Ethnic identities around the world are deeply linked to the modern territorial state, yet the extent to which states have shapes and still shape ethnic groups is empirically unclear. I argue that governments at the national and subnational level have incentives to bias governance in favor of the largest ethnic groups in their territory. The resulting disadvantages for ethnic minorities can motivate minority assimilation and emigration. Both gradually align ethnic with administrative boundaries. I examine this process at the subnational level across Sub-Saharan Africa. Exploiting credibly exogenous, straight borders allows for causal identification. I find substantive increases in local population shares of administrative units' predominant ethnic groups at the border, showing that administrative geographies shaped ethnic groups. Additional analyses demonstrate that ethnic assimilation and emigration of local minorities drive the phenomenon. These results highlight important effects of the territorial organization of modern governance on ethnic groups.

Previous studies show that unemployment has a positive effect on crime rates; however, unemployment insurance (UI) benefits could mitigate these effects. Using county-level unemployment and crime data and taking advantage of the UI law changes across states and over time (1990–2016), we provide new evidence that the UI benefits act as a buffer against local labour market shocks. A one-standard-deviation increase in benefits is associated with 2.4% and 1.9% lower property and violent crime rates for a county at average unemployment.

Previous studies by Borjas (2007), Ottaviano and Peri (2008), and Card (2001) focus on the impact Mexican immigration has on the U.S. labor market. Specifically, whether immigration has a direct effect on natives’ wages and unemployment. We study low-skilled males in the labor force between the ages of 16-64, while also controlling for gender, familial status, and race. Control variables are measured at the city-level, in hopes of providing us with more accurate estimates that may be overlooked at the national level (Levine 2010). Using data from IPUMS USA at the metropolitan level, we find that on average, Mexican immigration has no significant impact on the U.S. unemployment rate. In regard to native wages, however, we find a small statistically significant negative impact. Our results are used to analyze the substitutability and complementary relationships between immigrants and native workers. The downward pressure on wages may result in the potential substitutability between low-skilled male natives and low-skilled male Mexican immigrants. An influx of immigrants may result in an increase in labor supply, which will decrease the overall wages in the labor market for specific low-skilled occupations.

How did cliometrics in particular, and economic history in general, arrive at this crossroads, where it is at once considered to be a dying discipline and one that is spreading through the economics discipline as a whole? To understand the current status and future prospects of economic history, it is necessary to understand its past.

Many veterans rely on the Supplemental Nutrition Assistance Program (SNAP). We study the change in the veterans’ reliance on SNAP in response to the GI Bill, the veterans’ financial aid for higher education. Using the unanticipated increase in educational benefits due to the Post-9/11 GI Bill and employing a difference-in-differences approach, we estimate that the benefit increase lowered veteran SNAP participation by about 28%, the effect being larger among new veterans. These findings reflect changes in the veterans’ choices that are attributable to wealth effects, SNAP eligibility criteria, and human capital accumulation. SNAP eligibility typically expires when the veteran attends college, and a larger educational benefit increases the veterans’ probability of college attendance. Furthermore, a college degree increases future earnings, which reduces the veterans’ SNAP reliance in the longer run. Quantifying these relationships provides insights into how financial aid for education in general improves veterans’ economic well-being and may help break some veterans’ dependence on SNAP and similar welfare programs.

Overall, Latino children are more likely to be uninsured than their peers, even though nearly all Latino children are U.S. citizens. Research has shown that having health coverage as a child has life-long, positive impacts such as improved health, improved educational outcomes, and higher paying jobs in adulthood. Efforts to cover more Latino children will require developing a deeper understanding of the characteristics of subgroups of uninsured Latino children such as by age, income level, state residency, and country of origin. As a starting place, policymakers and stakeholders at the state and local level can turn to Census Bureau data to identify groups of Latino children that may benefit from more targeted outreach and enrollment efforts and build partnerships with community health workers to reach them in culturally and linguistically appropriate ways. Over the long term, the Biden Administration can work to improve Census Bureau data to address issues with the sample size and how the questions are phrased to better capture lived experiences. Leaders at the federal and state levels can also begin to rebuild trust among Latino communities by sharing clear and reliable information as they work toward more inclusive health coverage policies.

Introduction Despite evidence that greater diversity among health care workers may allow them to better care for patients with diverse cultural, social, economic, and clinical needs,1-3 data are limited on trends in diversity and representativeness of US health care workers by occupation. Using US Census data from 2000 to 2019, we examined national trends in representativeness in select health care occupations by race/ethnicity and sex. Methods In this cross-sectional study, we used 2 data sources: (1) the Decennial Census long form, a nationally representative, US Census–administered survey, from 2000, and (2) the American Community Survey, a nationally representative Census-administered survey, from 2001 to 2019. Response rates for both exceeded 90%.4,5 This study followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline. The University of California Los Angeles institutional review board determined that the study was not human subjects research and therefore exempt from review and the requirement for informed consent. Occupation, race, (White, Black, American Indian or Alaska Native, Chinese, Japanese, other Asian or Pacific Islander, other race, 2 major races, or ≥3 major races) and ethnicity (not Hispanic, Mexican, Puerto Rican, Cuban, and other Hispanic origin) were self-reported. Participants who selected Chinese, Japanese, or other Asian or Pacific Islander were included into the category Asian. Participants who selected Mexican, Puerto Rican, Cuban, and other were included in the Hispanic category. Participants who selected other race, 2 major races, or 3 or more major races were excluded, leaving 4 groups: non-Hispanic White, non-Hispanic Black, non-Hispanic Asian, and Hispanic. We estimated the composition of select health care occupations (Table 1) by race/ethnicity and sex in 2000 to 2004 and 2015 to 2019. For each occupation, we calculated the change in percentage in each race/ethnicity and sex subgroup between these 2 periods using linear regression. In addition, in each occupation, we assessed the population representativeness of each race/ethnicity and sex subgroup by calculating the ratio of the percentage of a specific subgroup in an occupation (eg, Black male physicians) to the percentage of the US population in that subgroup (eg, Black men).6 We used Census-provided sampling weights to make nationally representative estimates. P values were from 2-sided tests, and results were deemed statistically significant at P < .05. Analyses were conducted in Stata version 16.1 (StataCorp). Results Our study included 1 648 924 individuals (1 303 496 [79.1%] women; 345 428 [20.9%] men) across 6 health care occupations (Table 1). The percentage of White men in relatively more remunerative occupations (ie, physicians and surgeons, pharmacists, and dentists) decreased between 2000 to 2004 and 2015 to 2019. For example, the percentage of physicians and surgeons who were White men decreased from 54.1% (95% CI, 53.3% to 54.9%) to 43.8% (95% CI, 43.3% to 44.3%) (difference, −10.3 [95% CI, −11.2 to −9.3] percentage points), while the percentage of dentists who were White men decreased 15.6 (95% CI, 13.5 to 17.6) percentage points. Little to no change was observed in the percentage of men from underrepresented minorities in these occupations. For example, no change was observed in the percentage of physicians and surgeons who were Hispanic men (difference, 0.2 [95% CI, −0.2 to 0.6] percentage points) or in the percentage of pharmacists who were Black men (difference, −0.06 [95% CI, −0.8 to 0.6] percentage points). Statistically significant increases were observed in the percentage of both Black and Hispanic women in these 3 occupations. For example, the percentage of pharmacists who were Black women increased 1.3 (95% CI, 0.6 to 2.0) percentage points, and the percentage of dentists who were Hispanic women increased 1.0 (95% CI, 0.4 to 1.7) percentage points. Increases for White and Asian women in these occupations were larger than for Black and Hispanic women. Significant increases were observed among most minority race/ethnicity and sex subgroups in less remunerative occupations (ie, nurses, therapists, and health care aides). In an analysis of population representativeness in 2015 to 2019, Black and Hispanic men and women remained considerably underrepresented relative to the US population in more remunerative occupations (Table 2). Discussion In a nationally representative sample, little to no increase in Black or Hispanic men was observed among physicians and surgeons, pharmacists, and dentists between 2000 and 2019. While there were increases in Black and Hispanic women in these occupations, increases among White and Asian women were larger. Altogether, increases in representation of these 4 subgroups of women were accompanied by large declines in the proportion of White men. Other health care occupations, such as nurses, therapists, and health care aides, had increases across most minority subgroups during the examined period. These results quantify the current representativeness of the US health care workforce and changes in its composition during the past 2 decades. Study limitations include the use of self-reported survey data.

Analyzing votes on abortion-related legislation from the 103rd (1993–94) to the 115th (2017–18) Congresses, we find that both gender and party influence members’ voting behavior. Among Republicans, women are more likely than men to oppose pro-life initiatives, although the impact of gender attenuates over time. Among Democrats, apparent gender differences in voting behavior are explained by the nature of the districts they represent. We also find that the type of abortion issue impacts the influence of gender. Republican women are more likely than Republican men to defect on policies that highlight women's autonomy, such as on bills related to contraception, while Democratic men are more likely than Democratic women to support legislation related to abortion bans. These gender differences reflect a complex dynamic of members’ responsiveness to public opinion on specific issues and party efforts to influence that opinion in ways that favor perceptions of party issue expertise.

In this study an index is developed called the Transit Economic Equity Index, to enable quantitative assessment of transit service equity. The index measures convenience of travel for work trips for advantaged and disadvantaged populations, based on travel speed, using a multimodal network that includes transit lines, stop locations, transit schedules, and pedestrian connections via the street network. Non-peak hour service is compared with peak hour service to determine the degree to which operating resources are concentrated in times that might have greater benefits to advantaged populations. Finally, accessibility to the transit system is compared in relation to the number of transit stops in neighborhoods and employment centers, and these figures are compared between advantaged and disadvantaged locations. The scores for these three components are combined to create a single measure of transit economic equity. Disadvantage is defined using criteria established in Title VI of the Civil Rights Act of 1964. The index is constructed in a way that balances a robust and meaningful measure of transit equity that is decipherable by practitioners so that they can assess the equity of their systems as well as how potential service changes affect equity.

In early 2020, just as the COVID-19 pandemic started to affect the health of millions around the world, epidemiologists and public health experts pointed to social distancing as the key measure to control the spread of the virus. From an economic perspective, it became immediately clear that the ability to work from home would determine workers’ outcomes.

As a central component of the smart city, sensor infrastructures locate and measure a wide range of variables in order to characterise the urban environment. Perhaps the most visible expression of the smart city, sensor deployment is a key equity concern. As new sensor technologies and Big Data interact with social processes, they have the potential to reproduce well-documented spatial injustices. Contrary to promises of providing new knowledge and data for cities, they can also create new gaps in understanding about specific urban populations that fall into the interstices of data collection – sensor deserts. Building on emerging data justice debates, specifically considering distributional, recognition, and procedural forms of injustice, we conceptualise and analyse sensor deserts through two case studies, Newcastle's Urban Observatory (UK) and Chicago's Array of Things (USA). Open sensor locations are integrated with small-area, socio-economic data to evidence the demographic configuration and spatialities of sensor deserts across each city. We illustrate how the structural processes via which inequality is reinforced by smart agendas manifest as uneven social and spatial outcomes. In doing so, the paper opens up a new conceptual space in which to consider what it means (not) to count in the smart city, bringing a demographic perspective to critical debates about smart urbanisms.

When using differential privacy to publish high-dimensional data, the huge dimensionality leads to greater noise. Especially for high-dimensional binary data, it is easy to be covered by excessive noise. Most existing methods cannot address real high-dimensional data problems appropriately because they suffer from high time complexity. Therefore, in response to the problems above, we propose the differential privacy adaptive Bayesian network algorithm PrivABN to publish high-dimensional binary data. This algorithm uses a new greedy algorithm to accelerate the construction of Bayesian networks, which reduces the time complexity of the GreedyBayes algorithm from OnkCm+1k+2 to Onm4. In addition, it uses an adaptive algorithm to adjust the structure and uses a differential privacy Exponential mechanism to preserve the privacy, so as to generate a high-quality protected Bayesian network. Moreover, we use the Bayesian network to calculate the conditional distribution with noise and generate a synthetic dataset for publication. This synthetic dataset satisfies ϵ-differential privacy. Lastly, we carry out experiments against three real-life high-dimensional binary datasets to evaluate the functional performance.

This article examines referendums for open space conservation, focusing on an assessment of their likelihood in cities. It presents data on conservation referendums, over 15 years, based on the Trust for Public Land’s LandVote® database. Economic and institutional factors of influence are explored across cities, testing whether those factors explain differences in the likelihood of referendums and their passage. One finding is that the frequency of conservation referendums varies dramatically across American cities. Additional findings, from a pooled time-series analysis, are that economic and institutional contexts of cities affect the likelihood of conservation referendums. The likelihood of referendums and their passage is further tested across alternative models to evaluate the robustness of the findings. While its central contribution is to research on local referendums, the article connects to the political market framework to identify factors influencing the likelihood of open space referendums.

The COVID-19 outbreak has had devastating impacts on the restaurant industry, with 6 million workers losing work temporarily or permanently. Tipped restaurant workers, who are over two-thirds women, reported facing dramatically decreased tips and increased health risks and harassment in restaurants during the pandemic. This report documents the massive exodus of workers from restaurants, their reasons for leaving, and what would make them stay. The pandemic has had devastating impacts for women and mothers in particular, with many economists dubbing the crisis a “she-cession.”1 Even prior to the pandemic, working mothers already bore the brunt of domestic duties and were heavily concentrated in low wage jobs.2,3 As one of the largest employers of women and one of the largest employers of subminimum wage workers, the restaurant industry plays an outsized role in perpetuating inequality among women, particularly women of color.4,5 Not only must these women endure one the lowest wages in the country, but also experience higher levels of sexual harassment than any other industry in the country.6,7 This report documents women and mother’s experiences of the pandemic, and also how it has motivated many of them to leave the restaurant industry altogether.

The legal issues that impact rural people in the United States have been largely invisible to legal scholars, lawyers, judges, legislators, and the media. Unsurprisingly, people of color in rural areas have been particularly rendered invisible. This chapter demonstrates how using a New Legal Realism (NLR) framework can help remedy a failure in empirical and legal approaches in some legal scholarship that explicitly or implicitly purports to be of relevance to rural America, by requiring more rigorous questioning of framing assumptions, stereotypes, and forms of translation between social science and law. Legal and sociolegal scholars who would employ a more careful and inclusive empirical approach that would generate better data could help uncover the difficulties people of color in rural areas experience and could help improve perceptions about the actual conditions in many rural places. For example, such scholarship could help make clear that agricultural long ago ceased to be the main pillar of most rural economies, notwithstanding widespread incorrect assumptions to the contrary. The chapter concludes with examples of informed property law scholarship and policy initiatives, including the author’s own, showing how empirical research, media attention, and legal reform efforts can combine to substantially improve law and policy in rural areas.

A nascent body of research suggests that economic freedom is positively associated with entrepreneurial activity. Most of this literature is based on cross-countries analyses, although there is significant regional heterogeneity in entrepreneurial activity and the institutional and policy context within countries. The literature also largely overlooks the potential for the entrepreneurial inducing effects of economic freedom to drive less efficient firms out of the market. Additionally, economic freedom is a multi-dimensional construct comprised of numerous underlying aspects of the institutional and policy environment, but most studies have employed a composite economic freedom measure to assess its impact on entrepreneurial activity. I contribute to these gaps in the literature by decomposing the recently developed Metropolitan Economic Freedom Index into its underlying institutional indicators to explore their potential impact on the firm entry and firm exit rates for a sample of nearly 300 US cities over the period 1972–2012.

Less educated workers experience higher and more cyclically sensitive job separation rates. Meanwhile, workers with a bachelor's degree or more exhibit pro-cyclical wages and workers without a high school degree exhibit no statistically discernible cyclical pattern. Differences in the sensitivity are most stark when measurement of labor costs accounts for the persistent effects of current macroeconomic conditions on future remitted wages. These findings suggest optimally differential implementation of self-enforcing implicit wage contracts in which educated workers and their employers leverage relative employment stability to smooth the effects of cyclical fluctuations over longer horizons. This margin of adjustment is less available to the less well educated, who have shorter expected employment durations. Furthermore, failure to account for the heterogeneities documented here leads to substantial underestimation of the welfare costs of business cycles.

We go behind the scenes of our recent project on what it looks like to reconnect Black communities torn apart by highways.

We describe how racial and ethnic disparities among prime-aged men have evolved over the last 50 years. We examine several outcomes including annual earnings, employment, measures of income, and home ownership status using data from the March CPS, the Census, and the ACS. Both Blacks and Hispanics have experienced a 20-25% earnings disadvantage relative to whites since 1980. In terms of employment, the gap has been increasing for Blacks but decreasing for Hispanics. These differences are reflected in income and home ownership status. The disparities in earnings are similar across education groups but the disparities in employment are driven primarily by workers who have not completed high school. Comparing Hispanic immigrants with natives reveals that while native Hispanics fare better than Blacks, many of the employment and earnings gains are attributable to Hispanic immigrants.

Racial discrimination by housing and lending institutions occurs worldwide. In the United States, it was legal and widely practiced well into the 1960s and has persisted in varying forms since. The Home Owner's Loan Corporation (HOLC) was one of many institutions engaging in racially discriminatory practices and created neighborhood appraisal maps in the 1930s based in part on race, ethnicity, and economic class of a neighborhood's residents. Using these HOLC neighborhood boundaries, we compared 12 present day population characteristics including health, employment, education, and income measures in each of the four HOLC neighborhood ratings across 14 U.S. cities. We used population-weighted logistic regression for paired data comparison and unsupervised learning techniques to uncover the consistency between HOLC evaluations and today's socio-economic and health outcomes. While existing literature focuses on case studies of particular cities and outcomes, we took a broad view and found consistent relationships over our study's cities and variables with few exceptions. Though there are many factors that contribute to continued inequality in a particular area, this study demonstrates that socio-economic and health inequality measured across numerous indicators continues to align with historic discriminatory housing boundaries.