larger for the low-income group who initially have lower investment levels, which can help their children catch-up. I test the predictions of the model using data from Chetty et al. (2014) which show how college attendance rates of children in U.S. commuting zones (CZs) are linked to the rank of their families in the national income distribution. A technology measure is constructed for each CZ using its share of STEM workers, which I instrument using a Bartik-type IV to deal with endogeneity concerns. From 2SLS estimations, I find that college attendance rates of children from households in the same income rank improve if households are located in higher technology CZs, with the improvement being larger among lower-ranked households. Thus, SBTC is found to improve both absolute and relative intergenerational education mobility.

In December of 2017, President Trump signed the Tax Cuts and Jobs Act of 2017 (TCJA). While the law made several changes to the tax code, one major change was instituting a cap on the amount of state and local tax (SALT) deductions a filer can claim. The SALT cap limits a tax filer’s ability to limit the impacts of state and local taxes on their overall tax burden. This new inability to soften the impact of state and local taxes could cause residents to view states with higher taxes as less attractive. The results presented in this paper showed a state’s top income tax rate and a state’s representative tax burden had a statistically significant negative effect on the probability of a household living in a new state after the SALT cap was implemented. This effect was statistically different than the negative impact of the tax measure before the passing. Suggesting, for households of varying income levels, if a state were to increase the top income tax rate by 10 percentage points the probability of a household moving to that state would decrease, on the low end 0.17 percentage points and on the high end 0.52 percentage points more than if the SALT cap was not in place. Larger impacts were found for the representative tax burden measure, where for a 10% increase in the state tax burden the probability of a household moving to the state would fall by 0.57 percentage points on the low end and 0.87 percentage points on the high end.

Climate change is largely caused by continued use of fossil fuels to provide energy services. Increasingly, given the goal of mitigating climate change, organizations like power utilities are announcing “net-zero” greenhouse gas (GHG) emissions goals that do not necessarily require fossil fuel-fired facilities to mitigate their emissions or close. If paired with carbon dioxide removal (CDR), ongoing emissions could theoretically coexist with net-zero goals. CDR, however, is resource intensive, regardless of removal pathway. One common question is whether tree planting could be a low-impact pathway to compensate for ongoing or legacy GHG emissions, since trees take up atmospheric CO2 and store the carbon as wood. Although planting trees might sound like a benign climate strategy, the need for additionality and permanence means that forestry-based CDR has immense land requirements at climate-relevant scales. To contextualize this land intensity, this case study evaluates how much land would be required to counterbalance a utility's emissions from a large coal-fired power plant in Georgia with forest-based CDR. Compensating for 1 year of plant emissions would require permanent industrial forestation of all land in the plant's host county that is not already forested or developed (with buildings, roads, etc.), with a 30-year lead time-highlighting a key challenge of relying on tree planting to meet climate goals. Readers engaging this case will be able to discuss land use requirements of relying on compensatory forestry-based CDR for net-zero emissions goals, in addition to being prepared to replicate this analysis for other power plants or emitters.

We offer new evidence on the dynamics of wealth holding in the United States over the Civil War decade based on a hand-linked random sample of wealth holders drawn from the 1860 census. Despite the wealth shock caused by emancipation, we find that patterns of wealth mobility were broadly similar for northern and southern residents in 1860. Looking at the determinants of individual wealth holding in 1870, we find that the elasticity with respect to 1860 wealth was quite low in both regions-consistent with high levels of wealth mobility.

Over the past half-century, while self-employment has consistently accounted for around one in ten of the United States workforce, its composition has changed. Since 1970, industries with high startup capital requirements have declined from 53% of self-employment to 23%. This same time period also witnessed declines in "hometown" local entrepreneurship and the probability of the self-employed being among top earners. Using 2016 data, we show that high startup capital requirements are linked with lower profitability at small scales. The transition away from high startup capital industries appears most closely linked to changes in small business production functions and less due to advantageous reallocation to other opportunities, growth in returns-toscale among large businesses, or a worsening of financing conditions and debt levels.

Consumers with higher income often spend more on luxury goods. As a result, lower-income consumers who seek to increase their perceived income status may be motivated to purchase conspicuous luxury goods. They may also desire to emulate the visible consumption displayed by their wealthier peers. Using a unique vehicle financing dataset, we find that consumers with lower credit scores value vehicle brand prestige more than average consumers. The stronger preferences for prestige lead non-prime consumers to purchase more expensive vehicles than they otherwise would have. We find evidence that the preferences for prestige are driven both by status signaling and peer emulation motives. Furthermore, we show that larger vehicle purchases financed by auto loans lead to worse loan performance and credit standing for non-prime consumers.

The Affordable Care Act’s Medicaid expansion to individuals with adults under 138 percent of the federal poverty level led to insurance coverage for millions of Americans in participating states. This study investigates Medicaid expansion’s potential spillover participation in the Supplemental Nutrition Assistance Program (SNAP; formerly the Food Stamp Program). In addition to providing public insurance, the policy connects individuals to SNAP, affecting social determinants of health such as hunger. We use difference-in-differences regression to estimate the effect of the Medicaid expansion on SNAP participation among approximately 414,000 individuals from across the United States. The Current Population Survey is used to answer the main research question, and the SNAP Quality Control Database allows for supplemental analyses. Medicaid expansion produces a 2.9 percentage point increase (p = 0.002) in SNAP participation among individuals under 138 percent of federal poverty. Subgroup analyses find a larger 5.0 percentage point increase (p = 0.002) in households under 75 percent of federal poverty without children. Able-Bodied Adults Without Dependents (ABAWDs) are a category of individuals with limited access to SNAP. Although they are a subset of adults without children, we found no spillover effect for ABAWDs. We find an increase in SNAP households with $0 income, supporting the finding that spillover was strongest for very-low-income individuals. Joint processing of Medicaid and SNAP applications helps facilitate the connection between Medicaid expansion and SNAP. Our findings contribute to a growing body of evidence that Medicaid expansion does more than improve access to health care by connecting eligible individuals to supports like SNAP. SNAP recipients have increased access to food, an important social determinant of health. Our study supports reducing administrative burdens to help connect individuals to safety net programs. Finally, we note that ABAWDs are a vulnerable group that need targeted program outreach.