Critical migration scholarship examines cities’ economic, sociopolitical dimensions that not only shape migration patterns via a demand for migrant labor, but also forge complex social relations between migrants and their new neighbors. Drawing from critical migration theories, this study interrogates the dispersion or placement strategy of U.S. refugee policy, which resettles refugees into cities largely without a systematic, deliberative process. Meanwhile, refugee placement has become politicized. State and city governments are divided on resettling refugees in their jurisdictions. Using mixture model analysis, we examined city-level factors in 3000 U.S. cities where about 73,000 refugees were placed in 2010. Findings show that 90% of refugees were placed in just three types of resettlement cities: one parallels ‘traditional immigration gateways’ and two parallel ‘new immigrant destinations’. We find that what is salient in resettlement cities is not the availability of jobs per se, but that of low-wage jobs specifically, pointing to cities’ demand for refugee labor. Findings along sociopolitical dimensions suggest that the typical resettlement city is simultaneously anti-refugee in political party affiliation but have integrative local policies, reflecting tensions between “contact” and “threat” hypotheses in migration literature. This study reveals contradictions inherent to U.S. resettlement policy that heretofore has been undetected.

This article examines how the Affordable Care Act Medicaid expansions affected the sources of health insurance coverage of undergraduate students in the United States. We show that the Affordable Care Act expansions increased the Medicaid coverage of undergraduate students by 5 to 7 percentage points more in expansion states than in nonexpansion states, resulting in 17% of undergraduate students in expansion states being covered by Medicaid postexpansion (up from 9% prior to the expansion). In contrast, the growth in employer and private direct coverage was 1 to 2 percentage points lower postexpansion for students in expansion states compared with nonexpansion states. Our findings demonstrate that policy efforts to expand Medicaid eligibility have been successful in increasing the Medicaid coverage rates for undergraduate students in the United States, but there is evidence of some crowd out after the expansions—that is, some students substituted their private and employer-sponsored coverage for Medicaid.

In this project I investigate three sets of policy changes related to overtime penalties, school bond measures, and police training. I study the effects that these policy changes have had on labor market and other outcomes. In the first chapter, I examine how the demand for labor and the categorization of labor change in response to a change in penalties for overtime violations. I propose a model for determining labor demand for fully compensated overtime hours, undercompensated overtime hours, and total hours when employers rationally undercompensate overtime labor. I find evidence that, following a decrease in the expected penalty for state overtime violations in Massachusetts, the average number of undercompensated and fully compensated overtime hours worked increased, while the average number of nonovertime hours worked decreased. There is little evidence that employers responded to the change in penalties by reclassifying workers as exempt or nonexempt from the overtime law. In the second chapter I use multiple methods to examine how school bond measures, and the accountability measures associated with the bond measures, affect home prices and teacher labor market outcomes. I find evidence that school bonds passed with a 55% passage threshold are correlated with increases in home prices and average teacher salaries. The findings are reversed for bonds passed with a two-thirds passage threshold, which are correlated with reductions in home prices and teacher salaries. The findings suggest that the accountability measures for school bond measures do influence the way the bonds are used, and have downstream effects on home prices and teacher labor market outcomes. In the final chapter, I evaluate how different types of police training may affect the conduct of police officers. I find that increased Peace Officer Standards and Training (POST) funding leads to a small temporary decrease in civilian complaints sustained. Increased POST funding is also correlated with decreases in police shootings in each of the following three years, though these results are statistically indistinguishable from zero. Differences between how POST and non-POST training programs cover various topics—such as those related to mental health, professionalism, and rights—may explain these results. Policymakers may look to investing in increased police training funding from the state to improve policing outcomes.

Nicholas Eberstadt’s landmark 2016 study, Men Without Work, cast a spotlight on the collapse of work for men in modern America. Rosy reports of low unemployment rates and “full or near full employment” conditions, he contends, were overlooking a quiet, continuing crisis: Depression-era work rates for American men of “prime working age” (25–54). The grim truth: over six million prime-age men were neither working nor looking for work. Conventional unemployment measures ignored these labor force dropouts, but their ranks had been rising relentlessly for half a century. Eberstadt’s unflinching analysis was, in the words of The New York Times, “an unsettling portrait not just of male unemployment, but also of lives deeply alienated from civil society.” The famed American work ethic was once near universal: men of sound mind and body took pride in contributing to their communities and families. No longer, warned Eberstadt. And now—six years and one catastrophic pandemic later—the problem has not only worsened: it has seemingly been spreading among prime-age women and workers over fifty-five. In a brand new introduction, Eberstadt explains how the government’s response to Covid-19 inadvertently exacerbated the flight from work in America. From indiscriminate pandemic shutdowns to almost unconditional “unemployment” benefits, Americans were essentially paid not to work. Thus today, despite the vaccine rollouts, inexplicable numbers of working age men and women are sitting on the sidelines while over 11 million jobs go unfilled. Current low rates of unemployment, touted by pundits and politicians, are grievously misleading. The truth is that fewer prime-age American men are looking for readily available work than at any previous juncture in our history. And others may be catching the “Men Without Work” virus too. Given the devastating economic impact of the Covid calamity and the unforeseen aftershocks yet to come, this reissue of Eberstadt’s groundbreaking work is timelier than ever.

Sub-Saharan Africa is the least urbanized region in the world. Yet, home to the world’s youngest and fastest-growing population, Africa has recorded faster urban growth than any other world region since 1960. Its urban population has been growing at an average annual rate of 4%–5% since 1960, at much lower income levels than Asia or Latin America. The United Nations forecasted that Africa’s urban population is likely to nearly triple between 2018 and 2050. Cities are viewed as important engines of African economic growth, generating a much larger share of countries’ GDP than their share of the population (McKinsey 2011; UN-Habitat 2016a). Cities are thus attractive to those in search for economic opportunity. Cities not only ofer higher wages than rural areas, but urban housing, schools, and health facilities also tend to be superior. Such perspectives of urban privilege, upward social mobility, and opportunity remain dominant motivations for rural-urban migration in Africa.

Who dies in police custody? Where? To answer these questions, we use spatially disaggregated georeferenced data that measure 9098 deaths occurring by multiple causes during interactions with police throughout the U.S. from 2016 to 2020. We use a Sociospatial Ecology framework and Bayesian statistics over U.S. counties that establishes the relationship between social contexts – regional poverty, White/non-White population, violent crime rates, and political identity – and the risk of dying during police interactions. In addition, we evaluate the effects of police force Whiteness on deaths during police interactions. Controlling for alternative explanations, we show heterogeneous distributions of fatality risk, with large clusters in the Southwest and isolated high-probability pockets in other states. Risk maps allowing for visualization of these patterns are provided. We arrive at five main results. 1) There is a general trend of higher death during police interaction in areas of high poverty, fewer White people, higher violent crime rates, and higher populations with conservative values. 2) A great risk of deadly encounters for Black people exists throughout most of the U.S., while regional patterns of high risk exist for all other people of color. 3) White deaths during police interactions are most sensitive to ecological factors. 4) The risk of Blacks getting killed by police increases in White areas regardless of violent crime rates. 5) Higher proportions of White police within U.S. counties leads to higher interactive death risk for all races/ethnicities except Asian/Pacific Islander. Ultimately, our findings identify widespread racial/ethnic biases in situations of power and control.

Increasing the racial diversity of the physician workforce can reduce Black-White gaps in life expectancy. However, relative to the 13% of the US population who are Black, the proportion of physicians who are Black remains low at 5%. Alongside this low representativeness are substantial racial differences in physician incomes, particularly among male physicians. Historical trends in the racial diversity of physicians and in racial differences in their incomes are unknown and may provide a better sense of progress made in these areas.

In 2018, more than 43 million people, or 16.9 percent of the population in the United States, held a professional certification or license. Licensing regulations cover nearly 30 percent of occupations and have become a central labor market policy that shapes employment opportunities for many workers. Because of the enormous benefits, such as licensing wage premium and positive signals in the labor market, acquiring licenses has been extremely popular among workers over the last 60 years. In 2019, 44.9 million immigrants born in other countries and from different cultures resided within the United States. They work in numerous occupations and contribute to our economy and society. However, after migration, immigrants face vast barriers in finding matched occupations, applying for licenses, developing their careers, and improving their social status. These barriers, such as language ability and lack of citizenship and residency, further deteriorate their vulnerable situation. This dissertation investigates several social and economic issues in occupational licensing and immigration. We examine: 1) Licensing behavior and the changes in labor market outcomes through licensing in immigrants and their cohorts, 2) The labor market effects of granting occupational licenses to the Deferred Action for Childhood Arrivals (DACA) program recipients in states, and 3) The dynamic impacts of granting licenses to DACA recipients on their labor market outcomes using the synthetic control approach. To address the first question, this dissertation examines the likelihood of immigrants in different cohorts getting occupational licenses and the impacts of licensing on the labor market outcomes using two datasets: The Current Population Survey (CPS) and Survey of Income and Program Participation (SIPP). We found that immigrants, especially new and high-skilled immigrants, are less likely to get licenses than similar natives. However, the longer immigrants stay in the U.S. after migration, the higher the possibility of getting a license. In addition, immigrants gain significantly lower wages than similar natives in all cohorts, but the cohort of new immigrants performs relatively better in the labor market mainly because they are more educated and highly skilled. Overall, licensing reduces the wage gap between natives and immigrants. However, recent immigrants receive the lowest licensing wage premium among all cohorts, and somehow licensing expands rather than closes this wage gap in younger cohorts. We find that compared to native workers, only immigrants able to be licensed from English-speaking areas do relatively well, but immigrants from developing countries seem to do worse, even after acquiring a license. Moreover, the ability of an immigrant to speak English provides higher wages, but this positive effect gradually disappears during more years in the host country since migration. Finally, acquiring certain licenses, such as cosmetology, is not a successful labor investment for immigrants. Moreover, this dissertation further explores the relationship between the policy changes in occupational licensing and undocumented immigrants, specifically DACA recipients, using Difference-in-Difference estimators and a more advanced approach, Synthetic Control Method. The results prove that granting licenses raises recipients’ wages by at least 12 percent. In addition, male recipients or recipients older than 24 are more positively affected by this policy change. However, all these positive impacts are only short-term and dissipate over time. Together these findings suggest that access to public benefits, including licensing, yields meaningful benefits for DACA recipients, but we are still questioning how effective this policy change is in the long term.

Promoting electric vehicles (EVs) has been a major goal of the US government to combat climate change, but the role that the EV fast charging network plays is relatively understudied. In this paper, I investigate Tesla's investment in its network of fast charging stations (called Supercharging stations) as a tool to increase the attractiveness of its EVs and how that incentive interacts with EV purchase subsidies. I develop a structural model that consists of three components: consumer demand for new vehicles, pricing competition among automak-ers, and Tesla's investment in its Supercharging network. The demand model incorporates consumer heterogeneity reflecting fast charging accessibility in their home counties and along their travel routes. Tesla's investment decision features various locations in communities and along highway corridors, and is rationalized by the profitability of its vehicle sales. I follow the revealed preference approach used by Holmes (2011) and Houde et al. (forthcoming) to set-identify investment cost parameters. The results show that consumers value access to in-community and along-highway fast charging almost equally, and the presence of either is equivalent to a 4 percent drop in vehicle prices. The counterfactual analysis shows that EV purchase subsidies have an expansionary effect on the Supercharging network. The effect is larger for in-community locations and depends on the demographics of the location. This paper also shows that ignoring the effect of the Supercharging network on demand or Tesla's adjustments to its network underestimates the positive effect of EV purchase subsidies on consumer welfare and emission reductions.

The COVID-19 pandemic has dramatically disrupted the United States labor market, and many commentators have interpreted the ongoing labor dynamics as evidence of a “Great Resignation”, emphasizing workers’ dissatisfaction with their employment situation as a significant instigator of labor market uncertainty. In this paper, I develop an indexed “lousiness” score for a given occupation based on occupational survey data. I then track the rebound in employment and labor force participation in the wake of the COVID-19 pandemic for workers within “lousy” and “non-lousy” occupations, revealing a sizable gap between their respective rates of return throughout 2020 and 2021. I then use industry-level data from the Job Openings and Labor Turnover Survey to calculate aggregated hiring and quit rates over time, revealing a larger increase in employee-initiated churn rates for industries with a high concentration of “lousy” occupations since the summer of 2020. This supports the perception that employee concerns about flexibility, safe working conditions, and emotional stress are affecting their employment choices and labor force participation rates to a greater degree than before COVID-19.

I analyze the value workers ascribe to the gender composition of their workplace and the consequences of these valuations for occupational segregation, tipping, and welfare. To elicit these valuations, I survey 9,000 US adults using a hypothetical job choice experiment. This reveals that women value gender homophily in the workplace and men value gender diversity. Older female workers are more likely to value gender homophily, suggesting that gender norms and discrimination, which have declined over time, may help explain women's desire for homophily. Using these results, I estimate a structural model of occupation choice to assess their consequences for gender sorting and welfare. I find that workers' average composition valuations are not large enough to create tipping points, but they do reduce the female share in male-dominated occupations substantially. Gender composition valuations also create a sorting externality: a welfare-maximizing social planner would reallocate workers to substantially decrease segregation, improving consumption-equivalent welfare by about 2%.

We study the influence of agricultural labor intensity on individualism across U.S. counties. To measure historical labor intensity in agriculture we combine data on crop-specific labor requirements and county-specific crop mix around 1900. To address endogeneity we exploit climate-induced variation in crop mix. Our estimates indicate that an increase of one standard deviation in labor intensity is associated with a reduction of 0.2-0.4 standard deviations in individualism (as captured by the share of children with infrequent names). We further document consistent patterns using within-county changes in labor intensity over time due to both mechanization and the boll weevil shock. While culture transformed in response to changes in labor intensity, we also find that historical agricultural patterns had a lasting imprint that influences geographic variation in individualism today.

Data collection under local diferential privacy (LDP) has been gradually on the stage. Compared with the implementation of LDP on the single attribute data collection, that on multi-dimensional data faces great challenges as follows: (1) Communication cost. Multivariate data collection needs to retain the correlations between attributes, which means that more complex privatization mechanisms will result in more communication costs. (2) Noise scale. More attributes have to share the privacy budget limited by data utility and privacy-preserving level, which means that less privacy budget can be allocated to each of them, resulting in more noise added to the data. In this work, we innovatively reverse the complex multi-dimensional attributes, i.e., the major negative factor that leads to the above diiculties, to act as a beneicial factor to improve the eiciency of privacy budget allocation, so as to realize a multi-dimensional data collection under LDP with high comprehensive performance. Speciically, we irst present a Multivariate k-ary Randomized Response (kRR) mechanism, called Multi-kRR. It applies the RR directly to each attribute to reduce the communication cost. To deal with the impact of a large amount of noise, we propose a Markov-based dynamic privacy budget allocation mechanism Markov-kRR, which determines the present privacy budget (lipping probability) of an attribute related to the state of the previous attributes. Then, we ix the threshold of lipping times in Markov-kRR and propose an improved mechanism called MarkFixed-kRR, which can obtain more optimized utility by choosing the suitable threshold. Finally, extensive experiments demonstrate the eiciency and efectiveness of our proposed methods.

Through the work of the House and Senate chief patrons: Delegate Delores L McQuinn (HB 142) and Senator George L. Barker (SB 342) changes to the Transit Ridership Incentive Program (TRIP) intended to increase funding to reduce the impact on public transit fares on individuals with low-incomes were signed into law during Virginia’s 2022 legislative session. House Bill (HB 142) and Senate Bill (SB 342) builds on 2020 legislation establishing TRIP to promote improved transit service in urbanized areas 1 of the Commonwealth with a population of more than 100,000 and to reduce barriers to transit use for low-income individuals. The identified goal of the Transit Ridership Incentive Program as established in 2020,1 is to increase regional connectivity and fund initiatives to lower public transportation costs to lowincome riders by encouraging “the identification and establishment of routes of regional significance, the development and implementation of a regional subsidy allocation model, implementation of integrated fare collection, establishment of bus-only lanes on routes of regional significance, and other actions and service determined by the Board to improve transit service” (LIS, 2022). Language in the 2020 legislation creating TRIP limited funds for reduced and zerofare transit to 25% of the program with the remaining 75% of the funding dedicated to regional connectivity(LIS, 2022). HB 142/SB 342 (2022) removed this limitation on funding, allowing for greater opportunity to fund reduced and zero-fare transit in Virginia. Per Virginia Department of Rail and Public Transportation (VDRPT) “$24.5 million to multi-year zero-fare/low income projects and $5.2 million to multi-year regional connectivity projects has been allocated”. An example of such an award was announced in a press release by Greater Richmond Transit Company (GRTC). On December 21, 2021, it was announced that $8 million was awarded to GRTC to study zero fares. Effective July 1, 2022, the Transit Ridership Incentive Program (TRIP) removed the maximum threshold of funding of 25% and instead established a minimum of 25% of TRIP funding going towards reduced or zero-fare transit initiatives. The proposed percentage of the TRIP funds will continue to support the establishment of programs to reduce the impact of fares on low-income individuals in the coming years. Unfortunately, a sunset clause was inserted as a Governor’s amendment meaning this change is set to expire on July 1, 2024. As the original legislation that passed the House and Senate was the result of a strong majority of bi-partisan support, based on the research, an extension of the current July 1, 2024 expiration date, or the elimination of the sunset clause is advised. To avoid the barriers for low-income individuals, it has been noted that “Virginia’s program could target low-income individuals through passes or by eliminating fares on certain high-capacity corridors or for entire transit systems'' (Pascale, 2021).

The decades-long rising housing market in the United States requires an in-depth understanding of the mechanism shaping the sustained high housing prices. This paper tries to ask the question from the perspective of changes in housing demand, specifically, how would property tax negatively affect housing prices. This is known as standard capitalization theory, first proposed by Oates (1969) and Yinger (1982). I intend to test for such relationship in the paper. Given the evaluation of the relationship is often obstructed by endogeneity of property tax to public goods provision and by the unobserved differences in neighborhood characteristics, a quasiexperiment design is needed. I utilized a property assessment reform that decreased property tax rate in early 2000s Indiana, by looking within boundary counties located at each side of Indiana. Since the Indiana reform is largely exogenous, counties then only differ by the level of property tax rates. Thus, I effectively isolate the impacts of property tax on house prices, with the help of an event study method. I found that as houses in Indiana are subject to a property tax rate cut of around 5.66%, their prices grow by 4.09% in the year of the tax change – for every 1% drop in property tax rate, house prices increase by 0.72%. The finding holds up to different sensitivity checks. But such relationship vanishes around 3-7 years after the policy change. To further examine the mechanism behind the lack of long-term capitalization effects, I concluded that even though demand for owner occupancy did increase, the long-term supply for owner occupied housing is elastic enough to offset the change and caused the zero results. The findings highlight the significant role of supply in shaping the long-term capitalization effects. They also shed light on the importance of effective measures in maintaining housing prices and ownership in regions where owner occupants have been priced out of the property market.

Suicide is steadily rising. Many blamed worsening economic conditions for this trend. Sociological theory established clear pathways between joblessness and suicide focused on status threat, shame, and consequent disruption of social relationships. However, recent empirical research provides little support for a link between unemployment and suicide. I attempt to reconcile this contradiction by focusing on white suicide and white employment-to-population ratio. Whiteness is not just a default category but a pervasive ideology that amplifies the effects of status loss. The white employment-to-population ratio represents a form of racialized economic threat and accounts for discouraged workers who have exited the labor force. I use longitudinal hybrid models with U.S. state-level data, 2000 to 2016, and find that decreasing employment is associated with increasing suicide among the white population and white men. I discuss this study’s contributions to the literature on suicide and joblessness and the emerging scholarship on whiteness and health.

Background: Culturally tailored interventions may reduce disparities in diabetes care. We conducted a nationally representative assessment of self-reported cultural competency measures of care among patients with diabetes in the United States. Methods: The 2017 National Health Interview Survey was queried for adults with self-reported diabetes. Sample weight-adjusted multivariable logistic regressions defined adjusted odds ratios and 95% confidence intervals of a positive response to each of the cultural competency measures while controlling for relevant sociodemographic variables. Findings: 2,448 adults were included in the analyses. Black, Latinx, and Asian respondents had greater odds of and individuals with the highest income level had lower odds of placing greater importance in sharing cultures with their provider. Black and Latinx individuals had lower odds of reporting encountering providers who shared or understood their cultures. Asians had lower odds of and respondents aged 40-64 and 65 years and older had greater odds of reporting frequently being treated with respect by their providers. Non-English speakers had lower odds of and individuals from higher income brackets had greater odds of reporting frequently receiving easy-to-understand information about their care. Blacks and respondents not part of the workforce had greater odds of reporting frequently being asked about their opinions or beliefs in care. Interpretation: Disparities in self-reported provider cultural competency measures exist among cultural minorities in the United States. Our findings may inform efforts to reduce disparities and improve care among minorities with diabetes. Funding: No funding was used in the preparation of this work.

Editor—The increasing prevalence of opioid-related deaths across the USA prompted the US Department of Health and Human Services to declare opioid overdoses a public health crisis in 2017. 1 ,2 Here we hypothesised that disaggregating opioid-related overdose deaths and intention by race will uncover differences in geography, age, and opioid overdose intention within the USA. To test our hypothesis, we conducted an observational, cross-sectional study utilising death certificate data from the US National Vital Statistics System (NVSS) dataset containing vital events from 2005 to 2017 under a data use agreement. This study was approved by the Stanford Institutional Review Board (#53429) as non-human subject research.

We explore the labor market for Hispanic high school graduates in the United States by age using information from the US Census, American Community Survey, Current Population Survey, and three laboratory experiments. We find, in general, that the differences in outcomes for Hispanic and non-Hispanic high school graduates do not change across the lifecycle. Moving to a laboratory setting, we provided participants with randomized resumes for a clerical position that are on average equivalent except for name and age (as indicated by date of high school graduation). In all three experiments, hypothetical applicants with Hispanic and non-Hispanic names were generally treated the same across the lifecycle by a student population, a population of human resources managers, and a more general population from mTurk. These results stand in contrast to earlier results that find strong differences by age in how resumes with Black and White names are treated.

Objective: This study examined the association between social determinants of health (SDOH) burden and overweight/obesity in a nationally representative sample of adults in the United States. Methods: Data for 161,795 adults aged ≥18 years from the 2013 to 2017 National Health Interview Survey were used. A total of 38 SDOH were aggregated to create a cumulative SDOH score, which was divided into quartiles (Q1-Q4) to denote levels of SDOH burden. Prevalence of overweight and obesity was examined across SDOH quartiles in the total population and by age, sex, and race/ethnicity. Multinomial logistic regression models were used to analyze the association between SDOH quartiles and overweight/obesity, adjusting for relevant covariates. Results: There was a graded increase in obesity prevalence with increasing SDOH burden. At nearly each quartile, overweight and obesity rates were higher for middle-aged and non-Hispanic Black adults compared with their counterparts; additional differences were observed by sex. In fully adjusted models, SDOH-Q4 was associated with 15%, 50%, and 70% higher relative prevalence of overweight, obesity class 1 and 2, and obesity class 3, respectively, relative to SDOH-Q1. Conclusions: Cumulative social disadvantage, denoted by higher SDOH burden, was associated with increased odds of obesity, independent of clinical and demographic factors.