Can low-quality investments in schooling displace the creation of higher-quality schools in the long run? I investigate whether Mexico's rapid expansion of rural education during the 1920s successfully promoted human capital acquisition. By combining newly digitized schools data with census samples from 1930 and 1960, I find that Mexico's first major expansion in public education increased literacy rates and language homogenization, but did not induce primary school completion. Through a difference-indifferences analysis, I first show that rural schools achieved short-run education goals central to Mexico's nation-building efforts: by 1930, treated cohorts were up to 10% more likely to be literate and, among indigenous communities, up to 20% more likely to speak Spanish and 4% less likely to speak an indigenous language. I then show that while literacy gains persist into 1960, other long-run education measures suggest a lack of broader human capital growth. Affected cohorts were more likely to have attended but less likely to have completed primary school. These findings highlight the potential drawbacks of rapid, low-quality investments in human capital: the rural school program increased literacy in the short run, but without additional public investments in education, affected cohorts may have had fewer opportunities to complete primary education.

This paper analyses the processes through which racially exclusionary policies lead to lower educational outcomes for indigenous population groups in racialised and colonial settings. Focusing on Colombia and Mozambique, we show that for much of the 20th century indigenous people were unable to access the same schooling as the non-indigenous population. Most indigenous children did not advance beyond very low-quality forms of education in schools run by Catholic missions. This, together with much lower public investments in the education of indigenous peoples, put indigenous children at a comparative disadvantage for the accumulation of human capital. We show this by constructing new estimates of literacy and primary education completion rates for the different ethnic groups in Colombia and Mozambique over the 20th century. In accordance with our argument, we find systematic differences in the accumulation of human capital for the indigenous and non-indigenous populations respectively.

With 43 million families living in apartments, the highest level in half a century, renting is popular even among high-earners who are able to buy but prefer to rent their home instead. According to the most recent analysis of IPUMS data from RentCafe [1] shows that the number of renters with annual incomes of over $150,000 grew by 82% between 2015 and 2020, faster than renters overall. There are now 2.6 million high-earners living in rentals in the U.S. and among them are many millionaire renters. High-income renters earning $150,000 or more saw rapid growth of 82% in five years — the most significant increase among all income groups — followed by renter households with annual incomes between $100,000 and $150,000. At the same time, middle-income renters grew at a slower pace, but still posted double-digit increases. The only segment to register a drop was that of households earning less than $50,000, which decreased by 11.2%. This is explained by low-income renters moving in with family members when the pandemic started, as well as households whose earnings grew and transitioned to higher income groups.

U.S. HIV diagnoses disproportionately affect Non-Hispanic Black (NHB) and Hispanic gay and bisexual men. Using data from the National Health Interview Survey (2013-2018), we examined race and ethnicity and primary care access, an HIV prevention resource, among gay and bisexual men. The explanatory variable was NHB, Hispanic or Non-Hispanic White (NHW). Outcomes were primary care-specific usual place of care (potential access) and saw general doctor <12 months (realized access). We used multivariable logistic regression, adjusting for individual sociodemographic characteristics, health status, and care barriers. In sensitivity analysis, we examined general access (any place/doctor) and subgroups (1) NHB (2) has usual place of care. The sample included 1,858 adult, gay and bisexual men (unweighted). Nearly one-third self-identified as NHB or Hispanic. Compared to NHW men, NHB and Hispanic men were younger, with lower household income, and more care barriers (p < 0.05). NHB and Hispanic men had lower realized access (aOR 0.7058, p = 0.030) than NHW men. Potential access was lower for NHB only (versus NHW) and, among those with any usual place of care, NHB and Hispanic men versus NHW men. Lower primary care access for NHB or Hispanic, rather than NHW, gay and bisexual men, may reduce HIV prevention access.

Why has voter turnout in the United States not increased proportionally with educational attainment over time? Relative education theories have attempted to answer this question by highlighting how the value of individuals’ education may be influenced by the educational levels achieved by others. For instance, individuals may attain a higher level of education compared to previous generations, but the relative value of their education may not improve if society as a whole also achieves higher levels of education. Thus, this increased educational attainment may have little influence on voter turnout. Using a new measure of relative education and incorporating more recent post-2000 data, this research finds that while the relative education model explains the education–turnout relationship prior to 2000, since then individuals with a higher absolute level of education have been more likely to vote, regardless of the relative value of their education. The rise in voter turnout over the past two decades could be attributed to this increase in the absolute level of education.

This paper analyzes the employment dynamics of households in the U.S. during 2020, the first year of the COVID-19 pandemic. Focusing on couples’ behavior, the empirical analysis uses data from the Current Population Survey (CPS) to build linear regressions with employment indicators as dependent variables, and months before and during the pandemic as independent variables. The process examines different sub-samples of the population, controlling for education level, occupation-based flexibility and if there are children in the households. The major findings are that women sustained substantially higher unemployment rates than men, and that couples were not able to coordinate their labor supply, suffering strong exogenous correlated shocks. The software used during the empirical analysis was R.

Medicaid expansion narrowed racial and ethnic disparities in health coverage, but few studies have explored differential impact by exposure to structural racism. We analyzed data on historical residential redlining in US metropolitan areas from the Mapping Inequality project, along with data on uninsurance from the American Community Survey, to test whether Medicaid expansion differentially reduced uninsurance rates among nonelderly adults exposed to historical redlining. Our difference-in-differences analysis compared uninsurance rates in Medicaid expansion and nonexpansion states both before (2009-13) and after (2015-19) the state option to expand Medicaid pursuant to the Affordable Care Act took effect in 2014. We found that Medicaid expansion had the greatest impact on lowering uninsurance rates in census tracts with the highest level of redlining. Within each redline category, there were no significant differences by race and ethnicity. Our results highlight the importance of considering contextual factors, such as structural racism, when evaluating health policies. States that opt not to expand Medicaid delay progress toward health equity in historically redlined communities.

How did the adoption of reform-style government affect socioeconomic inequality in U.S. cities during the Progressive Era? The conventional wisdom describes the reforms of this time as reflecting racist and nativist impulses and primarily benefiting white business owners. However, political science work offers theoretical reasons to expect more nuanced redistributive effects of reform. We study the impact of reform lever-aging deanonymized census records, newly digitized municipal budgets, and reform adoption dates across 455 U.S. cities during 1900-1940. Using a two-way fixed effects design, we document the impact of Progressive municipal government on the relative socioeconomic well-being of black, immigrant, and working-class residents compared to whites, natives, and business elites. We find that inequality increased only modestly in reformed cities, with no significant differences in public spending. Our results challenge the dominant narrative that the reforms of this era produced large increases in socioeconomic inequality.

The Blue Cross Blue Shield of Massachusetts Foundation (the Foundation) recognizes that structural racism is a public health issue and that access to affordable, quality health care is a racial and social justice issue.In 2021, the Foundation published a primer on health disparities in Massachusetts to serve as a foundational resource to broaden collective understanding of racial and ethnic health inequities and disparities in the Commonwealth. The primer showed that while disparities in health outcomes across racial and ethnic groups are often narrower in the Commonwealth than they are in the nation, clear disparities persist. The Foundation engaged Manatt Health to develop a vision and proposed plan for action—collectively a Health Equity Action Plan—for achieving a racially and ethnically equitable health care delivery system in Massachusetts. To inform the development of the Health Equity Action Plan, Manatt facilitated two focus groups in the spring of 2023 and conducted a state and national landscape scan between February 2023 through April 2023 of over 100 research articles, reports, and organizational policies/practices to identify best practices and examples for operationalizing and achieving such a system. The landscape scan also includes examples identified through stakeholder interviews conducted by Manatt in the summer/fall of 2023 with close to 40 stakeholders representing diverse perspectives on Massachusetts’ health care delivery system and the national health equity landscape.The landscape scan, interviews, and consumer focus groups reinforced our understanding that the health care delivery system alone can only go so far. Long-lasting, systemic change requires action from all of government (across agencies and areas of focus), health care providers, health plans, the social service sectors, philanthropy, and other stakeholders. The focus of this work is on racial and ethnic inequities in the health care delivery system and therefore can be considered a first phase in a larger system-wide effort to eliminate all inequities that affect people’s health.This Health Equity Action Plan Toolkit (Toolkit) includes an illustrative set of interventions, policies, and programs identified through the landscape scan and interviews that providers, health care delivery system leaders, and other implementation stakeholders can deploy to help achieve a racially and ethnically equitable system in Massachusetts.

Anaemia is a concerning global public health issue and it has a higher prevalence in developing countries, where it usually relates to the population’s socioeconomic status. African and South-East Asian countries are the most affected. In Nigeria, anaemia has a high prevalence among women and children. Anaemia is a severe nutritional condition that affects most young children, girls and women menstruating, pregnant and postpartum women and elderly people. Inadequate intake or absorption of nutrients (e.g. iron, vitamin B12, folate), parasitic infections, inflammations, bleeding (e.g. heavy menstruation) and pregnancy problems can all cause anaemia. Left untreated anaemia can have serious health consequences. The purpose of this study is to examine the prevalence of anaemia, test hypotheses and assess the correlations between anaemia, age and different socioeconomic factors among pregnant and non-pregnant Nigerian women, aged 15-49. Methodology This is a quantitative correlational study. The 2018 Nigeria Demographic and Health Survey (NDHS) was used for the current research. Permission was granted from the Demographic and Health Surveys (DHS) Program to download the datasets. The 2018 NDHS was a cross-sectional study which covered all of Nigeria. This provided updated national sociodemographic, socioeconomic and health indicators estimates. 4 41821 girls and women of reproductive age, 15-49, were interviewed but only 14750 girls and women were screened for anaemia. Descriptive and inferential statistical tests were used to analyse the women’s dataset, trying to make predictions about the population. Because the variables were categorical, the chi-square test and Spearman’s correlation were used to check the relationship between anaemia, age and different socioeconomic characteristics such as highest educational level, literacy, employment, region, type of place of residence (urban/rural areas) and wealth index for urban/rural areas. P-values < 0.05 were interpreted as statistically significant. Results A total of 8557 women, out of 14750, were anaemic, a prevalence of 58%. A total of 5875 anaemic women could not read at all or they could read only partially and 4394 anaemic women had no education or had primary education only. The total number of anaemic women (3518 women) living in wealthy areas (richer and richest) was higher compared to the total of 3372 anaemic women from poor areas (poorest and poorer). Most women suffering from anaemia were from rural areas, comprising 5288 women. Most of the anaemic women were working, a total of 5504 women, and a total of 4909 anaemic women were living in the North regions of Nigeria. Most of the anaemic women (5850 women) were aged 15-34. Chi-square tests (p<0.05) showed statistically significant correlations between anaemia and region, type of place of residence and employment. Spearman’s correlation (p<0.05, r s <0.2) indicated that there is a statistically significant weak positive correlation between anaemia and the highest educational level, literacy and wealth index for urban/rural areas. However, there is no statistically significant correlation between anaemia and age (p>0.05). Conclusions 58% of the women tested for anaemia were anaemic and there are correlations between anaemia and different socioeconomic determinants. These findings highlight that the prevalence of anaemia in women is a concern in Nigeria and policymakers should adopt strategies to reduce it.

Transit systems are instrumental in reducing vehicle miles travelled and greenhouse gas (GHG) emissions. The transitway program in the Twin Cities, initially focused on dedicated right of way (ROW), has seen newer forms such as mixed traffic and managed lanes emerge. Understanding the impact of different ROWs on ridership and emissions is critical for future planning. This research project examined the influence of dedicated ROW on transit ridership and GHG emissions reduction. With data from 78 US rail transit and BRT routes, we applied the gradient boosting decision tree method to assess the impact of four ROW types and other factors on ridership and GHG emissions. Transit routes with less traffic interference attract substantilly more passengers. An upgrade from mixed traffic to semi-exclusive ROW could see a yearly ridership increase of 70,000, while moving from semi-exclusive to exclusive could add 3.68 million passengers annually. Apart from ROW, number of stops, commence year of the route, population density, signal priority, and several other factors significantly influence ridership. Upgrading ROW has substantial GHG emission reduction benefits, especially with increased usage of electric BRT vehicles. Improving ROWs can notably enhance transit route performance in terms of ridership and GHG reductions. Strategies like dedicated transit lanes, smart traffic management systems, and enhancing service frequency can boost the efficacy of transit routes. It's also pivotal to focus on areas with sufficient population and network density. Implementing a larger share of electric bus vehicles can further amplify emission reductions. While increasing ridership and reducing carbon emissions through enhanced ROWs is beneficial, a comprehensive cost-benefit analysis involving all stakeholders is vital before allocating a dedicated ROW to any transit route.

School connectedness, a construct indexing supportive school relationships, has been posited to promote resilience to environmental adversity. Consistent with prominent calls in the field, we examined the protective nature of school connectedness against two dimensions of early adversity that index multiple levels of environmental exposure (violence exposure, social deprivation) when predicting both positive and negative outcomes in longitudinal data from 3,246 youth in the Fragile Families and Child Wellbeing Study (48% female, 49% African American). Child and adolescent school connectedness were promotive, even when accounting for the detrimental effects of early adversity. Additionally, childhood school connectedness had a protective but reactive association with social deprivation, but not violence exposure, when predicting externalizing symptoms and positive function. Specifically, school connectedness was protective against the negative effects of social deprivation, but the effect diminished as social deprivation became more extreme. These results suggest that social relationships at school may compensate for low levels of social support in the home and neighborhood. Our results highlight the important role that the school environment can play for youth who have been exposed to adversity in other areas of their lives and suggest specific groups that may especially benefit from interventions that boost school connectedness.

Objectives Online reviews provided by users of assisted living communities may offer a unique source of heretofore unexamined data. We explored online reviews as a possible source of information about these communities and examined the association between the reviews and aspects of state regulations, while controlling for assisted living, county, and state market-level factors. Design Cross-sectional, observational study. Setting and Participants Sample included 149,265 reviews for 8828 communities. Methods Primary (eg, state regulations) and secondary (eg, Medicare Beneficiary Summary Files) data were used. County-level factors were derived from the Area Health Resource Files, and state-level factors from the integrated Public Use Microdata series. Information on state regulations was obtained from a previously compiled regulatory dataset. Average assisted living rating score, calculated as the mean of posted online reviews, was the outcome of interest, with a higher score indicating a more positive review. We used word cloud to visualize how often words appeared in 1-star and 5-star reviews. Logistic regression models were used to determine the association between online rating and a set of community, county, and state variables. Models were weighted by the number of reviews per assisted living bed. Results Overall, 76% of communities had online reviews. We found lower odds of positive reviews in communities with greater proportions of Medicare/Medicaid residents [odds ratio (OR) = 0.986; P < .001], whereas communities located in micropolitan areas (compared with urban), and those in states with more direct care worker hours (per week per bed) had greater odds of high rating (OR = 1.722; P < .001 and OR = 1.018, P < .05, respectively). Conclusions and Implications Online reviews are increasingly common, including in long-term care. These reviews are a promising source of information about important aspects of satisfaction, particularly in care settings that lack a public reporting infrastructure. We found several significant associations between online ratings and community-level factors, suggesting these reviews may be a valuable source of information to consumers and policy makers.

We examine one of the secondary effects of the granting of Permanent Normal Trade Relations (PNTR) to China in October 2000: lower than expected house price appreciation. We consider housing prices for 2,800 US counties in a panel data setting for the years 1990 to 2020. We find that the 2000 PNTR trade event caused house prices to appreciate 6 to 8 percent less in highly trade-exposed counties within 2 to 3 years of the trade event and that the slower appreciation persisted to 2020. The size of the trade impact is highly robust to various sensitivity checks.

I investigate racial disparities in infant mortality in the United States and consider how local socioeconomic conditions have shaped these disparities over time, from 1962 to 2016. Initial investigations find higher non-white average incomes are associated with lower non-white infant mortality rates (IMR), while the relationships between white IMR and average white incomes are weak and statistically insignificant. This association is strongest in the early 1960s and the patterns are consistent across regions, counties, and levels of aggregation. Further investigation of this association shows that the finding does not appear to be driven by more local hospitals or hospital beds. In addition, hospitals and hospital beds do not consistently show significant differential associations with non-white infant mortality rates. Further, the average income association with the IMR does not appear to be influenced by fluctuations in unemployment rates. Associations between the IMR and unemployment itself are highly sensitive to the time period examined. Higher poverty rates are associated with higher infant mortality, but this association is present for both whites and non-whites. Including poverty rates in regressions of the IMR on incomes reduces the magnitude of the association between the non-white IMR with non-income somewhat, but a statistically significant relationship remains. Some counterintuitive results with income distribution and inequality point to a need for future investigation. Consistent with the literature, education rates show consistently statistically significant results that a greater share of non-white high school attainment is associated with lower non-white infant mortality rates. However, inclusion of this education measure does not appear to explain the association of non-white infant mortality with average non-white income.

Despite a recent and dramatic re-evaluation of the health consequences of alcohol consumption, very little is known about the effects of in utero exposure to alcohol on longrun outcomes such as later-life mortality. Here, we investigate how state by year variation in alcohol control arising from the repeal of federal prohibition affects mortality for cohorts born in the 1930s. We find that individuals born in wet states experienced higher later-life mortality than individuals born in dry states, translating into a 3.3% increase in mortality rates between 1990 and 2004 for affected cohorts.

Real-world transit service often deviates substantially from schedules, leading to variability in route-choice behaviors and experienced travel times that are not adequately reflected in existing accessibility analyses based on general transit feed specification (GTFS) schedule data alone. This study presents a methodology for more accurately assessing origin–destination (OD) transit reliability and accessibility by using GTFS data to generate candidate itineraries, then using automatic passenger counting and automatic vehicle location (APC-AVL) data to determine which routes are selected in real time and calculate the experienced travel time. The methodology is applied across March 2016–2020 from the perspectives of two groups in Allegheny County, Pennsylvania: residents in origins of high socioeconomic need traveling to opportunity employment hotspots, and prospective employers looking to establish a transit-accessible worksite. The worst OD pairs in practice achieved less than 15% of the accessibility captured by 95% of scheduled trips. At the 90-min threshold, the lowest observed accessibility corresponded to a realized loss of 17% of the eligible workforce due to service unreliability. These findings reveal the need to incorporate APC-AVL data to accurately model the route choice process and evaluate rider experiences.

We investigate the effect of education on public job choice using quarter of birth as an instrumental variable. We find that an additional year of education increases the probability of public sector employment by 1.87 percentage points. However, this positive effect is driven by females, whites, and those with high school degrees or less. For those with college or higher degrees, we observe a decrease in public employment with more education. Our results imply that highly-educated individuals go into high-risk, high-return occupations.

The Geospatial Information Authority of Japan defines geographic information system (GIS) as “a technology that enables an advanced analysis and a swift decision making through the comprehensive management, processing, and visualization of spatial data”(1). Although natural and social scientists are often assumed to be the main users of GIS, researchers in the humanities have also actively adopted this technology. At the turn of the twentiethfirst century, historical geographers established the field of historical GIS (HGIS) as a new research field to digitally reproduce and study geographic spaces in the past. Likewise, digital historians have carried out a wide range of GIS-based projects(2). This essay examines how historians have utilized GIS in their research in American history. The field has pioneered the use of GIS technologies for historical inquiries since American institutions of higher education and business industries have led technological innovation. Recently, Japan-based researchers of American history have also demonstrated a growing interest in GIS since the digitization of historical sources has progressed steadily for the past three decades. Besides, the COVID-19 pandemic has made it challenging for researchers to visit the United States, enhancing the interest in GIS as a new research methodology. To better respond to this trend, this essay first briefly discusses the history of GIS and the development of information infrastructure in the United States. Next, this paper examines the three types of GIS-based projects in the field of American history. Finally, the essay elucidates how researchers have addressed analytical problems of GISbased projects and explores its prospects for the future.

It is well established that air pollution is linked to numerous adverse health outcomes. Many studies show disparate air pollution related health impacts in communities due to factors such as proximity to air pollutions sources, age, race/ethnicity, and income. The goal of this study is to build upon previous work by examining statewide air pollution exposure and life expectancy disparities across generations and within communities. The impact of air pollution on life expectancy over two generations in California, especially for vulnerable populations is not well studied. The University of California, Berkeley (UCB) will acquire statewide Medi-Cal population data for the years 1990-2020 for this research. The Medi-Cal population are followed by the California Department of Health Care Services (DHCS) monthly and have the most stable continuous enrollments, generally across multiple generations for a family. The dates of death will be used to estimate the degree to which life expectancies were impacted by air pollution from fine particulate matter (PM2.5), separately, for (1) the first and second generations of the entire Medi-Cal population, (2) raceethnicity and vulnerability subgroups of each generation, and (3) the first and second generations within families. UCB hypothesizes that, due to improvements in air quality, overall air pollution-specific impacts on life expectancy improved from the first to the second generation, however, certain areas and groups may not have experienced the same improvements. Therefore, UCB aims to investigate which communities and groups over two generations continued to experience the greatest disparities in PM2.5 exposure and air pollution-related impacts to life expectancy. To reduce exposure misclassification, UCB will apply daily surfaces of PM2.5 at 100 meters (m) spatial resolution that is being developed for the State for the years 1989-2020 (creating 1989 daily surfaces for rolling average exposure for death in 1990). The home address of an enrollee will be assigned daily PM2.5 exposure and one-year rolling average exposure to the date of death. The death of an enrollee will be matched through propensity score by two survival enrollees who had similar individual and neighborhood characteristics except air pollution. The same time span and length of exposure will also be estimated for the matched survival enrollees. The Medi-Cal population will be separated into two periods: 1990-2005 and 2006-2020. When comparing the same age group between the two periods, the 1990-2005 population will be identified as first generation and, subsequently, the 2006-2020 population for the second generation. To identify the impact of air pollution on life expectancy, the years of life expectancy lost due to air pollution will be modeled through differentiating life expectancies estimated with all cause and cause PM2.5- eliminated mortality information (i.e., cause PM2.5-eliminated mortality = all cause mortality – cause PM2.5 mortality). Life expectancies on all cause and cause PM2.5 eliminated cohorts will be estimated through the traditional life table method and area under the curve function. The impact of PM2.5 on mortality will be modeled through a series of age-group specific logistic regression models that estimate the causal impact of air pollution on mortality. The difference in air pollution specific life expectancy loss between the first and second generation will then be identified. These differences will be identified not only for all the Medi-Cal enrollees, but also for race-ethnicity and vulnerability subgroups. Numerous studies identified that vulnerable communities historically experienced and continue to experience the highest air pollution and the greatest health burden. The air pollution level from 1989-2020 will be aggregated at the census tract (CT) level to identify if similar exposure trends exist. Air pollution exposure hotspots using the top 25 percent most occurring CTs with the greatest PM2.5 for a generation will be created and overlaid with CT level vulnerability (identified through CalEnviroScreen1 ) to identify exposure disparities in vulnerable communities. Further, CT level race-ethnicity composition will be used as weights to adjust statewide life expectancy loss estimated for the race-ethnicity subgroups to create CT level life expectancy loss. Similarly, the CT level life expectancy loss will be overlaid with CT vulnerability to identify life expectancy disparities in vulnerable communities. The Regional Asthma Management & Prevention (RAMP) will take the lead on the community outreach of the project. RAMP will host two webinars at the beginning of the project to inform stakeholders about the research and to solicit feedback on the scope and direction. RAMP will also host two webinars toward the end of the project to share the research results. UCB will work with RAMP to prepare webinar materials that are in lay language. The community outreach will not only serve the purpose of presenting research ideas and results to communities through accessible languages but will also gain feedback on what areas of the research findings communities are most interested in and what form the research findings should take such as mapping of CT level air pollution exposure and life expectancy disparities in vulnerable communities. Overall, this study will provide CARB with information on the impacts of PM2.5 exposure on life expectancy in the first generation and the second generation not only for California residents overall, but also for race-ethnicity and vulnerability subgroups. The subgroups with the greatest reductions in life expectancy due to increased PM2.5 exposure will be identified. This study will also identify at the CT level the communities that consistently experienced both the highest air pollution exposure and had the greatest life expectancy loss due to air pollution. Further, the study will provide research findings on changes in life expectancy from air pollution from the first generation to the second generation within families.