Scholars debate whether residential racial segregation associates positively, negatively, or at all with the black self-employment rate in the United States. This study engages that debate using data from the Integrated Public Use Microdata Series (IPUMS) 1980 5 percent State Sample and the 2006-2010 American Community Survey (ACS) five-year sample. Specifically, I investigate the county-level association between residential racial segregation and the black selfemployment rate in 1980 and 2010. Three indices measure residential racial segregation: (1) black-white dissimilarity, (2) black-white isolation, and (3) black clustering. The number of unincorporated black self-employees divided by the number of employed black adults (i.e., 16 years old and older) captures the black self-employment rate. Using fractional logit models and net of control variables, I find that residential racial segregation does not predict the black selfemployment rate in 1980, but positively predicts it in the South by 2010.

This research seeks to understand the rates of antenatal care for women in Mali during 2001, 2006, and 2012. The goal of this research is to analyze and compare antenatal care rates of women to other variables such as: desire for children, children ever born, marital status of women, etc.

We estimate how the non-pecuniary benefits related to the quality-of-life (e.g., clement weather) of a target firm’s location affect its acquisition price. Using new data on private firm acquisitions, we find that firms in cities with a higher quality-of-life sell for up to a 16% premium over comparable firms in cities with a lower quality-of-life. Using historical wage-to-rent differentials to instrument for the contemporaneous proxy of quality-of-life, we show that the premium for non-pecuniary amenities of a city is in addition to any premium for the economic and trade-production amenities (e.g., agglomeration economies and navigable waters) that affect firm fundamentals.

This paper uses regression analysis on a national data set from the United States from 2001-2016 to analyze racial or ethnic group disparities in home ownership between whites and blacks, Asian and Pacific Islanders, Puerto Ricans, Cubans, Mexicans, other Hispanics and American Indians. I employ Integrated Public Use Microdata combined with Bureau of Labor Statistics data and Federal Reserve Economic Data from the Federal Reserve Bank of St. Louis. Controlling for demographic, educational, income and wealth, employment and housing characteristics, I find no significant differences between whites and Asian and Pacific Islanders, Mexicans and American Indians. However, blacks, Puerto Ricans, Cubans and other Hispanics face racial disadvantages in regard to home ownership. All minority racial or ethnic groups, except American Indians, lost home ownership parity to whites from 2007-2011, the years primarily affected by the economic crisis.

In today’s society, children’s value to their parents is primarily emotional. As such, scholars have devoted a tremendous amount of effort to understanding how children both enhance, and diminish, the emotional wellbeing of parents. What remains unclear, however, is how these emotional ‘costs’ and ‘benefits’ vary across different socioeconomic segments of U.S. society. We investigate this question using random effects models and a representative sample of adults participating in the American Time Use Survey Wellbeing Module (N activities =52,036, N respondents =17,481). We find that caring for minor children (versus not) is associated with greater levels of positive emotions (happiness, meaning) and less sadness for all socioeconomic groups, but it is only associated with greater levels of negative emotions (stress, fatigue) for higher SES parents. This overall pattern of results was also observed when looking only at men. For women, however, it was only observed among higher SES mothers. For lower SES women, raising children did not seem to enhance, or diminish, emotional wellbeing. We discuss these SES and gender related findings in the context of recent trends in fertility among both lower and higher socioeconomic segments of society, as well as trends in social inequality more broadly.

Declines in American educational attainment and test scores in the 1970s, stagnating wages since that period, and recent increases in the mortality of white Americans have each sparked large literatures and public outcry. I propose a link between these notable episodes of decline and a few declines that had previously gone unnoticed. I present evidence of a precisely timed decline in the health and human capital of cohorts of Americans born after World War II, which predated labor market entry and played an important role in the above declines. There are discontinuous changes in the slope of “cohort effects” such that those born after 1947 or 1948 were less likely to work in white-collar occupations, earned less, gave birth to less healthy infants, and had a greater likelihood of dying prematurely, than they would have had the trend for earlier born cohorts continued. These declines are remarkably widespread among individuals born in the United States. The timing of the declines by cohort correspond closely to the schooling and test score declines but do not appear to be explained fully by them. I present tentative evidence that the root cause may have been a worsening of the respiratory health environment when these cohorts were infants.

Roughly one in ten Americans move every year, bringing significant social and economic impact to both the places they move from and places they move to. We show that migration intent mined from internet search queries can forecast domestic migration and provide new insights beyond government data. We extract from a major search engine (Bing.com) 120 million raw queries with migration intent from 2014 to 2016, including origin and destination geographies, and the specific intent for migration such as whether the potential migration is housing or employment related. Using these queries, we map U.S. state level migration flows, validate them against government data, and demonstrate that adding search query-based metrics explains variance in migration prediction above robust baseline models. In addition, we show that the specific migration intent extracted from these queries unpack the differential demands of migrants with different demographic backgrounds and geographic interests. Examples include interactions between age, education, and income, and migration attributes such as buying versus renting housing and employment in technology versus manual labor job sectors. We discuss how local government, policy makers, and computational social scientists can benefit from this information.

Women comprise approximately 8% of the active component in the Marine Corps, a number less than half of female representation in other military services. While the DoD’s recent mandate to fully integrate women is not the focus of this project, the policy dramatically increases the set of opportunities the Marine Corps can offer to women. This project seeks to provide a foundation to ultimately help determine the “optimal” number of women in the Marine Corps. In particular, we determine what a feasible level of gender integration could look like by creating an empirically justified upper bound of female representation across Marine Corps occupations. To establish this, we develop a mapping of Marine military occupational specialties (MOS) to its civilian equivalents using detailed job descriptors. We find previously male-only Marine MOS are equivalent to primarily male-dominated civilian jobs, where the proportions of women still sit at or below 5 percent. There is substantial variation in female representation across Marine jobs, however; for example, women comprise more than 25 percent in the Manpower/Admin Occupational Field (OCCFLD). The analysis reveals the occupational segregation in the Marine Corps closely mirrors that of the civilian . . .

The declining pattern of population density from city centres to the outskirts has been widely observed in American cities. Such a pattern reflects a trade-off between housing price/commuting cost and employment. However, most previous studies in urban population density functions are based on the Euclidean distance, and do not consider commuting cost in cities. This study provides an empirical evaluation of the classic population density functions in 382 metropolitan statistical areas (MSA) in the USA using travel times to city centres as the independent variable. The major findings of the study are: (1) the negative exponential function has the overall best fit for population density in the MSAs; (2) the Gaussian and exponential functions tend to fit larger MSAs, while the power function has better performance for small MSAs; (3) most of the MSAs appear to show a decentralisation trend during 1990–2016, and larger MSAs tend to have a higher rate of decentralisation. This study leverages crowdsourced geospatial data to provide empirical evidence of the classic urban economic models. The findings will increase our understanding about urban morphology, population–job displacement and urban decentralisation. The findings also provide baseline information to monitor and predict the changing trend of urban population distribution that could be driven by future environmental and technological changes.

Type 2 diabetes mellitus (T2DM) affects over 7.2% of the U.S. population and costs associated with the disease exceed $245 billion (CDC, 2017). In the past decade, T2DM research has generated over one million articles, yet the dissemination and translation of this large body of research remain a public health challenge. An impediment to disseminating and translating T2DM research is that all persons receiving information do not have the same capability to understand the information received. Understanding and processing of health information can be improved by tailoring and targeting the amount and level of health information. However, existing epidemiological intervention research lacks metrics to guide distribution of appropriate amounts and levels of health information. Further, existing interventions rarely consider interaction of factors, such as socioeconomic status, age and education level, in combination with health communication or behavioral response to health information. To address the need in epidemiological intervention research and public health communication, the objective of this research is to examine communication strategies of tailored and targeted messaging in terms of health outcomes and equity. In this research, an agent-based simulation model that depicts the processes of T2DM progress, information distribution and processing and behavior change was developed and validated, and then used to examine the effects of communication strategies with age, education level and income. The simulation results reveal that communication strategy of tailored messaging and random messaging are more effective in increasing adoption of health communication messages and life expectancy (L.E.). In addition, income statistically significantly affects adoption of health behavior. This research introduced a novel tri-diffusion agent-based simulation model integrating disease progression, information processing and behavior change in the context of a non-communicable disease, i.e., T2DM. Additionally, the Gini correlation 2 coefficient has been applied to assess the equity in terms of an intangible asset, i.e., health information. The evaluation results of health communication have met the need in epidemiological intervention research and public health communication. Further, understanding the impact of the interactions of key factors on health information communication and, indirectly, disease propagation, can provide insights to existing epidemiological trials and future research studies.

'Guest workers' earn higher wages overseas on temporary low-skill employment visas. This wage effect can quantify global inefficiencies in the pure spatial allocation of labor between poorer and richer countries. But rigorous estimates are rare, complicated by migrant self-selection. This paper tests the effects of guest work on Indian applicants to a construction job in the United Arab Emirates, where a crisis exogenously influenced job placement. Guest work raised the return to labor by a factor of four, implying large spatial inefficiency. Short-term effects on households were modest. Effects on information, debt, and later migration were incompatible with systematic fraud.

After more than a century of convergence, the economic fortunes of rich and poor regions of the United States have diverged dramatically over the last 40 years. Roughly a third of the US population now lives in metropolitan areas that are substantially richer or poorer than the nation as a whole, almost three times the proportion that did in 1980. In this paper I use counterfactual simulations based on Census microdata to understand the dynamics of regional divergence. I first show that regional divergence has primarily resulted from the richest people and places pulling away from the rest of the country. I then estimate the relative contributions to regional divergence of two major socioeconomic trends of recent decades: the sorting of people across metro areas by income level and the national rise in income inequality. I show that the national rise in income inequality is sufficient on its own to account for more than half of the observed divergence across regions, while income sorting on its own accounts for less than a quarter. The major driver of regional economic divergence is national-level income dispersion that has exacerbated preexisting spatial inequalities.

Importance Cancer survivors experience difficulties in maintaining health care coverage, but the reasons and risk factors for lack of insurance are poorly defined. Objective To assess self-reported reasons for not having insurance and demographic and socioeconomic factors associated with uninsured status among cancer survivors, before and after implementation of the Affordable Care Act (ACA) in 2014. Design, Setting, and Participants This survey study analyzes National Health Interview Survey (NHIS) data from January 1, 2000, through December 31, 2017. Included were adult participants (age, 18-64 years) reporting a cancer diagnosis; however, those with a diagnosis of nonmelanoma skin cancer were excluded. Exposures Insurance status. Main Outcomes and Measures Multivariable logistic regression was used to define the association between demographic and socioeconomic variables and odds of being uninsured. The prevalence of the most common self-reported reasons for not having insurance (cost, unemployment, employment-related reason, family-related reason) were estimated, with adjusted odds ratios (aORs) for each of the reasons defined by multivariable logistic . . .

Although public debate ensues over whether parents or nonparents have higher levels of emotional wellbeing, scholars have suggested that both statuses are associated with a mixed bag of emotions. Drawing on the American Time Use Survey (2010, 2012, 2013) and unique measures of subjective wellbeing that capture positive and negative feelings linked to daily activities, we ‘unpack’ this mixed bag. We do so by examining contextual variation in the parenting emotions gap based on: (1) activity type, (2) whether parents’ children were present, (3) parenting stage, and (4) gender. We find that parenting is associated with more positive emotions than nonparenting, but also more negative emotions. This pattern only existed during housework and leisure, however; not paid labor. Moreover, patterns in positive emotions only existed when parents’ children were present; whereas patterns in negative emotions were primarily observed during earlier stages of parenting. Results were similar for men and women.

This paper investigates the relationship between income and commute time, both at the individual and community levels. I use data from Integrated Public Use Microdata Series (IPUMS) sourced from the American Community Survey to show that increases in average income in a community are associated with increases in average commute time. In addition, I examine data from Los Angeles County to show that between individuals of the same demographic characteristics, higher income is associated with longer commute time. Across the United States, I find that commute times have been increasing in the 13 years sampled, but the increase is consistent across all races, education levels, and income deciles. Though increases in income are associated with increases in commute time for individual communities, I find that within Los Angeles, the average income of a community is negatively related to average commute time, meaning that residents of poor communities in Los Angeles take longer to get to work than their wealthy counterparts.

Using Census Bureau estimates of the market value of in-kind transfers and Current Population Survey (ASEC-CPS) data over the period 1979 to 2007, Burkhauser et al. (2012b) construct measures of income and its distribution. We extend their work forward to 2016 and back to 1967 using ASEC-CPS data and decennial Census data for 1959. With this newly linked data set, we provide a fresh look at the twenty-year period 1959 to 1979 that encompasses the inauguration of New Frontier and Great Society programs as well as the first survey-based look at levels and trends in income and its distribution from 1959 to 2016. We find that the dramatic decline in the market income of the middle class (measured as the median American tax unit or the mean value of the middle quintile of American tax units) began in 1969. However, we find that this decline was more than offset by government tax and transfer programs—especially in-kind transfers. Conventional measures of median income and income inequality that exclude the market value of in-kind transfers will substantially understate the impact of government policies in offsetting the stagnation of median market income growth and the rise in market income inequality since 1969.

Discussions regarding immigrants and their economic output in the United States have been on-going for quite some time now. The policies surrounding the topic significantly affect immigration from the country which the United States accepts the most immigrants, Mexico. In 2017, the Pew Research Center found that 11.2 million immigrants living in the U.S. were from Mexico, accounting for 25% of all U.S. immigrants (China being the next largest at 6%). Additionally, the Pew Research Center projects that immigrants and their U.S. born descendants will account for 88% of U.S. population growth through 2065, assuming current immigration trends continue. This points toward a significant factor to consider, from both the political and economic perspectives – the assimilation and performance of the second generation of Mexican immigrants in the U.S. labor market. Analysis of such a large portion of our current and projected population is imperative in order to provide a large-scale representation of their economic effects in the United States.

There is growing concern over rising economic inequality, the decline of the middle class, and a polarization of the U.S. workforce. This study examines the extent to which workers in the United States transition from low-end to higher-quality occupations, and explores the factors associated with such a move up the job ladder. Using data covering the expansion following the Great Recession (2011-2017) and focusing on short-term (i.e., less than 1 year) labor market transitions, the authors find that just slightly more than 5% of workers in low-end occupations moved into a higher-quality occupation. Instead, around 70% of workers in low-end occupations stayed in the same occupation, 11% exited the labor force, 7% became unemployed, and 6% switched to a different low-end occupation. Study results point to the importance of educational attainment in helping workers successfully climb the job ladder.

Importance National guidelines recommend screening for several cancer types, yet screening rates remain below target. To date, cancer screening patterns by smoking status, a major cancer risk factor, are unknown. Objective To assess cancer screening patterns among individuals who never smoked (never smokers), formerly smoked (former smokers), and currently smoke (current smokers) in the United States. Design, Setting, and Participants This cross-sectional study assessed data from the National Health Interview Survey years 2010, 2013, and 2015. Adult participants (aged ≥18 years) who had never reported a cancer diagnosis were included in the analysis. Data were analyzed from August 1, 2018, through February 1, 2019. Exposures Receipt of cancer screening, including colonoscopy, mammography, prostate-specific antigen testing, and Papanicolaou test per the US Preventive Services Task Force guidelines. Main Outcomes and Measures Multivariable logistic regression defined adjusted odds ratios (AORs) and 95% CIs for undergoing cancer screening by smoking status. Among participants who received a specific screening test, AORs and 95% CIs of receiving the test within guideline-recommended intervals were also assessed. Results Among 83 176 participants (45 851 [55.1%] women; mean [SD] age, 47 [18] years), 51 014 (61.3%) were never smokers; 17 235 (20.7%), former smokers; and 14 927 (17.9%), current smokers. Compared with never smokers, current smokers were less likely to ever have received a colonoscopy (43.8% vs 57.7%; AOR, 0.74; 95% CI, 0.68-0.82;P < .001), mammogram (88.8% vs 93.3%; AOR, 0.70; 95% CI, 0.57-0.87;P = .001), or prostate-specific antigen test (46.1% vs 60.8%; AOR, 0.76; 95% CI, 0.64-0.90;P = .001). Among those who had ever received a specific screening test, current smokers were less likely to have undergone colonoscopy (92.1% vs 95.1%; AOR, 0.75; 95% CI, 0.59-0.96;P = .02), mammography (62.4% vs 79.4%; AOR, 0.52; 95% CI, 0.45-0.60;P < .001), or Papanicolaou test (80.9% vs 90.8%; AOR, 0.61; 95% CI, 0.56-0.67;P < .001) within the recommended time frame compared with never smokers. Former smokers were more likely than never smokers to undergo any of the screening studies evaluated, with the exception of prostate-specific antigen screening (colonoscopy, 65.2% vs 57.7%; AOR, 1.20; 95% CI, 1.12-1.30;P < .001; mammography, 95.7% vs 93.3%; AOR, 1.35; 95% CI, 1.07-1.70;P = .01; Papanicolaou test, 97.6% vs 91.4%; AOR, 2.51; 95% CI, 1.93-3.26;P < .001). Conclusions and Relevance This study found that current smokers appeared to be less likely to receive guideline-concordant screening studies for breast, prostate, and colorectal cancer compared with never smokers. Further research is needed to identify barriers to screening among current smokers with the goal of increasing acceptance and uptake of cancer screening among this population at high risk of cancer.

Objective: To determine the link between children ever born and children ever died in Ethiopia using IPUMS DHS data. This link will be further explained through the use of food security data provided by FEWS NET and UN-OCHA.