As the 2020 presidential election in the United States approaches, Indian Americans are unexpectedly in the spotlight thanks to their growing affluence and influence in political circles and Democratic candidate Joe Biden’s selection of Kamala Harris (who is of partial Indian origin) as his running mate. But significant attention is also being paid to Indian Americans because a narrative is emerging that the apparent courtship between U.S. President Donald Trump and Indian Prime Minister Narendra Modi, compounded by concerns over how a Biden administration might manage U.S.-India ties, will push Indian Americans to abandon the Democratic Party in droves. This study finds no empirical evidence to support either of these claims. The analysis is based on a nationally representative online survey of 936 Indian American citizens—the Indian American Attitudes Survey (IAAS)—conducted between September 1 and September 20, 2020, in partnership with the research and analytics firm YouGov. The survey has an overall margin of error of +/- 3.2 percent. The data show that Indian Americans continue to be strongly attached to the Democratic Party, with little indication of a shift toward the Republican Party. In addition, Indian Americans view U.S.-India relations as a low priority issue in this electoral cycle, emphasizing instead nationally salient issues such as healthcare and the economy. As the political behavior of Indian Americans in the United States gains influence, this study provides an empirically robust and analytically nuanced picture of the diversity in attitudes of this important demographic. Between 2000 and 2018, the Indian American population grew by nearly 150 percent, making it the second-largest immigrant group in America today. The community’s elevated levels of educational attainment and household income render its members valuable campaign contributors and potential mobilizers. And in select swing states, the Indian American population is larger than the margin of victory that separated Hillary Clinton and Trump in the closely contested 2016 presidential race. Yet, despite the rising political profile of Indian Americans, their political attitudes are woefully under-studied. The objective of this study is to harness new empirical data that can help characterize the political attitudes and preferences of Indian Americans. The findings in this study, the first in a series on the political attitudes of Indian Americans, are briefly summarized below: • Indian Americans remain solidly with the Democratic Party. Recent anecdotal narratives notwithstanding, there is scant evidence that Democratic voters are defecting toward Trump and the Republican Party. Seventy-two percent of registered Indian American voters plan to vote for Biden and 22 percent intend to vote for Trump in the 2020 November election. • Indian Americans do not consider U.S.-India relations to be one of the principal determinants of their vote choice in this election. The economy and healthcare are the two most important issues influencing the vote choice of Indian Americans, although supporters of the two parties differ on key priorities. “Kitchen table” issues dominate over foreign policy concerns. • Indian Americans exhibit signs of significant political polarization. Just like the wider voting public, Republican and Democratic Indian American voters are politically polarized and hold markedly negative views of the opposing party and divergent positions on several contentious policy issues—from immigration to law enforcement. • U.S.-born Indian American citizens tilt left compared to foreign-born citizens. While both U.S.-born and naturalized Indian Americans favor the Democratic Party, this tilt is more pronounced for U.S.-born Indian Americans. Political participation by naturalized citizens is more muted, however, manifesting in lower rates of voter turnout and weaker partisan identification. • Harris has mobilized Indian Americans, especially Democrats. Harris’s vice presidential candidacy has galvanized a large section of the Indian American community to turn out to vote. On balance, while the Harris pick might not change large numbers of votes (given the community’s historic Democratic orientation), her candidacy is linked to greater enthusiasm for the Democratic ticket. • A large section of Indian Americans view the Republican Party as unwelcoming. Indian Americans refrain from identifying with the Republican Party due, in part, to a perception that the party is intolerant of minorities and overly influenced by Christian evangelicalism. Those who identify as Republicans are primarily moved to do so because of economic policy differences with the Democrats—with particularly marked differences regarding healthcare. • Political beliefs seep into perceptions of U.S.-India bilateral relations. Indian Americans believe Democrats do a better job of managing U.S.-India ties by a considerable margin while Republicans hold more favorable views of Modi. How Will Indian Americans Vote? Results From the 2020 Indian American Attitudes Survey.

Immigrants immigrate to the United States for a number of social, economic and/or political reasons. The last decade bore witness to economic motivations, namely labor market earnings potential, as the primary driving force and motivation for immigration. However, foreign born persons have historically earned less labor market earnings than their native born counterparts in the United States. This is not a new phenomenon by any means. The gap could simply be a result of an immigrant’s non-transferable skills to the United States labor markets. However, the diversity in the explanation of the literature implies a different story. Scholars argue that it takes 15 years for immigrants to close the gap. Other scholars argue that the gap will never be closed. While there is no clear understanding of why immigrants, both first and second generation, make less labor market earnings than their native born counterparts, even at every education attainment level. Past scholars have often cited only one variable, such as education attainment, or language proficiency, or time in country, as the singular cause of the gap. This dissertation introduces a matrix of variables: education attainment, language fluency, and time in country to suggest an alternative methodological approach. It also controls for demographic characteristics like age, marital status, race, citizenship, and first or second generation status. Previous literature lacks any holistic approach or considers micro-level factors to understanding the complexity of the gap. Using survey level data collected annually, this dissertation explores labor market earnings gap for first and second generation immigrants compared to their native born counterparts. Ultimately, this dissertation concludes that the labor market earnings gap will never close, regardless of education attained, language fluency, time in country or citizenship. This study sides with the existing scholarship that concludes that an immigrant’s labor market earnings gap exists when compared to that of the native born population.

Objective Few population-based studies have examined the health care experiences of children with sexual minority parents. The purpose of this study was to compare health insurance status, access to care, and health services utilization for children by mother’s sexual orientation. Methods We used data on children with lesbian mothers (n=195), bisexual mothers (n=299), and heterosexual mothers (n=23,772) in the 2013–2017 National Health Interview Survey. Logistic regression models were used to compare health insurance status, access to care, and health services utilization while adjusting for demographic and socioeconomic characteristics of the child, mother, and household. Results After controlling for sociodemographic factors, there were no statistically signifcant diferences in health insurance coverage, access to care, or health services utilization between children of lesbian mothers and children of heterosexual mothers. Compared to children with heterosexual mothers, children with bisexual mothers were more likely to have public health insurance (OR 2.33; 95% CI 1.07–7.68), delayed medical care due to cost (OR 2.33; 95% CI 1.12–4.86), unmet medical care due to cost (OR 2.86; 95% CI 1.07–7.68), and a visit to the emergency room (OR 1.74; 95% CI 1.27–2.39) in the prior year after controlling for child-level characteristics. Some of these diferences were attenuated after controlling for maternal demographics and household characteristics. Conclusions for Practice Children with bisexual mothers experience barriers to routine medical care. Addressing socioeconomic dimensions of health care access and targeted outreach to bisexual parents will help promote health equity for children growing up in sexual minority households.

New large-scale linked data are revolutionizing quantitative history and demography. This paper proposes two complementary strategies for improving inference with linked historical data: the use of validation variables to identify higher quality links and a simple, regression-based weighting procedure to increase the representativeness of custom research samples. We demonstrate the potential value of these strategies using the 1850–1930 Integrated Public Use Microdata Series Linked Representative Samples (IPUMS-LRS)—a high quality, publicly available linked historical dataset. We show that, while incorrect linking rates appear low in the IPUMS-LRS, researchers can reduce error rates further using validation variables. We also show how researchers can reweight linked samples to balance observed characteristics in the linked sample with those in a reference population using a simple regression-based procedure.

The extent to which cultural beliefs about gender shape occupation-level wages remains a central yet unresolved question in the study of gender inequality. Human capital theorists predict that gendered beliefs have no direct effect on occupation-level wages. Devaluation theorists argue that occupations associated with women and femininity are systematically devalued and thus underpaid. We test these explanations using data from the American Community Survey, the Occupational Information Network, and an affect control theory (ACT) data set of affective meanings. We use the ACT data set to operationalize occupational gendered cultural sentiments along two distinct dimensions: evaluation (goodness, caring, warmth) and potency (power, strength, competence). Hierarchical linear models show that potency but not evaluation affects occupational income net of individual and occupational controls. Path analyses show that potency has a direct effect net of occupational traits. The gender composition of an occupation indirectly affects occupational income through potency. The cultural meanings of potency/competence associated with masculinity, rather than the devaluation of feminine nurturant occupations, is the primary cultural mechanism linking gender composition and occupational reward.

Environmental justice scholarship argues state power perpetrates environmental inequalities, but less is known about the U.S. Military’s impact on local urban environmental inequalities. To evaluate the role of the military in contributing to environmental health disparities, I draw on the case study of Las Vegas, Nevada, a southwestern city with active military sites. The analysis uses environmental health, demographic, and Geographic Information System (GIS) data from federal and county agencies. Findings from spatial error models support environmental inequality and treadmill of destruction hypotheses by demonstrating that census tracts in closer proximity to military areas have greater estimated cancer risk from air toxics. Census tracts with a higher percent of poor and Latinx residents, independent of their proximity to military areas, have an additional increase in exposure to air pollution. The case study of Las Vegas offers important lessons of environmental injustice on Latinx environmental health vulnerability and military sites in urban areas.

Domestic work, once the most common occupation for women around the globe, was thought to be well on its way to extinction at the end of the twentieth century. However, in the 1980s and 1990s, evidence began to appear that domestic work was in many places again becoming a growth occupation. My goal in this article is to examine the factors related to the recent expansion of domestic work in countries in the Global North, using the United States as a case study. I draw on U.S. Census data to document the resurgence of domestic work both nationally and in many large cities across the country, and then use multivariate analysis to compare rates of domestic work across these cities. The results indicate that rates of domestic work are highly related to variables measuring structural inequalities (racialization of the labor force, immigration, and economic polarization), while showing little relationship with variables measuring unmet care needs (care dependency ratios, female/maternal labor force participation, and availability of institutional care options). These findings underline the urgency of providing protections to domestic workers and point to the need for scholarship that better theorizes the relationships among unpaid care and different forms of paid care.

The COVID-19 pandemic has thrown labor markets into a tailspin. The overall U.S. unemployment rate reached an all-time recorded high of 14.7 percent in April 2020, and weekly claims for unemployment insurance peaked at 6.2 million—nearly six times higher than any pre-pandemic level since data were first recorded.1 Prior to the onset of this coronavirus-generated recession, the narrative around the American economy would suggest that workers were enjoying some of the lowest unemployment rates of all times. But this aggregation hid a bleak reality of inequality in the United States: Labor market conditions for Latino workers consistently lag behind those of their non-Hispanic white counterparts. This trend, which has held since 1976 when the U.S. Bureau of Labor Statistics (BLS) first started tracking employment data by ethnicity, reveals that the Latino unemployment rate has generally remained between 1.6 and 1.9 times higher than the non-Hispanic white unemployment rate, and it has never dropped below a ratio of 1.2.2

Growing economic disparities across the U.S. have increased the need for effective place-based jobs policies. This paper seeks to uncover determinants of effective policies by analyzing the job impacts of thousands of spatially targeted investments made by local governments to spur economic development in low-income areas, funded by $3-4 billion in annual federal block grants from the Community Development Block Grant. Using a hybrid approach combining synthetic control methods with traditional differences-indifferences , I find that jobs increase by 13% over ten years in census tracts where large CDBG investments occurred, without a corresponding increase in home prices. The increase in jobs is driven by low-income workers living in close proximity. The most effective place-based investments provided direct financial assistance to businesses or subsidized commercial/industrial construction. While the CDBG can only be deployed in lower-income neighborhoods, investments had greater job impacts in comparatively less-disadvantaged tracts. I verify that block grants do not crowd out public spending and estimate that each dollar of block grant generates approximately three dollars of public spending.

This book provides modern technical answers to the legal requirements of pseudonymisation as recommended by privacy legislation. It covers topics such as modern regulatory frameworks for sharing and linking sensitive information, concepts and algorithms for privacy-preserving record linkage and their computational aspects, practical considerations such as dealing with dirty and missing data, as well as privacy, risk, and performance assessment measures. Existing techniques for privacy-preserving record linkage are evaluated empirically and real-world application examples that scale to population sizes are described. The book also includes pointers to freely available software tools, benchmark data sets, and tools to generate synthetic data that can be used to test and evaluate linkage techniques. This book consists of fourteen chapters grouped into four parts, and two appendices. The first part introduces the reader to the topic of linking sensitive data, the second part covers methods and techniques to link such data, the third part discusses aspects of practical importance, and the fourth part provides an outlook of future challenges and open research problems relevant to linking sensitive databases. The appendices provide pointers and describe freely available, open-source software systems that allow the linkage of sensitive data, and provide further details about the evaluations presented. A companion Web site at https://dmm.anu.edu.au/lsdbook2020 provides additional material and Python programs used in the book. This book is mainly written for applied scientists, researchers, and advanced practitioners in governments, industry, and universities who are concerned with developing, implementing, and deploying systems and tools to share sensitive information in administrative, commercial, or medical databases.

Do undocumented migrants underreport crimes to the police in order to avoid being deported? And do criminals exploit such vulnerability? We address these questions using victimization surveys and administrative data around the 1986 U.S. immigration amnesty. The amnesty allows us to solve two major identification issues that have plagued this literature: migrants’ legal status is endogenous and unobserved. The results show that the reporting rate of undocumented immigrants is 17 percent, which limits the immigrants’ ability to protect some of their fundamental human rights. However, right after the 1986 amnesty, which disproportionately legalized individuals of Hispanic origin, crime victims of Hispanic origin show enormous improvements in reporting behavior. The implied increase in the reporting rate by amnesty applicants is close to 20 percentage points.

Construction employment by demographic and work-related characteristics was estimated using data from the Current Population Survey (CPS). Employment numbers among construction subsectors were obtained from the Current Employment Statistics (CES). Both CPS and CES are conducted by the U.S. Bureau of Labor Statistics (BLS). The effects of COVID-19 on construction businesses were assessed using the U.S. Census Bureau’s new weekly Small Business Pulse Survey (SBPS), which measures the changes in business conditions during the pandemic. The trends of monthly employment and weekly business performance were traced and compared between construction and all industries on average. Differences between construction subgroups were analyzed to identify which groups were hit harder. Definitions for italicized terms are included as the reader’s references.

This paper provides insights into the gains of forming a couple by estimating how much of the difference in housework between single and married individuals is causal and how much is due to selection. Permanent unobserved heterogeneity explains about half of the observed differences in housework documented in the cross-sectional data. Further ancillary evidence suggests that individuals with a higher preference for marriage also have more traditional views on the division of household labour. There remains a genuine half-an-hour increase per week in housework time for each partner, with women specializing in routine and men in non-routine housework tasks.

Information on the available supply of workers in a local job market is important when determining whether there are qualified workers to fill health care jobs in demand. The American Community Survey (ACS), a publicly available annual survey of over 3.5 million households conducted by the U.S. Census Bureau, has been a regular source of information for mapping the geographic distribution of a wide range of occupations, describing the time, duration and distance of workers’ commutes, and identifying common forms of transportation for commuting. In this study, we explore what the ACS can tell us about commuting patterns among selected allied health occupations and registered nurses (RNs) as well as how these patterns may inform discussions of health workforce supply

A sanctuary policy is a policy that inhibits local law enforcement from cooperating with immigration authorities. Sanctuary policies have gained more attention in recent U.S. policy debates. Opponents claim that sanctuary policies attract criminals and lower the cost of crime through weakter sanctions and lower apprehension probability. Supporters counter that these policies produce a spiral of trust that supports police and reasies informal social control over crime. Using city crime data from 1999 to 2010, I estimate the effect of sanctuary policies on crime. Using a difference-in-differences approach, this paper finds no evidence that sanctuary policies cause an increase in crime and some evidence that they may lead to a decrease in property crime.

As with many other aspects of life—including the record-setting decline in employment—the COVID-19 pandemic has profoundly affected the living arrangements of millions of Americans. In this note, we document a fact that has as yet received little attention: The aggregate headship rate in the US has fallen dramatically since February, in large part because people have moved back in with older family members. Similar to many other consequences of the pandemic, these changes have been particularly stark among young adults, Black adults, and those without a college education.

South Los Angeles embodies a complex history that captures the dynamics of spatial inequality. It is an area where some of the largest protests reacting to a system of racial oppression have imprinted a persistent image on the names South Central and Watts. This article analyzes how the stigma attached to the South Los Angeles area has translated to place specific forms of inequality. We take advantage of the consistency in the boundaries the Census used to collect data in the area from 1960 to 2016 to test hypotheses about the relative importance of race, place, and economic class in the Los Angeles region. The analysis revolves around three themes critical to furthering equality: housing, employment, and transportation. We find that the significance of place has changed significantly over the course of half a century without ever disappearing. In each of the themes we study, the significance of the factors we highlight changes, but South Los Angeles remains disadvantaged relative to the region.

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.

Purpose: The aim of this study was to evaluate racial/ethnic disparities in follow-up adherence for incidental pulmonary nodules (IPNs) using a cascade-of-care framework, representing the multistage pathway from IPN diagnosis to timely follow-up adherence. Methods: A cohort of 1,562 patients diagnosed with IPNs requiring follow-up in a tertiary health care system in 2016 were retrospectively identified. Racial/ethnic disparities in follow-up adherence were examined by developing a multistep cascade-of-care model (provider communication, follow-up examination ordering and scheduling, adherence) to identify where patients were most likely to fall off the path toward adherence. Racial/ethnic adherence disparities were measured using descriptive statistics and multivariate modeling, controlling for sociodemographic, communication, and health characteristics. Results: Among 1,562 patients whose IPNs required follow-up, unadjusted results showed that nonwhite patients were less likely to meet each step on the cascade than White patients: for provider-patient IPN communication, 55% among Black patients and 80% among White patients; for follow-up ordering and scheduling, 42% and 41% among Black patients and 66% and 64% among White patients; and for timely adherence, 29% among Black patients and 54% among White patients. Adjusting for provider communication, sociodemographic, and health characteristics, Black patients had increased odds of never adhering to and delaying follow-up compared with White patients (odds ratios, 1.30 [95% confidence interval, 0.90-1.89] and 2.51 [95% confidence interval, 1.54-4.09], respectively). Conclusions: These findings demonstrate substantial racial/ethnic disparities in IPN follow-up adherence that persist after adjusting for multiple characteristics. The cascade of care demonstrates where on the adherence pathway patients are at risk for falling off, enabling specific targets for health policy and clinical interventions. Radiologists can play a key role in improving IPN follow-up via increased patient care involvement.

Objectives. To estimate the population lacking at least basic water and sanitation access in the urban United States. Methods. We compared national estimates of water and sanitation access from the World Health Organization/United Nations Children’s Fund Joint Monitoring Program with estimates from the US Department of Housing and Urban Development on homelessness and the American Community Survey on household water and sanitation facilities. Results.We estimated that at least 930 000 persons in US cities lacked sustained access to at least basic sanitation and 610 000 to at least basic water access, as defined by the United Nations. Conclusions. After accounting for those experiencing homelessness and substandard housing, our estimate of people lacking at least basic water equaled current estimates (n = 610 000)—without considering water quality—and greatly exceeded estimates of sanitation access (n = 28 000). Public Health Implications. Methods to estimate water and sanitation access in the United States should include people experiencing homelessness and other low-income groups, and specific policies are needed to reduce disparities in urban sanitation. We recommend similar estimation efforts for other high-income countries currently reported as having near universal sanitation access. (Am J Public Health. 2020;110:1567– 1572. doi:10.2105/AJPH.2020.305833)