Our research seeks to understand the challenges with public transportation accessibility for people with disabilities (PWD) in the metropolitan area of Minneapolis, Minnesota. We show both the necessity of access to transportation and the lack of equity that currently exists with a focus on better understanding the issue in the Twin Cities, Minnesota through the global perspectives of the United States, China, and France.

This brief extends Cato’s earlier research on drunk driving deaths to see how the illegal immigrant proportion of the population in the years 2010–2019 at the state and metropolitan statistical area (MSA) levels are related to drunk driving deaths in those localities.

The COVID-19 pandemic caused a variety of social, economic, and environmental changes. This paper examines the employment-related impacts of the pandemic on workers in the transportation industry compared to other industries, and within different transportation sectors. We estimated random effects logistic regression models to test the following three hypotheses using the monthly Current Population Survey micro-data. One, the transportation industry experienced a greater incidence of unemployment than other industries. Two, there is heterogeneity in employment impacts within the transportation sector. Three, specific sectors within the transportation industry experienced more employment impacts than other essential industries, as designated by the Centers for Disease Control and Prevention (CDC) Phase 1a vaccination guidelines. Model results highlight that workers in the transportation sector were 20.6% more likely to be unemployed because of the pandemic than workers in non-transportation industries. Model results also indicate large intra-sector heterogeneities in employment impacts within the transportation sector. Taxi and limousine drivers were 28 times more likely to be unemployed compared to essential workers. Scenic and sightseeing transportation workers were 23.8 times more likely to be unemployed compared to essential workers. On the other end of the spectrum, however, postal workers and pipeline workers were 84% and 67% less likely to be unemployed compared to essential workers, respectively. From a policy perspective, these results suggest that attention to several aspects of transportation work are needed in the coming years to prepare for future interruptions to the transportation industry.

Scholars debate whether residential racial segregation associates positively, negatively, or at all with the Black self-employment rate in the United States. This study engages that debate using data from the Integrated Public Use Microdata Series (IPUMS) 1980, 1990, and 2000 5% sample and 2006–2010 American Community Survey (ACS) 5-year sample. Specifically, I investigate the county-level association between residential racial segregation and the Black self-employment rate, and whether this association varied by region in 1980, 1990, 2000, and 2010. Using fractional logit models and net of control variables, I find that residential racial segregation positively predicts Black self-employment in the South. Implications for understanding how time and region condition Black self-employment opportunities are discussed.

More than one-third of US children receive coverage through Medicaid and the Children's Health Insurance Program (CHIP), but undocumented immigrant children are not eligible for public coverage in most states. California's May 2016 Health4All Kids coverage expansion allowed children with qualifying household incomes to enroll in Medi-Cal, California's Medicaid and CHIP program, regardless of their immigration status. We examined the effects of California's expansion on noncitizen children's uninsurance rates and sources of coverage, using data from the 2012-18 American Community Survey. California's expansion was associated with significant increases of about 9 and 12 percentage points in any coverage and public coverage, respectively. The estimated increase in any coverage translates to a 34 percent decline in the uninsurance rate relative to the preexpansion rate among noncitizen children (26 percent). Counties with an existing program to reduce children's uninsurance rates experienced an increase in coverage earlier than those without a program in effect before the statewide expansion.

With the removal of legal barriers to mixed-race marriage, there has been a consistent increase in the number of Black-White couples. This has coincided with growth in the number of Black-White individuals who have formed couples with a Black or White partner. Little is known, however, about how these couples function within a key area of stratification—neighborhood attainment. We use data from the Home Mortgage Disclosure Act and the U.S. Census to investigate the percentage of Whites and the average income in the neighborhoods of home-purchasing couples defined by their levels of Black and White representation. These couples being White couples, Black-White individuals with White partners, Black-White couples, Black-White individuals with Black partners, and Black couples. Findings reveal that the percentage of Whites and average income in the neighborhoods of couples decrease as couples increase in Black representation. These results have implications for our understanding of the contemporary color line.

Anonymisation technique has been extensively studied and widely applied for privacy-preserving data publishing. However, most existing methods ignore personal anonymity requirements. In these approaches, the microdata consist of three categories of attribute: explicit-identifier, quasi-identifier and sensitive attribute. In fact, the data sensitivity should be determined by individuals. An attribute is semi-sensitive if it contains both QI and sensitive values. In this paper, we propose a novel anonymisation approach, called local anatomy, to address personalised privacy protection. Local anatomy partitions the tuples who consider the value as sensitive into buckets inside each attribute. We conduct some experiments to illustrate that local anatomy can protect all the sensitive values and preserve great information utility. Additionally, we also present the concept of intelligent anonymisation system as our direction of future work.

In March 2020, the Covid-19 global pandemic dramatically altered the day-to-day routines of most Americans. As the pandemic wore on and Americans internalized the realities of extended, national public health and economic crises, changes in circumstances or priorities (including job loss/departure, remote work, virtual versus in-person schooling, space and outdoor activities at a premium, etc.) inspired or forced many Americans to reconsider their place of residence. Media stories told anecdotal accounts of migration away from city centers towards more rural and natural amenity destinations in response to pandemic realities. This report describes historical migration patterns in and out of Michigan’s Upper Peninsula (UP) and systematically documents change to that historical pattern during the global pandemic in 2020 and through August 2021. The report then situates those findings in the context of broader literature about migration, focusing on rural America and natural amenity destinations. The report’s final section builds on the demographic findings and literature review to provide recommendations for migration-related community and economic development endeavors in the UP. While some people did move in response to the pandemic, pandemic migration appears to be modest in nature and nuanced. In September 2020, Bloomberg City Lab reported that based on data from moving companies and real estate websites, Americans were moving less in 2020, with some notable exceptions for major cities such as New York City and San Francisco (Patino, 2020). The New York Times (Kolko et al., 2021) and CBRE (Willett & Mowell, 2021) independently published analyses of United States Postal Service (USPS) data, each arriving at the same conclusion: pandemic migration patterns largely matched pre-pandemic patterns, with residents of large, coastal urban metros continuing to move to Sun Belt cities (e.g., Austin), smaller metros (e.g., Boise), or areas considered “destinations” (e.g., Cape Cod) in much the same pattern as 2019. Review of Consumer Credit Panel data similarly shows that while urban neighborhoods saw increased out-migration in 2020, lack of in-migration made a bigger impact on urban centers, suggesting that on the whole Americans were more likely to stay in place in response to Covid-19 than to move (Whitaker, 2021). In a survey study of 300,000 residential and interstate moves over the last three years, Haslag & Weagley (2021) found that while inter-state moves in 2020 were lower than previous years, 15% of movers directly cited the influence of the pandemic in their decision to move; less moved for reasons of employment and more for family or lifestyle (though differences exist among socio economic groupings); and the ability to work remotely factored highly in decisionmaking. Consistent with others’ findings, movers perceived or knew their destinations to have less Covid-19 cases, less pandemic-related restrictions, lower density, and lower rents (Haslag & Weagley, 2021). Given this, a mass inflow of migrants to Michigan’s Upper Peninsula (UP) as a result of the pandemic is unlikely. Still, even a reduction of out-migration or a slight increase of in-migration would signal a noteworthy change to a pattern of primarily out-migration from the region over the last several decades. Migration research (see Appendix A) demonstrates that for those who are not tethered to their geographic location by employment, migration is strongly motivated by quality-of-life factors, such as access to amenities. Michigan’s UP is an attractive location, especially relative to pandemic life in an urban environment: low density (19 people per square mile), moderate cost of living, year-round recreation opportunities, and easy access to outdoor amenities such as beaches, forests, lakes, and rivers. For this report, we analyzed migration trend data in the 20 years prior to the pandemic (1999-2019), the pandemic year itself (2020), and the months since (through August 2021). Our findings show that: • Over the last fifty years, the UP has generally experienced population loss due to net out-migration, but also and increasingly, due to natural decrease (more deaths than births). • Outflow from the UP slowed considerably during the pandemic. • Inflow to the UP also slowed, but not as much as outflow, meaning that between May 2020 and August 2021 there was less net loss from the UP than is typical. • These patterns vary across space, with some areas attracting/losing more than others in the pandemic year (May 2020-Apr 2021). Alger and Iron counties both saw net positive migration in the pandemic year itself. Marquette, Mackinac, Dickinson, Iron, Houghton, Keweenaw, and Alger counties saw the greatest increase in netflow in the pandemic year relative to the three years prior. The pandemic resulted in little change to migration in Baraga, Luce, Ontonagon, and Schoolcraft counties.

Lesbian, gay, and bisexual-identified (LGB) people experience worse mental and physical health than their straight-identified counterparts. Given remarkable social and legal changes regarding LGB status in recent decades, we theorize that this profound health disadvantage may be changing across cohorts. Using data from the 2013–2018 National Health and Interview Surveys, we analyze five mental and physical health outcomes—psychological distress, depression, anxiety, selfrated physical health, and activity limitation—across three birth cohorts colloquially known as (1) Millennials, (2) Generation Xers, and (3) Baby Boomers and pre-Boomers. We find no evidence of reduced health disparities by sexual orientation across cohorts. Instead, relative to straight-identified respondents, the health disadvantages of gay, lesbian, and—most strikingly—bisexual-identified people have increased across cohorts. Findings highlight the importance of identifying the causes of increased health disparities as well as designing and implementing more direct public policies and programs to eliminate health disparities among more recent LGB cohorts.

Flexible exchange rates can facilitate price adjustments that buffer macroeconomic shocks. We test this hypothesis using adjustments to the gold standard during the Great Depression. Using prices at the goods level, we estimate exchange rate pass-through and find gains in competitiveness after a depreciation. Using novel monthly data on city-level economic activity, combined with employment composition and sectoral export data, we show that American exporting cities were significantly affected by changes in bilateral exchange rates. They were negatively impacted when the UK abandoned the gold standard in 1931 and benefited when the US left the gold standard in April 1933. We show that the gold standard deepened the Great Depression, and abandoning it was a key driver of the economic recovery.

A popular cash transfer program credited with lifting millions out of poverty, the Earned Income Tax Credit (EITC) also reduces wages for non-college educated workers, particularly older workers. Meanwhile, eligibility rules have long prevented most older workers from receiving EITC benefits at the same rate as their younger counterparts. Expanding EITC benefits permanently would offset some of these lost earnings and help stabilize older workers’ earnings. In 2021, Congress enacted a temporary EITC expansion—and our research shows that a permanently expanded EITC would benefit millions of older low-income workers.

Women used to lag behind but now exceed men in college enrollment. We argue that changes in non-college job prospects contributed to these trends. We first document that routine-biased technical change disproportionately displaced non-college occupations held by women. We next employ a shift-share instrument for the impact of routinization to show that these lower non-college job prospects for women increase female enrollment. Results show that a one percentage point decline in the share of routine task intensive jobs leads to a 0.6 percentage point rise in female college enrollment , while the effect for male enrollment is directionally smaller and insignificant. We next embed this instrumental variation into a dynamic model that links education and occupation choices. The model finds that routinization decreased returns in non-college occupations for women, leading them to shift to cognitive work and increasing their college premiums. In contrast, non-college men's occupations were less susceptible to routinization. Altogether, our model estimates that workplace routinization accounted for 67% of the growth in female enrollment and 31% of the change in male enrollment between 1980 to 2000.

Emerging evidence suggests that the COVID-19 pandemic has extracted a disproportionate toll on immigrant communities in the U.S. Media accounts highlight the way that low-wage immigrant workers in a variety of industries have been ravaged by COVID-19 (Swanson, Yaffe-Bellany, and Corkery 2020; Tully 2020). Epidemiological studies indicate high rates of COVID-19 infection and mortality among racial and ethnic minorities in general (Figueroa et al. 2020; Gross et al. 2020; Holtgrave et al. 2020), including immigrants (Garcia et al. 2021; Rodriguez-Diaz et al. 2020; Strully, Yang, and Liu 2021). The fact that immigrants often lack access to health insurance and frequently live in overcrowded residential conditions that make quarantining after contracting the virus more difficult are cited as potential explanations for why COVID-19 has affected immigrants so severely (Garcia et al 2021).

We investigated relationships between independently observed, visual cues of residential environments and subsequent participant-reported stress within a population-based cohort of Black breast cancer survivors (n = 476). Greater visual cues of engagement – presence of team sports, yard decorations, outdoor seating – (compared to less engagement) was marginally associated with lower perceived stress in univariate models, but attenuated towards null with adjustment for socio-demographic, behavioral, and health-related covariates. Similarly, physical disorder and perceived stress were not associated in adjusted models. Relationships between observed built environment characteristics and perceived stress might be influenced by socioeconomic and health behavior factors, which longitudinal studies should investigate.

Forced separation of immigrant children from their parents in 2018 spurred calls for immigration reform. Research shows that immigrant children experience separation from parents during the immigration process for many reasons and that they experience a wide range of negative outcomes. This paper builds on the scholarship exploring the relationship between family separation and education outcomes of US immigrant children. Using the sample of immigrant children (n = 94,731) in the 2010–2018 American Community Survey, this study analyzes the association between separation and the likelihood of a peer education gap using descriptive statistics and multivariate logistic regression analysis. This paper supports prior scholarship and finds that immigrant children who experience separation are over 35% more likely to experience a peer education gap. It adds to the literature by exploring patterns of immigrant children from all countries of origin and examining the effects of length of separation on education outcomes. While children from all places of origin experience separation, the percentage of such children is much smaller when children come from wealthier countries and regions and, more importantly, the length of separation is much longer for immigrant children from poorer countries. This study finds that the length of separation correlates with poorer education outcomes.

Researchers and journalists have argued that work-related factors may be partly responsible for disproportionate COVID-19 infection and death rates among vulnerable groups. We evaluate these claims by examining racial and ethnic differences in the likelihood of work-related exposure to COVID-19. We extend previous studies by considering 12 racial and ethnic groups and five types of potential occupational exposure to the virus: exposure to infection, physical proximity to others, face-to-face discussions, interactions with external customers and the public, and working indoors. Most importantly, we stratify our results by occupational standing, defined as the proportion of workers within each occupation with at least some college education. This measure serves as a proxy for whether workplaces and workers employ significant COVID-19-related risk reduction strategies. We use the 2018 American Community Survey to identify recent workers by occupation, and link 409 occupations to information on work context from the Occupational Information Network to identify potential COVID-related risk factors. We then examine the racial/ethnic distribution of all frontline workers and frontline workers at highest potential risk of COVID-19, by occupational standing and by sex. The results indicate that, contrary to expectation, White frontline workers are often overrepresented in high-risk jobs while Black and Latino frontline workers are generally underrepresented in these jobs. However, disaggregation of the results by occupational standing shows that, in contrast to Whites and several Asian groups, Latino and Black frontline workers are overrepresented in lower status occupations overall and in lower status occupations associated with high risk, and are thus less likely to have adequate COVID-19 protections. Our findings suggest that greater work exposures likely contribute to a higher prevalence of COVID-19 among Latino and Black adults and underscore the need for measures to reduce potential exposure for workers in low status occupations and for the development of programs outside the workplace.

This article quantifies the effect of individual social distancing on the spread of the novel coronavirus. To do so, we use data on time spent by individuals on activities that would potentially expose them to crowds from the American Time Use Survey linked with state-level data on positive tests from the COVID Tracking Project. We estimate count data specifications of observed COVID-19 infections at the state level as a function of control demographic variables, and a measure of social distance that captures the amount of time individuals across the states spend in activities that potentially expose them to crowds. Parameter estimates reveal that the number of state-level novel coronavirus infections decrease with respect to our measure of individual social distance. From a practical perspective, our parameter estimates suggest that if the typical individual in a U.S. state were to spend eight hours away from crowds completely, this would translate into approximately 240,000 fewer COVID-19 infections across the states. Our results suggest that, at least in the United States, social distancing policies are effective in slowing the spread of the novel coronavirus.

They may lack the sweep of a novel, the pathos of a play or the beauty of a poem, but the facts and figures collected through the census tell us a great deal about ourselves, and about the generations who came before us. Just ask Steven Ruggles, a historical demographer at the University of Minnesota who has built a career deciphering census data to trace the history of the family in the Western world. By mining public records, Ruggles can learn how family structures have changed over time: who and when people marry, when they have children, where and how people live, the ways people make a living.

We provide novel evidence on the role of negative social comparisons in population health behaviors by exploiting variation in Miss America and Miss USA beauty pageant winners. We show that there was more front-page newspaper coverage and more pageant-related internet search behavior following a home-state win. Teen girls and pageant-aged women with home-state winners were more likely to report that they were trying to lose weight, and pregnant women gained less gestational weight. We do not detect meaningful changes for teen boys, young adult men, or older women for whom social comparisons were plausibly less salient.