One of the most significant shifts in the study of inequality is a growing appreciation of geographic inequality, specifically inequality across the 50 US states. We assess the role of state governments in social policy provision, directing attention to the consequences of policy decentralization. Using unique data from the State Safety Net Policy (SSNP) dataset which consists of comparable indicators of state-level social provision, we examine the magnitude of cross-state variation in the generosity of benefits and the inclusiveness of safety net provisions. We find substantial inequality across states in social provision. We find that this cross-state inequality is larger in programs that allow for higher levels of state discretion. Finally, we find that when accorded these higher levels of discretion, states with substantial Black populations use this discretion in ways that limits the generosity and inclusiveness of social provision. These findings demonstrate how cross-state policy variation can contribute to, and exacerbate, consequential racial disparities in economic security.

We study changes in educational homogamy in the US and four European countries over the decade covering the Great Recession. The marital preferences identified point to the widening of the social gap between different educational groups since these preferences have increased the inclination of the individuals to match with others of similar educational traits in all five countries. We obtain this finding with an aggregate measure characterizing revealed preferences of individuals in relationship. We apply a novel approach for validating our finding: we compare our aggregate measure with dating data informative about the reservation points not only of those people who will be in a couple, but also those who will remain single. Finally, we challenge a commonly held view: we argue that marital preferences should not be blamed for the documented increase of the social gap since preferences are not exogenous, but are shaped by changes in the employment prospects of the potential partners.

Teaching immigrant parents about mental health awareness is vital for the Latino community because of the lack and high barriers for them to obtain resources on mental health. The immigrant parents have a background in English studies at the Watsonville adult school and Cabrillo College in Watsonville, California. The immigrant parents are from Mexico, and they are from different states in Mexico. Many immigrant parents have language barriers that prevent them from communicating and accessing mental health resources in the community to support them. Cultural competency can affect the misdiagnosis of mental health illnesses and education. Additionally, immigrant parents' status brings more challenges that can increase mental health issues such as anxiety and depression. In the development of the curriculum implementation for the project, there was an inadequacy of knowledge to address mental health awareness in the population of Latinos. The lack of information led to the designing of a workshop for a group of five parents who are immigrants. They will learn a one-lesson seminar to teach them about awareness of mental health issues. The workshop will provide indicators and symptoms related to mental health issues, recognize general vocabulary about mental health, and provide resources in their community.

Many institutions of higher learning aim to promote greater racial diversity to harness learning benefits and foster a sense of inclusion. Nevertheless, the institutional pursuit of racial diversity is difficult to benchmark. The current constitutional boundary limits the use of race to promote the diversity in college admissions to a “narrow,” “holistic,” and “case-by-case” strategy laden with definitional ambiguity. This ambiguity is deepened by constraints, such as institutional history, demographics, geography, and institutional rank, that often go unaccounted for in popular diversity measures. This article creates an expected diversity measure that describes the amount of racial diversity one would expect accounting for the home state of their incoming class. This initial step serves as an example that universities may follow when using their own internal data to account for a richer set of diversity constraints and to better monitor progress toward reaching their racial diversity goals. These measures can free universities from chasing unattainable external judgments on diversity targets, such as national benchmarks, thereby encouraging a more effective redistribution of resources for diversity-related outcomes.

Objectives: The COVID-19 pandemic has profoundly affected the lives of people globally, widening longstanding inequities. We examined the COVID-19 pandemic’s impact on employment conditions by race/ethnicity, gender, and educational attainment and the association between such conditions and well-being in older adults in the United States. Methods: Using data from the Health and Retirement Study respondents interviewed between May 2020 and May 2021 when they were ≥55 years of age, we examined intersectional patterns in COVID19-related changes in employment conditions among 4,107 participants working for pay at the start of the pandemic. We also examined the compounding nature of changes in employment conditions and their association with financial hardship, food insecurity, and poor self-rated health. Results: Relative to non-Hispanic White men with greater than high school education (>HS), Black and Latinx men and women were more likely to experience job loss irrespective of education; among those who did not experience job loss, men with ≤HS reporting Black, Latinx, or ―other‖ race were >90% less likely to transition to remote work. Participants who experienced job loss with decreased income or continued in-person employment with decreased income/shift changes had greater prevalence of financial hardship, food insecurity, and poor/fair self-rated health than others. Discussion: The impact of COVID-19 on employment conditions is inequitably patterned and is associated with financial hardship, food insecurity, and adverse health in older adults. Policies to improve employment quality and expand social insurance programs among this group are needed to reduce growing inequities in well-being later in life.

The Supplemental Nutrition Assistance Program (SNAP) is the nutritional cornerstone of the nation’s safety net, providing monthly benefits to help millions of Americans to purchase food. In this brief, we examine the individual and combined effects of two policies affecting SNAP benefits in the fourth quarter of 2021: (1) a reevaluation of the Thrifty Food Plan (TFP)that increased the maximum SNAP benefit 21 percent, and (2) “emergency allotments,” a temporary measure enacted in response to the COVID-19 pandemic that provides SNAP participants in participating states with the maximum SNAP benefit for their family size. We estimate the effects of these policies on SNAP benefits and quarterly poverty using the Urban Institute’s Analysis of Transfers, Taxes, and Income Security (ATTIS) microsimulation model.

How do students form beliefs about how their future career will depend on their choice of college major? Using both nationally representative survey data and surveys that we administered among undergraduates at the Ohio State University, we document that U.S. freshmen hold systematically incorrect beliefs about the relationship between majors and occupations. Students appear to stereotype majors, greatly exaggerating the likelihood that they lead to their most distinctive jobs (e.g., counselor for psychology, journalist for journalism, teacher for education). A stylized model of major choice suggests that stereotyping boosts demand for "risky" majors: ones with rare stereotypical careers and low-paying alternative jobs. In a field experiment among the same Ohio State sample, providing statistical information on career frequencies to first-year college students has significant effects on their intended majors (and, less precisely, on their choices of which classes to enroll in), with larger effects on students considering risky majors. Finally, we present a model of belief formation in which stereotyping arises as a product of associative memory. The same model predicts-and the survey data confirm-that students also overestimate rare non-stereotypical careers and careers that are concentrated within particular majors. The model also generates predictions regarding role model effects, with students exaggerating the frequency of career-major combinations held by people they are personally close to.

Accurate knowledge about the Covid-19 is crucial for individuals and communities to protect themselves from disease. Recent research finds that countries with populations high in social trust and interpersonal engagement have higher mortality rates from Covid-19, while countries with populations that place trust in their governments have lower rates. Drawing on Performance Monitoring for Action (PMA) and Afrobarometer data from three Sub-Saharan African countries (Burkina Faso, Nigeria, and Kenya), we ask: how do social trust, interpersonal engagement, and governmental trust shape individual knowledge of Covid-19 and does engagement with local health systems (through family planning) play a role? Findings suggest that civic and social engagement is positively associated with better knowledge of Covid-19 in both urban and rural areas and greater government trust is associated with correct knowledge of Covid-19, in rural areas. Findings also suggest that pairing family planning with information on Covid-19 may increase understanding of the disease.

This paper analyzes and provides estimates of the undercount of the foreign-born in the US Census Bureau’s 2020 American Community Survey (ACS). It confirms that a differential undercount occurred in the 2020 ACS. In particular, noncitizens that arrived from Central American countries after 1981 had undercount rates of 15–25 percent, but undercount of noncitizens that arrived from European countries in the same period was not detectable by the methods described in this paper. The Center for Migration Studies of New York (CMS) and others use ACS data to derive annual estimates of the US undocumented population. The Census Bureau recently reported that the total population count for the 2020 Census was consistent with the count for recent censuses, despite the Covid-19 pandemic and the Trump administration’s interference in the 2020 Census. Nonetheless, the accuracy of 2020 ACS data for the noncitizen population that arrived after 1981 remains a major concern given the fear generated by the Trump administration’s abusive rhetoric and anti-immigrant policies. The estimates set forth in this paper were derived by analyzing trends in annual ACS data for 2016–2020 compiled from the IPUMS website (Ruggles et al. 2021). Decennial census data cannot be used for this purpose because data on country of birth, citizenship, and year of immigration are not collected in the census. However, it is reasonable to believe that the 2020 census and the 2020 ACS experienced similar challenges because they were conducted under comparable conditions. The patterns of undercount of noncitizens described here for the 2020 ACS are likely mirrored in the 2020 census and will reduce federal funding and representation to affected cities and states for the next decade.

U.S. homeownership rates have largely recovered since the depths of the Great Recession, except for Black Americans. In 2019, 42 percent of Black households owned a home, compared to 73 percent of white households. Currently, about two thirds of households own their home, a rate of homeownership that has prevailed in the U.S. since mid-century. However, whether this rate can be sustained over the next decades is in question. Black and Hispanic/Latinx homeownership rates have remained far below that of the white non-Hispanic rate. In addition, the homeownership rate for younger households is now below its level prior to the 2000s housing boom and bust. In this paper, we discuss what is known about homeownership outcomes and policies: in particular, how borrowing constraints and housing affordability are impacting current homeownership outcomes; how the trajectory of homeownership rates over time from pre-Great Depression through the current period reflects lending regimes; and how future trajectories based on projected demographic trends and lending environments imply a very different future for U.S. homeownership outcomes. We also present policy interventions that could help to change the course of these trends and support sustainable access to homeownership.

In the 1930s, the Home Owners’ Loan Corporation (HOLC) graded the mortgage security of urban US neighborhoods. In doing so, the HOLC engaged in the practice, imbued with racism and xenophobia, of “redlining” neighborhoods deemed “hazardous” for lenders. Redlining has caused persistent social, political and economic problems for communities of color. Linkages between redlining and contemporary food access remain unexamined, even though food access is essential to well-being. To investigate this, we used a census tract-level measure of low-income and low grocery store food access from the US Department of Agriculture Food Access Research Atlas, redlining data from Mapping Inequality Project, and demographic data from the American Community Survey. We employed generalized estimating equations with robust covariance estimates to analyze data pertaining to 10,459 census tracts in 202 US cities. Tracts that the HOLC graded as “C” (“decline in desirability”) and “D” (“hazardous”) had reduced contemporary food access compared to those graded “A” (“best”). Increases in contemporary census tract proportions of Black, Hispanic, or other racial/ethnic minority residents, as well as disabled residents, were associated with reduced food access. Increases in contemporary proportions of residents age 75 years and older or those without a car were associated with better food access. Tracts that underwent housing redevelopment since being graded had better food access, while those undergoing gentrification had reduced food access. Results suggest that issues of redlining, housing discrimination, racism, ableism, displacement, and food inaccessibility are deeply intertwined.

The high cost-of-living in “superstar” US metropolitan areas has become an area of increasing scholarly and policy concern. One question relates to whether low socioeconomic status (SES) and other historically disadvantaged residents are getting pushed out of these city-regions. To unpack what is occurring with respect to migration out of large expensive metros, I examine who is moving out of these areas in the US and where they are going. I use regression, coarsened exact matching, and latent class analysis to understand who is staying within large expensive US metros and who moves out of them, as well as what revealed preferences underlie these moves. I find evidence that lower SES households are slightly more likely to leave superstar US city-regions, though Black, Latinx, and immigrant households are less likely to leave than White and US-born households. Rather than leaving, many low SES households may instead continue to live in these areas while enduring increasingly crowded living arrangements and/or long commutes. The results also highlight substantial heterogeneity in where households go to once they move, suggesting migration out of these urban areas may be more complex than simply the push of high cost-of-living.

Prior research suggests that disruptive events, such as shocks induced by family instability, neighborhood violence, or relocation, tend to be detrimental for children’s educational outcomes, but findings are heterogeneous depending on the type of event. Limited evidence is available on how shocks resulting from immigration enforcement impact educational outcomes among targeted minority groups. This study contributes to the literature by assessing how a policy implementation in the US–Secure Communities–is related to the school district level achievement of Hispanic students. The Secure Communities program is a national level immigration enforcement policy that was rolled out on a county-by-county basis. The program has increased the risk of deportation and led to rising apprehension and insecurity among undocumented migrants and the wider Hispanic community. Using detailed information on the implementation of Secure Communities, data from the Stanford Education Data Archive, and the Current Population Survey, this study estimates dynamic difference in differences exploiting regional variation in the timing of the policy change to assess its impact on educational outcomes. Results show that the activation of Secure Communities is negatively associated with Hispanic students’ subsequent English language arts achievement, while white and black students’ achievement does not change. Findings further suggest that Hispanic students living in the South, rural areas, and areas with high proportions of likely undocumented migrants are disproportionately impacted by the program’s activation. Whereas, Hispanic students in sanctuary jurisdictions, which reduce the likelihood of deportation, are not impacted. These findings indicate that immigration enforcement can have negative consequences for educational and social inequalities in the United States.

We develop a new stochastic programming methodology for determining optimal vaccination policies for a multi-community heterogeneous population. An optimal policy provides the minimum number of vaccinations required to drive post-vaccination reproduction number to below one at a desired reliability level. To generate a vaccination policy, the new method considers the uncertainty in COVID-19 related parameters such as efficacy of vaccines, age-related variation in susceptibility and infectivity to SARS-CoV-2, distribution of household composition in a community, and variation in human interactions. We report on a computational study of the new methodology on a set of neighboring U.S. counties to generate vaccination policies based on vaccine availability. The results show that to control outbreaks at least a certain percentage of the population should be vaccinated in each community based on pre-determined reliability levels. The study also reveals the vaccine sharing capability of the proposed approach among counties under limited vaccine availability. This work contributes a decision-making tool to aid public health agencies worldwide in the allocation of limited vaccines under uncertainty towards controlling epidemics through vaccinations.

Hierarchical histogram publication can improve the accuracy of range queries by adding the same noise level to different layers, and histogram compression can also improve the accuracy of range queries with considering the inherent redundancy of real-life histograms. However, the existing hierarchical histogram publication schemes have high sensitivity without considering the inherent redundancy of real-life his-tograms. In addition, the existing histogram compression schemes compress the whole histogram with high sensitivity. To address these issues, we present a histogram publication scheme, which combines histogram compression and hierarchical histogram to increase the accuracy of range queries. In particular , we propose a compression method base on coarse division and dynamic budget allocation to get an efficient compressed histogram, which can decrease the sensitivity of compression method and increase the allocated privacy budget for each division in the same privacy level. The accuracy of released his-togram by our proposed scheme outperforms the existing schemes. The comparison of simulation results among two latest schemes, a classic hierarchical tree scheme and our scheme show that our scheme outperforms the existing schemes.

This paper presents new estimates of the level and persistence of poverty among US households since the Great Recession. We build annual household data files using US income tax filings between 2007 and 2018. These data allow us to track individuals over time and measure how tax policies affect poverty trends. Using an after-tax household income measure, we estimate that while roughly 1 in 10 people are in poverty in any given year, over 4 in 10 people spent at least one year in poverty between 2007 and 2018. This implies substantial mobility in and out of poverty—for example, 41 percent of those in poverty in 2007 were out of poverty in the following year. Others spend multiple years in poverty or escape poverty only to fall back into it. Of those in poverty in 2007, one-third were in poverty for at least half of the years through 2018.

This research provides an extended profile of the social and economic well-being of rural Pennsylvania women. Using highly credible secondary data sources, the research describes the life circumstances of contemporary rural women. Rural Pennsylvania women, grouped into three broad age categories, are compared to their urban counterparts as well as to both rural men and urban men in the state. Trends spanning about a decade are depicted, and contextual measures and geographic considerations provide depth to the profiles of these women’s lives.

Background: The objectives of the present study are to understand the longitudinal variability in COVID-19 reported cases at the county level and to associate the observed rates of infection with the adoption and lifting of stay-home orders. Materials and Methods: The study uses the trajectory of the pandemic in a county and controls for social and economic risk factors, physical environment, and health behaviors to elucidate the social determinants contributing to the observed rates of infection. Results and conclusion: Results indicated that counties with higher percentages of young individuals, racial and ethnic minorities and, higher population densities experienced greater difficulty suppressing transmission. Except for Education and the Gini Index, all factors were influential on the rate of COVID-19 spread before and after stay-home orders. However, after lifting the orders, six of the factors were not influential on the rate of spread; these included: African-Americans, Population Density, Single Parent Households, Average Daily PM2.5, HIV Prevalence Rate, and Home Ownership. It was concluded that different factors from the ones controlling the initial spread of COVID-19 are at play after stay-home orders are lifted.

My dissertation consists of three papers on the response of various economic indicators to crude oil shocks. In the first paper, I investigate the Western Australian gasoline market for asymmetric responses in gasoline prices to changes in input costs, otherwise known as the rockets and feathers hypothesis. This theory states that after a positive cost shock, firms will swiftly increase their retail prices to consumers; after a decrease in input costs, however, they take longer to adjust and lower prices. Using daily, establishment level data, I estimate a multi-stage error correction model and find evidence of asymmetric price adjustment in the long-run adjustment process. I do not, however, find significant evidence in the short-run dynamics. Of particular interest in this market is that the regional firms transition to a uniform price cycle within the sample. I find that changes in pricing patterns and market conduct can impact the long-run relationship in downstream gasoline markets, which may -in turn- affect estimates obtained from traditional error correction models. While the crude oil and retail gasoline markets are naturally integrated, shocks in crude oil can have large repercussions to the overall macroeconomy. An unexpected increase in crude oil price affects the costs of production for many manufacturing industries. As such, it is important to investigate whether these shocks have an impact on the employment in such industries. My second paper uses quarterly, establishmentlevel data from the Census Bureau to construct job flows for the United States from 1980 to 2016. Combined with recent data on oil news shocks, I investigate the effect of unexpected shocks to oil news on job reallocation. I find that oil news shocks have significant effects on job creation and destruction rates, with the effects varying across industries. Furthermore, the automobile subsectors experience economically and statistically significant increases in labor reallocation following an oil news shock. I find that responses vary across some firm characteristics, such as level of capital investment, indicating that precautionary motives may be a possible transmission channel. There is a large body of literature that has investigated the changes in the labor market that occurred in the 1970s, however the impact of the 1973 and 1979 oil shocks has received less scrutiny. In my third paper, I inquire into the long-term decline in employment and earnings of unskilled young men since 1973. Using county level data,I combine variation at the industry and commuting zone level to identify the longrun impact of oil shocks on key demographic groups. I find that young low-education males experienced significant decreases in labor market outcomes, particularly when compared to older males, younger females, and young males with higher levels of education. When accounting for the importance of oil in industry production and differential effect for demand driven industries, similar results can be seen.