Technical change that improves economies of scale can generate fast income growth among top earners at the expense of everyone else. I test this classic “superstar model” in the labor market for entertainers where the historic roll-out of television led to a natural experiment in scale-related technological change. The launch of a local TV station multiplied audiences of top entertainers nearly fourfold and resulted in a 50% increase of the top percentile’s income share, a more right-skewed income distribution, and significant income losses for lowerranked entertainers. The results confirm the predictions of the “superstar model” and are at odds with canonical models of skill-biased technological change.

This paper calculates the welfare cost to families of an unemployment shock. Using U.S. data, we find an average annualized expected dollar equivalent welfare loss of $1,156 when the unemployment rate rises by one-percentage point. Relative to single families, the welfare loss is greater for married families and increases with education. We also estimate that a loss in purchasing power of 1.8% generates the same amount of welfare loss as a one percentage point rise in the unemployment rate. Additionally, the magnitude of the shock to purchasing power that a family is willing to endure to avoid a one percentage point increases in the aggregate unemployment rate rises with income. The results in this paper informs policy makers about the distributional implications of decisions likely to affect labor markets.

Dramatic changes in the population composition, realities of work, and family structure over the past 50 years have had a profound impact on the rural United States. In this chapter, I compare rural counties in 1960 to those in more recent years. I find amid the backdrop of aging and diversifying populations, shifts toward a service-based economy coupled with a rise in both adults living alone and single-parent families. Patterns largely mirror those in the urban U.S. but are sometimes more pronounced. Taken together, these changes have profound implications for how families can make ends meet: families work more hours at less-stable jobs, often with less-dense networks of family and friends for support. As a result, these changes necessitate rethinking some of the key assumptions of social safety net programs—such as work requirements—if they are to help low-income and poor rural families move up the income ladder.

Objective In Nigeria, unmet need for contraception is high despite improved access to modern contraception. To identify factors that support Nigerian women’s contraceptive decisions to achieve their reproductive goals, in the presence or absence of their partner’s support, we seek to identify individual/couple and community level determinants of a spectrum of contraceptive practices, from non-use to covert and overt use of contraception. Methods Data were drawn from a national probability survey conducted by Performance Monitoring and Accountability 2020 in Nigeria in 2017–2018. A sample of 12,948 women 15–49 years was included, 6433 of whom were in need of contraception at the time of the survey. We conducted bivariate and multivariate analysis to identify individual/couple and community level factors associated with covert use relative to non-use and to overt use of contraception. Results Altogether, 58.0% of women in need of contraception were non-users, 4.5% were covert users and 37.5% used contraception overtly. Covert users were more educated and wealthier than non-users, but less educated and less wealthy than overt users. Covert users were less likely to cohabitate with their partner compared to non-users [AOR = 4.60 (95%CI: 3.06–6.93)] and overt users [AOR = 5.01 (95%CI: 3.24–7.76)] and more likely to reside in urban areas. At the community level, covert users were more likely to live in communities with higher contraceptive prevalence and higher levels of female education relative to non-users. They were also more likely to live in communities with higher female employment [AOR = 1.62, (95%CI: 0.96–2.73)] compared to overt users. Conclusion By identifying individual and community level factors associated with the spectrum from non-use to covert use and overt use of contraception, this study highlights the importance of integrating individual and community interventions to support women’s realization of their reproductive goals.

Previous studies often use Hispanic non-citizens as a proxy to identify undocumented immigrants in survey data. This paper compares the ethnicity proxy with the residual method in identifying undocumented immigrants regarding two aspects: how closely they match ofcial statistics and how they difer when evaluating the efects of the state-level DREAM Acts and DACA on college enrollment and labor market outcomes. This study fnds that the residual method outperforms the Hispanic non-citizen proxy in matching the U.S. Citizenship and Immigration Services statistics of undocumented immigrants for a majority of variables. Consistent with the previous literature, results from both methods fnd that the state-level DREAM Acts increase college enrollment, while DACA decreases college enrollment and increases the probability of working. The residual method produces policy efect estimates in the same direction as does the Hispanic non-citizen proxy approach, but larger in magnitude for DACA.

We find that state mandated facility requirements may constrain the size and location of funeral homes. Many states have funeral regulations that require funeral homes to have embalming rooms, chapels, and casket display rooms. Often these facilities go unused, providing no discernible benefit to consumers while imposing unnecessary costs on firms. Using a case study, we present evidence that Arizona's more extensive facility requirements reduce the number of small funeral homes relative to Florida and prevent them from locating in shopping centers. We estimate that eliminating Arizona's cumbersome facility requirements would save consumers approximately 14% on their funeral expenditures. (JEL L51, L84, L88)

President Trump has prioritized the arrest and deportation of illegal immigrants based largely on his argument that they are a significant and disproportionate source of crime in the United States. But is his argument supported by the facts? Illegal immigration and the crimes illegal immigrants commit are notoriously difficult to measure. This policy analysis is the latest paper in a series that attempts to answer that question by estimating illegal immigrant incarceration rates in the United States by using the American Community Survey Public Use Microdata Sample from the U.S. Census. This analysis goes beyond previous studies in the series as it updates our residual estimation method based on new research authored by University of California, Riverside, doctoral candidate Christian Gunadi and published in Oxford Economic Papers. Furthermore, we apply the updated methods to estimate the illegal immigrant incarceration rates in earlier years. Gunadi’s new methods slightly increased the illegal immigrant crime rate relative to that of native-born Americans, but the illegal immigrant crime rate is still much lower than for that of native-born Americans. The states and federal government should collect better incarceration, conviction, and arrest data by immigration status so that we can more accurately understand how immigrants affect crime in the United States. Our estimates show that immigrants are less likely to be incarcerated than native-born Americans relative to their share of the population. Separately, legal immigrants and illegal immigrants each are less likely to be incarcerated than native-born Americans.

Between 1980 and 2015, Mexican immigration to the United States and the share of Mexican immigrants in the labor force quintupled. We provide the first evidence examining whether this impacted one element of the work environment for native workers: workplace safety. To account for endogeneity and ensure that the change in Mexican immigration arose from supply shifts, we use 2SLS and instrumental variables. We show Mexican immigration over this period led natives to work in safer jobs; resulted in fewer workplace injuries for natives; and reduced WC benefit claims overall, which had a meaningful impact on employer costs for WC.

Objective: This study describes how the intermarriage behavior of Hispanic racial groups changed between 1990 and 2017. Background: Prior work on intermarriage trends has seldom examined the role of race in the mate selection behavior of Hispanics. The following three questions of fundamental importance have thus remained unanswered: (a) Did the intermarriage of all Hispanic racial groups slow down during the 1990s? (b) Did this trend persist after the 1990s? (c) Did the solidification and possible racialization of Hispanic pan‐ethnic identity contribute to changes in Hispanic intermarriage behavior over time? Methods: Using data from the 1990 U.S. Census, 2000 U.S. Census, and 2008 to 2017 American Community Survey, the author conducted log‐linear analyses to examine changes in the relative permeability of racial and pan‐ethnic boundaries between 1990 and 2017. Results: For Hispanic Whites, the odds of intermarriage with non‐Hispanic Whites remained unchanged during the 1990 but bounced back after 2000. For Hispanic Blacks, the corresponding odds increased steadily after 1990. For Hispanics who rejected official U.S. racial categories, the odds of intermarriage with non‐Hispanic Whites decreased over time. Conclusion: For Hispanic Whites, rates of intermarriages with non‐Hispanic Whites decreased during the 1990s in large part due to the surge of immigration from Latin America. Hispanic ethnicity may have become racialized over time for Hispanics who rejected official U.S. racial categories, but not Hispanic Whites and Hispanic Blacks. Implications: The findings from this study underscore the importance of considering racial heterogeneity when studying Hispanic intermarriage behavior.

Past research consistently suggests that singles are stigmatized, but do they constitute a stigmatized group? The current research provides deeper insight into the stigmatization of single people by understanding their ‘group-y’ nature, and how group identification and perception map onto discrimination and prejudice. Study 1 examined the extent to which singles identify as part of a group. Participants were assigned a novel minimal group identity and then completed measures of group identification for four group memberships (e.g., minimal group, relationship status, sexual orientation, nationality). As hypothesized, singles' identification with other singles was lower compared to their identification with other identities—as well as compared to partnered people's group identification. Contrary to our hypothesis, singles did not perceive less discrimination towards singles relative to other aspects of their identity. Study 2 examined the extent to which singles are perceived as a group and the extent to which their group-y-ness vs. perceived responsibility for their group membership explains the acceptability of prejudice towards them. Participants completed measures of entitativity and perceived responsibility for similar out-group identities as in Study 1 (e.g., single people vs. people in romantic relationships). As hypothesized, singles were rated lower in entitativity than people in romantic relationships and other groups. Prejudice towards singles was also more acceptable than prejudice towards national and sexual orientation groups. Accordingly, perceived responsibility was a stronger predictor of the acceptability of prejudice towards singles than their entitativity. We discuss the importance of group-based theoretical perspectives for understanding the current and future stigmatization and well-being of singles.

Introduction Aggregation of all Black populations in US cancer mortality profiles masks remarkable heterogeneity by place of birth. Comparing U.S-born African Americans with African and Afro-Caribbean immigrants may highlight specific cancer prevention and control needs and clarify global cancer epidemiology. Such a comparison has yet to be undertaken on a population basis. Methods Using 2012–2017 vital statistics data from California, Florida, Minnesota and New York, age-standardized cancer mortality rates were computed for distinct Black populations. Comparisons were made to the majority White population using mortality rate ratios (MRR) obtained from negative binomial regression. Results Of the 83,460 cancer deaths analyzed among Blacks, nearly 20 % were immigrants. African males and females had the lowest all-sites-combined cancer mortality rates (121 and 99 per 100,000, respectively), African Americans had the highest (232 and 163), while Afro-Caribbean were in between (140 and 106 respectively). The average Black:White MRR was significant for prostate (2.11), endometrial (2.05), stomach (2.02), multiple myeloma (1.87), premenopausal breast (1.66), liver (1.58) and cervical (1.56) cancers, (P < 0.05). Conclusion While, in aggregate, Blacks in the US have high cancer mortality rates, race itself is not the primary determinant of these disparities. Black immigrant populations show lower cancer mortality than both African Americans and Whites, especially for cancers where environmental factors feature more predominantly: lung, colorectal and breast. Even for cancers with high mortality among all African-descent groups, this study suggests a complex interplay between genetic and environmental factors. Endometrial cancer was unique; mortality rates were similarly high for all three analyzed Black groups.

Competition between and within groups of workers takes place in labor markets that are segmented along various, often unobservable dimensions. This paper proposes a measure of the intensity of competition in labor markets on the basis of limited data. The maximum entropy principle is used to make inferences about the unobserved mobility decisions of workers in US household data. The quantal response statistical equilibrium class of models can be seen to give robust microfoundations to the persistent patterns of wage inequality. An application to labor market competition between native and foreign-born workers in the United States shows that this class of models captures a substantial proportion of the informational content of observed wage distributions.

This dissertation examines the ways that age shapes residential patterns in the United States. Sociologists have learned much about residential segregation since the founding of the discipline. However, few directly consider age as an element of segregation itself or as an important factor shaping racial segregation. I address these gaps by studying age as a dimension of residential segregation and by focusing on how the age structure in households, neighborhoods and the population is associated with segregation by age and by race. I use US Census data to study segregation in neighborhoods and metropolitan areas from 1940 to 2015. In the three chapters I explore segregation by age, longitudinal aging patterns in census tracts and the connections between age structure, neighborhood aging patterns and racial segregation. I find that age indeed structures residential patterns in the United States and is due greater attention in the sociological segregation literature and in public debates about generational change.

Background: High prevalence of maternal malnutrition, low birth-weight and child malnutrition in India contribute substantially to the global malnutrition burden. Rural India has disproportionately higher levels of child malnutrition. Stunting and wasting are the primary determinants of child malnutrition and their district-level distribution shows clustering in different geographies and regions. Methods: The last round of National Family Health Survey (NFHS4) has disaggregated data by district, enabling a more nuanced understanding of the prevalence of markers of malnutrition. We used data from NFHS4 and agricultural statistics datasets to analyse relationship of area under cereal cultivation with the prevalence of malnutrition at the district level. We analysed malnutrition through data on under-5 stunting and wasting; maternal malnutrition was assessed through prevalence of women’s low BMI and short stature by district. Results: Stunting and wasting patterns across districts show a distinct geographical and age distribution; districts with higher wasting showed relatively high prevalence of 40% before six months of age. Wasting was associated with higher cultivation of millets, with a stronger association seen for jowar and other millets (Kodo millet, little millet, proso millet, barnyard millet and foxtail millet). Stunting was associated with cultivation of all crops except other millets. Low women’s BMI was seen associated with cultivation of rice and millets. The analysis was limited by lack of fine-scale data on prevalence of low birth-weight and type of cereal consumed. Conclusions: Multi-site observational studies of long-term effects of type of cereals consumed could help explain the ecogeographic distribution of malnutrition in India. Cereals, particularly millets constitute the bulk of protein intake among the poor, especially in rural areas in India where high prevalence of wasting persists.

Advertisement banner for the F1000 Human Migration Research Call for Papers. Full Article Figures & data References Citations Metrics Reprints & Permissions Get access ABSTRACT This article assesses (a) the extent to which state landlord–tenant legislation may influence local evictions and (b) whether those laws may influence eviction-related outcomes within communities of color. This analysis uses an original data set combining 2016 state- and block group-level data from Princeton University’s Eviction Lab, the American Community Survey, and landlord-tenant policy typologies, based on state statutes related to landlord-tenant law. Using multilevel mixed-effects models, we find that neighborhoods in states with more tenant-friendly policy environments were associated with lower eviction and filing rates compared with those in states with more landlord–friendly policies. However, compared with majority-White neighborhoods, eviction and filing rates in communities of color and majority-Black neighborhoods remained significantly higher—even in states with more tenant-friendly policies. In other words, tenant-friendly policies appear to support the reduction of eviction disparities but not the elimination of them. These findings suggest state housing policy environments matter for eviction-related outcomes broadly and for communities of color. We propose that eliminating racial disparities should include a focus on the implicitly racialized nature of housing and landlord–tenant policy, specifically.

Nowadays, women are much more likely to earn more income than their husbands do. But this is a shift, not a revolution, because very very few women are the kind of breadwinner that men used to be.

Driving is the single biggest source of household carbon emissions, and land-use policies that encourage higher density are motivated in part by findings of lower vehicle ownership rates in compact areas. However, many previous estimates suffer from self-selection bias. Utilizing an indicator variable for the presence of same gender children in the household as an instrument for population density, I find a 10% increase in density causes a 0.012 decrease in the size of a household’s vehicle fleet, a reduction of about half a percentage point.

Several immigration restriction laws, passed in the background of anti-immigration populism in the early 1920s, put an end to the period of “open borders” in the U.S. In this paper, I use the linked county sample in the early twentieth century to examine how immigration restriction laws led to different trends in segregation across groups. Difference-in-difference estimations show that all immigrant groups followed similar trends in segregation before the passage of immigration laws; afterwards, segregation among immigrants from more restricted countries declined relative to segregation among immigrants from less restricted countries. I then construct linked census samples at the individual level, and study mechanisms behind de-segregation. I find two possible mechanisms: (a) limitations on new arrivals; (b) selection on return migration. Further analyses suggest that de-segregation might not benefit immigrants’ socioeconomic assimilation.

Green space has been associated with better health and well-being. However, most studies have been cross-sectional with limited long-term exposure data. Further, research is limited in what type of green space is beneficial for health. We conducted a longitudinal study to assess sensitive periods (birth, childhood or adulthood) of exposure to different types of green space in association with adult blood pressure and body mass index (BMI). Using longitudinal data from the New England Family Study (1960–2000) and multilevel regression analysis, we examined associations between time-varying markers of residential exposure to green space, and adult BMI, systolic (SBP) and diastolic blood pressure (DBP) (N = 517). We created three exposure metrics: distance, average area, and green space count in the neighborhood throughout the life-course. In adjusted models, living one mile farther away from a green space at birth was associated with a 5.6 mmHg higher adult SBP (95%CI: 0.7, 10.5), and 3.5 mmHg higher DBP (95%CI: 0.3, 6.8). One more green space in the neighborhood at birth was also associated with lower DBP (−0.2 mmHg, 95%CI: −0.4, −0.02) in adulthood. Finally, average area of green space was not associated with SBP, DBP nor BMI. Analysis by type of green space suggested that parks may be more relevant than playgrounds, cemeteries or golf courses. Our study suggests that the perinatal period may be a critical time-period where living closer to green spaces may lower hypertension risk in adulthood, but not obesity.

Exclusionary zoning takes many forms, but always aims to limit economic integration within certain communities. Understanding the effectiveness of programs designed to reduce exclusionary zoning yields insight for future policy design, and the program that followed the Mount Laurel decisions in New Jersey remains relatively unexplored. The program created the Council on Affordable Housing (COAH), which used an incentive-based structure to implement affordable housing requirements. Municipalities that volunteered to meet their requirement received legal protection from zoning lawsuits. They could also engage in a regional contribution agreement (RCA), which allowed them to pay another municipality to complete up to 50% of their affordable housing obligation. Using probit and multinomial logit models, I investigate two questions concerning the program’s design: (a) Did COAH’s incentive-based structure succeed in attracting those municipalities with the greatest need for affordable housing? And (b) Did RCAs exhibit a pattern of high-income municipalities sending their affordable housing obligations to low-income municipalities? I find that the program succeeded in attracting high-income municipalities to participate, but that these municipalities were also likely to use RCAs to send housing units to low-income municipalities. I argue that the program’s design undermined the Mount Laurel decision’s original intent by limiting economic integration in high-income municipalities.