Research suggests that racial/ethnic disparities in COVID-19 in the US are largely driven by higher rates of exposure to SARS-CoV-2 among Hispanic/Latino and Black populations. Occupational exposures play a large role in structuring risk of exposure, and essential workers are at elevated risk of COVID-19 infection. At a national-level, workers categorized as “essential” and “high-risk” are disproportionately Hispanic/Latino, but we lack analysis examining local-level racial/ethnic disparities in potential occupational exposures. Using the 2015–2019 5-year American Community Survey, we estimated disparities between the proportion of US Born Hispanic/Latino, foreign-born Hispanic/Latino, and non-Hispanic white (NHW) essential or high-risk workers in 27 of the largest metropolitan areas in the country. We found that, on average, 66.3%, 69.9%, and 62.6% of US-born Hispanics, foreign-born Hispanics, and NHW, respectively, are essential workers, while 50.7%, 49.9%, 49.5% are high exposure risk workers, respectively. The median absolute difference in proportions of US born Hispanic/Latino and NHW essential workers was 4.2%, and between foreign-born Hispanic/Latino and NHW essential workers was 7.5%, but these disparities varied widely by city. High likelihood of occupational transmission may help explain disparities in COVID-19 infection and mortality for Hispanic/Latino populations, especially foreign-born, and may also help explain heterogeneity in the magnitude of these disparities, with relevance for other acute infectious respiratory illnesses spread in the workplace.

The mounting evidence on the demographics of COVID-19 fatalities points to an overrepresentation of minorities and an underrepresentation of women. Using individual-level, race-disaggregated, and georeferenced death data collected by the Cook County Medical Examiner, we jointly investigate the racial and gendered impact of COVID-19, its timing, and its determinants. Through an event study approach we establish that Blacks individuals are affected earlier and more harshly and that the effect is driven by Black women. Rather than comorbidity or aging, the Black female bias is associated with poverty and channeled by occupational segregation in the health care and transportation sectors and by commuting on public transport. Living arrangements and lack of health insurance are instead found uninfluential. The Black female bias is spatially concentrated in neighborhoods that were subject to historical redlining.

The US suffers from persistent regional disparities in employment rates. In principle, these disparities should be eliminated by population mobility. Can immigration fulfill this role? Remarkably, since 1960, I show that new migrants from abroad account for 40% of the average population response to these disparities - which vastly exceeds their historic share of gross migratory flows. But despite this, immigration does not significantly accelerate local population adjustment (or reduce local employment rate disparities), as it crowds out the contribution from internal mobility. Indeed, this crowd-out can help account for the concurrent decline in internal mobility. Finally, I attribute the “excess” foreign contribution to a local snowballing effect, driven by persistent local shocks and the dynamics of migrant enclaves. This mechanism raises challenges to the (pervasive) application of migrant enclaves as an instrument for foreign inflows. But rather than abandoning the instrument, I offer an empirical strategy (motivated by my model) to overcome these challenges; and I demonstrate its efficacy.

Cancer incidence and mortality are typically presented as age-standardized rates. Inference about these rates becomes complicated when denominators involve sampling errors. We propose a bias-corrected rate estimator as well as its corresponding variance estimator that take into account sampling errors in the denominators. Confidence intervals are derived based on the proposed estimators as well. Performance of the proposed methods is evaluated empirically based on simulation studies. More importantly, advantage of the proposed method is demonstrated and verified in a real-life study of cancer mortality disparity. A web-based, user-friendly computational tool is also being developed at the National Cancer Institute to accompany the new methods with the first application being calculating cancer mortality rates by US-born and foreign-born status. Finally, promise of proposed estimators to account for errors introduced by differential privacy procedures to the 2020 decennial census products is discussed.

Although historically dairy farming has had higher social favorability as compared to other livestock species, this appears to be changing. Evidence from recent public surveys indicates that the majority of respondents in the U.S. were concerned about dairy cattle welfare (Wolf et al. 2016; Busch et al. 2017). Amongst the range of current issues, concerns about calf-dam separation at birth and calf housing are at the forefront. The former is a peculiar challenge for the dairy industry as it is unique to the industry (compared to other farmed mammals) (Costa, Von Keyserlingk and Weary 2016). The common practice in the management of other domestic livestock, such as beef and hogs, is to keep offspring with the mother for a longer period of time, making it seem like a more natural process. The practice of separating the calf from the cow has become commonplace since the 1950s. Proponents of this practice, mostly farmers and veterinarians, argue that: allowing the cow and calf to bond will result in greater separation distress when the separation does occur later; the calf may become infected from pathogens carried by the cow or her environment; the calf may become injured by adult cows/ barn equipment as farms are often not well designed for cow-calf pairs; and, reductions in the cow's milk yield. Others, mainly some members of the public, oppose this practice and argue that: calf-dam contact is an important element of natural behavior; early calfdam separation causes emotional distress to both calf and dam and that keeping them together is beneficial to both the dam and calf. There may be opportunities for farmers to meet consumers' concerns. However, this is predicated upon a proper understanding of consumer preferences. The range of options include free-dam contact, half-day contact, foster-cow system, and restricted calf-dam contact. These options differ in cost to farmers, milk productivity and impact on farm animal welfare (FAW). For example, farmes can reduce milk yield losses through a restricted calf-dam versus a foster cow system, calf-dam contact may be limited in the former1 . The latter may allow calves to stay bonded with a cow as well as develop social behaviors with fellow newborns. Further, it is also plausible that dairy farmers may ameliorate consumer concerns about calf separation by choosing housing methods that allow calves to interact with other calves once they are separated from their mothers. Previous research suggests that consumers prefer group housing to individual housing (Gaillard et al. 2014; Wormsbecher et al. 2017). The tradeoffs for increased animal welfare specific to calf management practices have not, however, been assessed. This paper examines consumer preferences for different calf retention practices in their milk purchase decision. Insights from this study are relevant to dairy industry stakeholders looking to effectively address calf welfare concerns on dairy farms and enhance the long term social and economic sustainability of the dairy industry. Indeed, there is a growing interest in the role of vertically differentiated process attributes, such as calf welfare practices on dairy farms, in consumer decision making with regards to the final product (milk). There is also the rise in ethical food behaviors. Added to this is the availability of plant-based alternative milk beverages often marketed as healthier, tastier, and more animal welfare friendly. These market dynamics have engaged the attention of academics, industry, and policy makers looking to identify points of convergence amongst multiple interest. The findings of this study can provide the basis for discussion on the provision of adequate calf welfare on dairy farms that balances consumer and farmer goals.

Middle-tier occupations, which require some training or education beyond high school but less than four years of college, are an important source of employment for the 62 percent of New York City adults who lack a bachelor’s degree. A disproportionate share of New York middle-tier jobs are in the health care sector, which is expected to grow rapidly in the wake of the Covid-19 pandemic as the population ages and requires more medical care. Data from the New York State Department of Labor paint a picture of the health care industry before the pandemic, revealing a wide range of labor market outcomes for middle-tier workers. Some jobs, such as radiologic technologists, pay more than $87,000 per year despite not requiring a bachelor’s degree. Other middle-tier jobs, such as medical assistants, pay less but offer opportunities for career advancement. Though there are important exceptions, most middle-tier health care jobs pay at least a living wage, making them a key source of economic opportunity for New Yorkers without a four-year college degree. Demand for middle-tier workers has remained robust throughout the pandemic. Even as the health care sector struggled overall in 2020, the number of job openings for midlevel workers expanded, according to data from Burning Glass Technologies. Interviews with New York health care employers explain why this was so: middle-tier workers are the backbone of virtually all health care services, whether in a hospital, a nursing home or an ambulatory care center, so their jobs remain resilient even in tough economic times. Although no one knows for certain how the aftermath of the Covid pandemic will affect the health care sector, four other long-term trends are also reshaping the field. The aging population will generate increased demand for medical care. Growing skepticism of nursing homes will mean more seniors seeking care at home. Technological change will create demand for workers adept with new machines and information technology, and shifting business models will intensify employer concern about labor efficiency. All four trends are likely to reinforce demand for midlevel health care workers. Most middletier health care jobs are difficult to automate, and over the coming decade, many are expected to grow significantly faster than the average rate for all US jobs. The question in New York City: are education and training providers, including the City University of New York, equipped to produce the skilled health care workers likely to be needed in years ahead? Governments have a role to play in ensuring that education and training programs can accommodate increased demand. But what’s needed goes beyond public policy. Middle-tier health care workers deserve more respect. They are the cornerstone of the health care sector and all but certain to remain so for years to come.

This project contains public use data, instructions, and code to replicate results for "When Innovation Goes Wrong: Technological Regress and the Opioid Epidemic."

The pattern of U.S. imports has changed dramatically in recent decades, mainly because of an unprecedented rise in imports from China. This new pattern has coincided with a resurgence of increasing wage inequality between high-skill and low-skill labor which has reignited a long-standing interest in the possibility that imports drive inequality. We investigate this issue using a production theory approach. Unlike competing methodologies, our model accounts not only for the capacity of imports to displace, but to also stimulate, demand for domestic labor. Our results suggest that imports are not the culprit of wage inequality. Importantly, we find that imports from China foster wage-convergence rather than inequality. Our results further suggest that capital accumulation and technical change may well be the main causes of increasing inequality.

The Midwestern cities of Pittsburgh and Detroit are often held up as quintessential examples of post-industrial urban trajectories—one positive (Pittsburgh) and one negative (Detroit). In this paper, we investigate the structural economic shifts reshaping work opportunities in these two urban regions in the aftermath of the 2008 Great Recession, using a shift share analysis of changes in occupational distributions from 2009 to 2016. Through this analysis, we identify comparable patterns in both cities, including the growth of creative workers across industries, and declining demand for service workers balanced only by growth in service-reliant industries. These findings add nuance to the prevailing narratives associated with Detroit and Pittsburgh, and demonstrate how structural forces intersect with understandings of “work” in these cities.

Local governments are facing large losses in revenues and increased expenditures because of the COVID-19 crisis. We document a causal relationship between fiscal pressures induced by COVID-19 and the layoffs of state and local government workers. States that depend more on sales tax as a source of revenue laid off significantly more workers than other states. The CARES Act’s provision of $150 billion in aid to state and local governments reduced the fiscal pressures they faced. Exploiting a kink in the formula for allocation of funding across states, we estimate a state and local government employment multiplier for federal aid—each dollar of federal aid was used by states to support 31 cents of payrolls. State rainy day fund balances limit the sensitivity of employment to both revenue shocks, revealing that balanced budget requirements for state and local governments increase the procyclicality of public service provision.

Seeking to understand the role played by labor market structure in affecting economic inequality, we examine the extent to which the public sector, as compared to the private sector, differentially employs and rewards women, Blacks and subgroups classified by race and gender (e.g., Black women, Black men). Analyzing data from the American Community Survey (2014–2015), we find that public-sector employment is more attractive for Blacks than for women; Blacks’ odds of becoming public-sector employees are much higher than those of Whites, regardless of gender. No evidence was found for the argument that gender interacts with race in affecting the tendency to work in the public sector. As for wages, despite recent trends pointing to a decline in the advantages of the public sector for Blacks, it is still found to be more protective of Blacks, men and women alike. The meaning of the findings and their implications are discussed in light of structural barriers of gender and race inequality.

A new case for immigration restrictions argues that migrants may transmit low productivity to their destination countries by importing low-quality economic institutions. Using the 1986 Immigration Reform and Control Act (IRCA) as a natural experiment, we test whether the legalization of undocumented immigrants affects the quality of state-level economic institutions in the United States. Using synthetic control models, we find that, in the short run, legalization may increase the burden of government spending. However, in the long run, we find statistically insignificant effects of legalization on economic institutions.

Employers' reliance on salary history in hiring and compensation decisions is a textbook example of structural bias. While the common practice of asking a job applicant about their prior salary may seem innocuous on the surface, it can have unintended, harmful consequences, including barring qualified candidates from job opportunities and systematically relegating women and workers of color-particularly women of color-to lower pay that may have been set lower because of discrimination. Many employers use salary history as a metric to screen, evaluate, or compare applicants; set compensation; or negotiate salaries. However, the practice relies on false assumptions and biases about the relationships among salary, worker value, and market value, rendering it ineffective as well as harmful. In addition to perpetuating wage disparities, reliance on prior salary is unnecessary given other available, less bias-informed factors that employers could use to gauge a candidate's value. Moreover, salary history can provide a convenient rationale for employers who seek to justify pay disparities or depress wages. Limiting employer reliance on salary history in hiring and compensation decisions would help eliminate a form of structural bias and is therefore an important component of a broader, comprehensive effort to narrow the gender wage gap and secure equal pay for working women. This issue brief details the connections among salary history, equal pay, and the gender wage gap; examines the legislative landscape at the local, state, and federal levels; and recommends the Paycheck Fairness Act as a federal policy solution.

We investigate the relationship of the new wave of digitalization of occupations with entry into different types of entrepreneurship in the United States, including entry into digital entrepreneurship. Based on the Current Population Survey for 2011–18 and using different measures of digitalization that reflect its destructive and transformative impacts on occupations, we provide evidence that digitalization is significantly associated with entrepreneurial entry at the individual level. The results suggest that high-skilled employees and employees in ICT occupations facing destructive digitalization have an increased likelihood of becoming entrepreneurs with unincorporated businesses. However, entrepreneurship does not seem to be a viable option for low-skilled individuals affected by destructive digitalization. We further find that starting an incorporated business is more likely and starting an unincorporated business is less likely for employees facing transformative digitalization. Apparently, advances in AI create opportunities for growth-oriented entrepreneurship, but also increase the opportunity cost of less ambitious entrepreneurship.

Gender differences in time use have been documented in the literature, but knowledge about the nature of such gender gaps remains limited. This study aims to examine whether changes in temperature, affect gender differentials in time allocation and the potential mechanisms through which the responses might operate. Based on the time use survey data, we find that, relative to men, women decrease their labour supply by approximately one hour during days with extremely high temperatures, despite having fewer working hours than men over the entire distribution of temperature. However, gender differentials in the time allocated to housework and leisure change little with temperature. Our further investigation indicates a substantial part of the gender gap can be explained by gender disparity in family responsibilities due to marriage and parenthood. The gender gap in supply to the market work is more pronounced for those with young children.

Dual-earner couples’ decisions of where to live and work often result in one spouse – the trailing spouse – experiencing earnings losses at the time of a move. This paper examines how married couples’ migration decisions differentially impact men’s and women’s earnings and the role that policy can play in improving post-move outcomes for trailing spouses. I use panel data from the NLSY97 and a generalized differencein-differences design to show that access to unemployment insurance (UI) for trailing spouses increases long-distance migration rates by 1.9–2.3 percentage points (38–46%) for married couples. I find that women are the primary beneficiaries of this policy, with higher UI uptake following a move and higher annual earnings of $4,500–$12,000 three years post-move. I then build and estimate a structural model of dual-earner couples’ migration decisions to evaluate the effects of a series of counterfactual policies. I show that increasing the likelihood of joint distant offers substantively increases migration rates, increases women’s post-move employment rates, and improves both men and women’s earnings growth at the time of a move. However, unconditional subsidies for migration that are not linked to having an offer in hand at the time of the move reduce post-move earnings for both men and women, with stronger effects for women.

Children require a large amount of time, effort, and resources to raise. Physical help, financial contributions, medical care, and other types of assistance from kin and social network members allow couples to space births closer together while maintaining or increasing child survival. We examine the impact of kin availability on couples’ reproductive success in the early twentieth-century United States with a panel data set of over 3.1 million couples linked between the 1900 and 1910 U.S. censuses. Our results indicate that kin proximity outside the household was positively associated with fertility, child survival, and net reproduction, and suggest that declining kin availability was an important contributing factor to the fertility transition in the United States. We also find important differences between maternal and paternal kin inside the household—including higher fertility among women residing with their mother-in-law than among those residing with their mother—that support hypotheses related to the contrasting motivations and concerns of parents and parents-in-law.

A growing body of research is demonstrating a robust positive relationship between the diversity of a city's foreign-born population in the USA and worker productivity. Other research has focused on diversity within firms, similarly finding positive effects in many cases. Although it appears that diverse teams within firms are better at problem-solving and are more creative, the exact mechanism(s) that drive the relationship between diversity and productivity at the scale of city-regions are less apparent and underexplored in extant research. Drawing on research from several fields, I describe four mechanisms that might drive the relationship between immigrant diversity and productivity at the urban level. I explore each mechanism with a pseudo panel of workers and fixed effects OLS regressions across U.S. Metropolitan Statistical Areas between 2011 and 2017. The results most strongly support that at the urban level, diversity enhances productivity through what I call 'exposure effects' and 'interactive problem-solving', wherein workers become more productive and more creative through exposure to new cultures and ways of thinking and through joint problem-solving. These results suggest that positive externalities arise when coupling rising immigrant diversity with the social integration of people from diverse backgrounds.

This article will explore a question about when the tensions of difference inherent in Latinx heterogeneity are part of the ambiguous and contingent process of political community formation and when they instead disrupt the potential power of a newly forming political community. It brings an anthropological perspective to a political question as it examines the intersection of Latinx racial identifications and class relations with both place-of-origin and place-making in Orlando, Florida. In contrast to Cuban Miami, in Orlando Puerto Ricans make up the overwhelming majority of Latinxs. Using the example of the 2011 redistricting process in Orange County, where Orlando is located, the article unpacks the language and technologies of redistricting and finds evidence of how relations marked by dominance and subordination can be reproduced in a combination of the conscious deployment of power by those who have it and the unconscious inability of others to see the mechanisms of injustice at work.

I use the military march of Union general William Sherman during the American Civil War to estimate the effects of wartime violence and destruction on post-war voting behavior and personal identity. First, I examine how the march influenced the support for the Democrats throughout the 19th and 20th centuries. Second, to proxy for the strength of Southern identity, I construct several variables from both historical and contemporary sources. These variables include the share of individuals likely named after famous Confederate generals, the relative frequency of streets likely named after Confederate figures, and the presence of Confederate monuments. The results show mostly small and statistically insignificant effects of the march on Democratic vote share. For some outcomes proxying for Southern identity, I find a significant positive effect; however, these results are not robust across different model specifications. Overall, the results suggest that Sherman’s march did not have a transformative impact on the politics and personal identity in the US South.