This article, based on 84 in-depth interviews and 10 months of ethnography, focuses on the rural Washington community of “Paradise Valley,” whose economic bases in mining, ranching, and logging declined by the end of the twentieth century. Recently, economic development has focused on amenity-based tourism and second-home ownership, as well as attracting wealthy in-migrants. Job growth has been concentrated in construction and service sectors, particularly low-paid, part-time, and seasonal jobs in hospitality, retail, and food services. The community has changed from a relatively homogenous population of working-class residents to a more diverse and divided community. The article explores outcomes of these changes, including gentrification and housing shortages, unemployment and underemployment, and a social divide in which the community's longtime and working-class residents are marginalized. I explore these social consequences of amenity-based development, illustrating the ways in which the social divide is reproduced and the gradual disenfranchisement of those with roots in earlier social and economic systems in the valley, focusing on the changing meanings and uses of different types of symbolic capital.

Studies show lighter skinned Black people are advantaged on a number of social indicators—a phenomenon called “colorism.” These studies generally contend preferences for light-skinned and/or Mulatto slaves endured the postbellum period to shape social outcomes into today. Following this idea, other studies examine differences in social outcomes between Mulattos and Blacks in the 19th century, but few empirically connect antebellum life to postbellum Mulatto–Black stratification. With that in mind, I examine whether the socio-economic differences between Mulattos and Blacks varied across geographic space in proportion to places’ reliance on slave labor and the characteristics of its free African American population. This allows me to examine whether differences in economic status between Mulattos and Blacks are a result of Mulatto advantage in the form of privileged positions during slavery. My results reveal that Mulattos have higher occupational statuses relative to Blacks in places where slavery was more prominent and where free Mulattos were literate. This suggests the intraracial hierarchy established during slavery was more likely to be replicated in places where slavery was more important, and Mulattos were able to capitalize on freedom by leveraging their literacy into better economic statuses after emancipation. These results support the idea that skin color stratification was initiated at least in part by practices during chattel slavery and offers some plausible mechanisms for its transmission.

This article estimates the potential economic benefits of STEM immigration and examines the impact of highly skilled STEM immigration on the wage structure in the United States. Considering that foreign-born share of STEM workers has been increasing rapidly in recent years, there are new interests in examining the extent to which labor market outcomes of natives-and immigrants alike-are affected by this supply inflow. The analysis yields a few main findings. First, U.S. and foreign-born STEM workers with similar skills have a high but finite elasticity of substitution (∼18), implying that the adverse impact of STEM immigration would be more concentrated among immigrant STEM workers themselves. Second, 2000-2015 foreign STEM labor supply shock increases the average wage of preexisting U.S.-born STEM workers by 4.67 percent. This finding, however, masks a distributional consequence of the shock as native STEM workers with higher educational attainment experience lower wage gains. Third, the economic benefit for native workers from 2000-2015 foreign STEM supply shock is approximately 103 billion USD or 1.03% of U.S. GDP in 1999. Almost all of this benefit comes from the productivity spillovers associated with high-skilled STEM immigration that increase the productivity and wages of U.S.-born workers. Finally, the average wage of U.S.-born STEM workers would have been approximately 1 percentage point higher in the absence of the H-1B Visa Reform Act of 2004. JEL Classification: J31, J61, J68

"Latinos" are the largest group among Americans of color. At 59 million, they constitute nearly a fifth of the US population. Their number has alarmed many in government, other mainstream institutions, and the nativist right who fear the white-majority US they have known is disappearing. During the 2016 US election and after, Donald Trump has played on these fears, embracing xenophobic messages vilifying many Latin American immigrants as rapists, drug smugglers, or "gang bangers." Many share such nativist desires to build enhanced border walls and create immigration restrictions to keep Latinos of various backgrounds out. Many whites’ racist framing has also cast native-born Latinos, their language, and culture in an unfavorable light. Trump and his followers’ attacks provide a peek at the complex phenomenon of the racialization of US Latinos. This volume explores an array of racialization’s manifestations, including white mob violence, profiling by law enforcement, political disenfranchisement, whitewashed reinterpretations of Latino history and culture, and depictions of "good Latinos" as racially subservient. But subservience has never marked the Latino community, and this book includes pointed discussions of Latino resistance to racism. Additionally, the book’s scope goes beyond the United States, revealing how Latinos are racialized in yet other societies.

Type 2 diabetes is at epidemic levels in the U.S., with 30.3 million Americans affected and 1-in-3 projected to become diabetic by 2050 (1,2,3). Prediabetes is a modifiable risk factor this disease, but despite its higher prevalence and significance as a diabetes risk factor (4,5), relatively little is known about this condition. This study evaluated the condition’s risk factors; the presence of age, period, and cohort effects on historical prediabetes prevalence; and produced special prediabetes projections in an effort to further knowledge about prediabetes and inform diabetes intervention strategies. Key findings: 1) identified educational attainment and household income as risk factors of prediabetes prevalence; 2) supported age, period, and cohort effects in prediabetes prevalence from 1976-1980 through 2013-2014; and 3) projected increasing prediabetes prevalence through 2060. Together, these findings underscored the importance of access to health-promotive resources and environmental conditions for health maintenance and disease avoidance. Vulnerable populations, such as older adults and race/ethnic minorities, historically have less access to these resources and bear a disproportionate burden of poor health outcomes (6,7,8). These groups drive projected prediabetes burden (and diabetes burden) through 2060, suggesting a major future burden on the national healthcare system to the individuals, families, and communities making up these vulnerable groups...

The Alaska Permanent Fund Dividend (PFD) program provides universal basic income (UBI) to all resi- dents from investment earnings of a state sovereign wealth fund created from oil rents. This paper eval- uates the effect of the PFD to mitigate poverty among the state’s rural Indigenous (Alaska Native) peoples: a population with historically high poverty rates living in a region with limited economic oppor- tunities. Errors in recording PFD income in data used to calculate official poverty statistics cause them to misrepresent poverty in Alaska and understate the effect of the PFD. Estimating poverty rates with and without PFD income therefore requires reconstruction of family incomes from household-level data. Estimated poverty rates from reconstructed income show that the PFD has had a substantial, although diminishing mitigating effect on poverty for rural Indigenous families. The PFD has had a larger effect on poverty among children and elders than for the rural Alaska Native population as a whole. Alaska Native seniors, who receive additional sources of UBI derived primarily from resource rents besides the PFD, have seen a decline in poverty rates, while poverty rates for children have increased. Evidence has not appeared for commonly hypothesized potential adverse social and economic conse- quences of UBI.

Brick and mortar retailers provided $376 billion of “free” consumer shopping experiences in 2015. For example, vehicle dealerships provide “free” test drives and department stores provide “free” fashion advice. In addition, brick and mortar services like banks also provide valuable “free” experiences as well. The recent shift to e-commerce raises fears that these “free” experiences may be disappearing. To capture the output of “free” experiences, I model their provision as a barter transaction of sales attention for experiences, and track this modeled transaction consistently with the industry outputs and inputs already tracked in GDP. Despite the rise of e-commerce, I find that brick and mortar shopping experiences grew faster than overall GDP after 2002. It may be true that Americans are spending less time at brick and mortar retailers – but retailers more than compensate by increasing the quantity of “free” experiences provided per hour. Consistent with the increased shopping output reported by retailers, shoppers self-reported lower stress levels during brick and mortar shopping. I argue that these changes are driven by competition from e-commerce, so the improvement in brick and mortar shopping experiences can be viewed as an indirect productivity effect from the Internet. Focusing on the wholesale and retail sector, the post-2002 productivity slowdown shrinks from 0.98 percentage points per year to only 0.13 percentage points per year. Across the entire private business sector, the post-2002 productivity slowdown shrinks from 0.44 percentage points per year to 0.26 percentage points per year.

This study presents empirical evidence that a health improvement program-municipal privatization of water services-in Argentina during the 1990s has a negative effect on later life human capital accumulation. Exploiting variation across regions and across cohorts, I find that early childhood exposure to the program reduces probability of secondary school completion by 3.5 percentage points and years of schooling by 0.4 years. The negative effect is more pronounced for males. I further use the previous census to look at the same cohorts when they were at their school ages, the results show that both girls and boys are more likely to drop out of school, and I find suggestive evidence that boys are more likely to go to work after the program. The finding is consistent with families require healthier children to go to work after improvements in health status.

Integrated PUMS (IPUMS) is made available through a web interface (www.ipums.org). The website includes IPUMS microdata for the U.S. Decennial Censuses (1850–2010); ACS (2000–2016); samples from Puerto Rico (1910–2016); and complete count datasets for 1790– 1840 households and 1850, 1880, 1910–1940 individuals and households. Still to be added are data from 1860, 1870, and 1900. The ACS microdata samples include: the 1-year 1% samples since 2005 (although 2000–2004 are smaller and limited to 1-year samples) and the . . .

Access to adequate antenatal care (at least four antenatal visits, beginning in first four months of pregnancy) in Zambia in 2013 varied according to population density. We expect greater access to antenatal care in urban areas than in rural areas; surprisingly, women in dense urban areas (urban slums) were least likely to receive adequate antenatal care. Data come from the IPUMS-DHS database, with information on the frequency and timing of antenatal visits collected in Demographic and Health Surveys. We classified women according to the population density of the area where they lived, using a contextual variable on population density added to IPUMS-DHS (based on CIESIN’s 2016 Documentation for the Gridded Population of the World) and GPS data on subjects’ location.

This dissertation demonstrates the importance of industry of employment for patterns of occupational segregation by race and ethnicity in the United States using multiple analytical methods. Two quantitative approaches are employed: the descriptive approach of segregation indexes using the additive decomposability property of the entropy-based indexes, and the statistical approach of econometric modeling using multilevel models. These methods are shown to have advantages for evaluating and contextualizing segregation at multiple scales simultaneously which advance the state of knowledge regarding intra-industry occupational segregation and its consequences for overall occupational segregation in the labor market. The application of these methods contributes to both the descriptive and the econometric literature and provides new evidence for variations in the severity of occupational segregation across industries and the relationship between occupational segregation and earnings inequality. The findings include new measures of intra-industry occupational segregation and the share of this segregation that is unexplained by worker and job attributes, a ranking of industries by the extent of segregation experienced by race and ethnicity groups, substantiation of the stratified dimensions of occupational segregation including racial and ethnic class differences based on earnings or occupational prestige, and an examination of the role of industry-specific factors that contribute to the occurrence of occupational segregation in the retail industry.

Research suggests the economy’s demand for college-educated workers exceeds the supply, which might be contributing to slower economic growth. Improving students’ preparation at the K-12 level could both increase the college completion rate and help those who are not college-bound choose the best paths for themselves.

This paper examines the effects of robotization on trade patterns, wages and welfare. It develops a Ricardian model with two-stage production and trade in intermediate and final goods in which robots can take over some tasks previously performed by humans in a subset of industries. An increase in robot adoption in the North reduces the cost of production and thereby impacts trade in final and intermediate goods with the South. The empirical analysis uses ordinary least squares and instrumental variable regressions exploiting variation in exposure to robots across countries and sectors. Both reveal that greater robot intensity in own production leads to: (i) a rise in imports sourced from less developed countries in the same industry; and (ii) an even stronger increase in exports to those countries. Counterfactual simulations indicate that Northern robotization raises domestic welfare, but initially depresses wages. However, this adverse effect is likely to be reversed by further reductions in robot prices. Northern robotization may lead to higher wages and welfare in the South.

This study explores the popularity of individualism among White working-class Americans in light of the structural forces that have negatively impacted their lives in recent years. Findings are based on data from semi-structured interviews with 20 non-Hispanic White custodial workers from five Appalachian universities across three U.S. states: Pennsylvania, Virginia, and West Virginia. Participants were asked a variety of questions about the causes of poverty and economic inequality in the U.S. in general, as well as the causes of their own personal fortunes. Data were analyzed utilizing grounded theory methods. Participants were found to be highly individualistic both in explaining poverty and economic inequality in the U.S. in general, as well as in explaining their own lives. Our results suggest that individualism remains popular among White working-class Americans. We argue that growing inequality is experienced as “double violence” by working-class Whites, both as structural violence and symbolic violence. We discuss the challenges this poses for tackling persistent poverty and growing economic inequality in contemporary American society.

We used spatial analyses to examine exposure of people in vulnerable occupational groups to neighborhood-level environmental pollutants in the Bronx borough of New York City. Five-year estimates of environmental ambient exposures (derived from land use regression models for PM2.5 [particulate matter with an aerodynamic diameter ≤ 2.5 μm] and black carbon) and demographic and occupational variables were harmonized at the census tract level. Correlations revealed that areas with high environmental exposures also had high proportions of people in service industries and manufacturing and high proportions of socioeconomically vulnerable populations. This combination of vulnerabilities may be cumulative, suggesting residents could have high occupational and residential exposures in addition to sociodemographic-related inequity.

One feature of the changing nature of work is an increase in gig and independent work. Gig and independent work includes a variety of full-time and part-time activities for earning income outside of an employer-employee relationship. In the US, most of this work occurs within service industries. This paper describes the attributes of gig and independent work in a set of US metropolitan economies and in the US as a whole, with an emphasis on determining its role within select service industries. The objective is to provide a more thorough understanding of this aspect of the changing nature of work to inform economic and policy discussions.

This comment is in response to Ifatunji's (2017) article, “Labor Market Disparities Between African Americans and Afro Caribbeans: Reexamining the Role of Immigrant Selectivity,” published in this journal.

When social scientists examine relationships between income and voting decisions, their measures implicitly compare people to others in the national economic distribution. Yet an absolute income level (e.g., $57,617 per year, the 2016 national median) does not have the same meaning in Clay County, Georgia, where the median income is $22,100, as it does in Old Greenwich, Connecticut, where the median income is $224,000. We address this limitation by incorporating a measure of one’s place in her zip code’s income distribution. We apply this approach to the question of the relationship between income and whites’ voting decisions in the 2016 presidential election. The results show that Trump’s support was concentrated among nationally poor whites but also among locally affluent whites, complicating claims about the role of class in the election. This pattern suggests that social scientists would do well to conceive of income in relative terms: relative to one’s neighbors.

Lawmakers in Iowa must pave the way to economic security for women and families by ensuring that state policies guarantee economic equality and reproductive health care access for all women. Policymakers should prioritize policies that allow families to receive higher, livable wages; promote equal pay for equal work; and help parents maintain good jobs that allow them to work and raise their children. Women need policies that reflect their roles as providers and caregivers. In Iowa, mothers are the sole, primary, or co-breadwinners in 68.1 percent of families, and these numbers are higher for some women of color. 1 The following policy recommendations can help support the economic security of women and families in Iowa. Promote equal pay for equal work Although federal law prohibits unequal pay for equal work, there is more that can be done to ensure that both women and men across Iowa enjoy the fullest protections against discrimination. • Iowa women who are full-time, year-round workers earned about 79 cents for every dollar that Iowa men earned in 2017; 2 if the wage gap continues to close at its current rate, women will not reach parity in the state until 2062. 3 The wage gap is even larger for black women and Latinas in Iowa, who earned 59.4 cents and 57.7 cents, respectively, for every dollar that white men earned in 2016. 4 • Due to the gender wage gap, each woman in Iowa will lose an average of $463,760 over the course of her lifetime. 5

In the process of management of traditional marine collective engineering management system, as the huge volume of data in marine collective engineering, it is impossible to achieve hierarchical data management. To address this problem, marine collective engineering management system with BS architecture based on big data is designed in this paper. The BS architecture of big data is used to optimize the general framework of the collective engineering management system. The system is divided into layers, the core functions and subsystems are differentiated, and the hierarchical functions of the system modules are optimized. The hardware design of the management system is realized. Logical calculation is used for qualitative analysis of engineering management data. The management order is identified through attribute identification to realize the software design of engineering management system. The experimental results show that the designed engineering management system can be applied to the marine collective engineering with big data, and the management efficiency is 34.5% higher than the traditional engineering management system.