A secure job that pays above-poverty wages is a fundamental economic underpinning of a good life, but one that is absent or precarious for many workers in the rural United States. This paper examines the link between work and poverty in rural America, drawing comparisons over time and in relation to national averages and conditions in urban areas. Using data from the 2001 to 2014 Current Population Surveys, we address three analytic objectives. First, we track changes in the share of poor householders in work, and compare the prevalence of work between the rural and urban poor. Second, we estimate trends in the share of rural and urban workers who are poor, and highlight key social and demographic differentials. Third and finally, we estimate a series of logistic regression models to assess whether and to what extent rural-urban and temporal differences can be explained by the composition of the workforce and changes therein. Results show that an increasing share of the rural poor are out of work, and that the risk of poverty among those who are employed has also increased. While some of the longstanding rural disadvantage appears to have moderated in recent years, these changes are largely due to declining conditions in urban areas. Overall, our results support pessimistic conclusions about the economic status of rural America's workforce, and the ability of rural American's to meet the basic requisites of the good life through work.

Given the traditional interpretation of women's labor force participation rate (LFPR) trends as movements along a positively sloped labor supply curve, it is surprising that the recent downward trend in U.S. women's LFPR has occurred over a period when women's real wages were commonly believed to be rising. I find that almost two‐thirds of the decline since 2000 is attributable to aging of the adult female population. The remainder, due to declining labor force participation for women under 55, becomes less puzzling in light of my evidence that the wage/education locus faced by women actually may have worsened since 2000.

America was on the move. The US Census has calculated the mean center of the US since 1790, and I Fig. 6.1 displays the trajectory of these means from 1790 to 2010. Of course, our main concern in this chapter is the Era 1950 to 1980. Nevertheless, note the movement West and Southwest. In 1950, the mean center of the US were in Richland County, Illinois and Clay County, Illinois. In 1960, Illinois continued to hold the mean center in Clinton, County Illinois. In 1970, St. Clair County, Illinois held the distinction of being the mean center of the US. In 1980, the mean center left Illinois and was located in Jefferson, County, and Missouri. America continued its movement west.

Ambitious global goals have been established to provide universal access to affordable modern contraceptive methods. The UN's sustainable development goal 3.7.1 proposes satisfying the demand for family planning (FP) services by increasing the proportion of women of reproductive age using modern methods. To measure progress toward such goals in populous countries like Nigeria, it's essential to characterize the current levels and trends of FP indicators such as unmet need and modern contraceptive prevalence rates (mCPR). Moreover, the substantial heterogeneity across Nigeria and scale of programmatic implementation requires a sub-national resolution of these FP indicators. However, significant challenges face estimating FP indicators sub-nationally in Nigeria. In this article, we develop a robust, data-driven model to utilize all available surveys to estimate the levels and trends of FP indicators in Nigerian states for all women and by age-parity demographic subgroups. We estimate that overall rates and trends of mCPR and unmet need have remained low in Nigeria: the average annual rate of change for mCPR by state is 0.5% (0.4%,0.6%) from 2012-2017. Unmet need by age-parity demographic groups varied significantly across Nigeria; parous women express much higher rates of unmet need than nulliparous women. Our hierarchical Bayesian model incorporates data from a diverse set of survey instruments, accounts for survey uncertainty, leverages spatio-temporal smoothing, and produces probabilistic estimates with uncertainty intervals. Our flexible modeling framework directly informs programmatic decision-making by identifying age-parity-state subgroups with large rates of unmet need, highlights conflicting trends across survey instruments, and holistically interprets direct survey estimates.

We construct longitudinal data from U.S. census records to study the economics of the Dust Bowl migration of the 1930s. Most of our findings contradict long-standing perceptions. While migration rates were high relative to elsewhere in the United States, they were similar to migration rates from the region in the 1920s. Relative to other occupations, farmers were the least likely to move. Furthermore, migrants from the Dust Bowl were not exceptionally likely to move to California. Finally, there was negligible migrant selectivity, and migration was not associated with long-lasting negative labor market outcomes; indeed, for farmers, the gains from migration were positive.

When Secretary of Commerce Wilbur L. Ross Jr. issued a statement on March 26, 2018, requiring the Census Bureau to add a question on citizenship to the 2020 Census questionnaire, it stirred up a storm of controversy. Much of the discussion was about the impact the decision would have on response rates in the 2020 Census. The citizenship question planned for the 2020 Census is the same as the one currently asked in the American Community Survey (ACS). The context of the ACS and the decennial census are quite different, but analysis of the ACS citizenship question can shed light on potential responses to the citizenship question in the 2020 Census. Completing the decennial questionnaire is mandatory for everyone in the United States and participating in the ACS is mandatory for everyone who is randomly selected to receive it each year. This paper provides a descriptive analysis of the nonresponse . . .

In this paper, we analyze the role of culture in determining whether, or not, an individual is a homeowner. We use data on first-generation immigrants who arrived in the United States under 6 years old. Following the epidemiological approach, those early-arrival immigrants grew up under the same US laws, markets, and institutions, so any dissimilarity in the proportion of homeowners by country of origin may be interpreted as a consequence of cultural differences. Our estimates indicate that there is a positive and statistically significant relationship between the cultural proxy, that is, the proportion of individuals who are homeowners by country of origin, and the immigrants’ choice of home-ownership. Results are maintained after controlling for home-country observable and unobservable characteristics, and are consistent in several subsamples. Neither the differences in the formation of couples (same or different origin) nor the existence (or not) of mortgage financing appear to be driving our findings. Additionally, we present evidence of different mechanisms of transmission of culture (horizontal transmission, respect for elders, and gender roles), which reinforces our results on the cultural effect.

BACKGROUND: Suboptimal exclusive breastfeeding (EBF) is a serious public health issue as it is associated with infant and maternal morbidity and mortality. Health care practices mothers experience in hospitals and primary care settings are highly influential during the critical window when breastfeeding is being established and maintained. Research on health care practices in these settings is essential to positively impact breastfeeding rates. OBJECTIVE: Our goal was to examine the role of health care practices and breastfeeding outcomes during the early postpartum period by exploring maternity care practices such as the Baby-friendly Hospital Initiative (BFHI) in the hospital and the Outpatient Breastfeeding Champion (OBC) program in the primary care setting. Methods: Data obtained from hospitals nationwide was analyzed along with one health care systems implementation of a breastfeeding support program. Relationships between EBF rates in hospitals and BFHI status, maternity care practices, and demographic characteristics were explored using linear regression. In a primary care setting, nurses, medical providers and mothers were evaluated pre- and post-implementation of the OBC program. Non-parametric tests and generalized linear models were used to test statistical differences and relationships. RESULTS: In the hospital setting, BFHI was associated with higher EBF rates (p < 0.01) across all population demographics studied. Using multiple linear regression, a model was built that included a collection of maternity care practices and demographic characteristics that explained almost half the variability in EBF rates (Adjusted R2 = 47.3%). In the primary care setting, we found nurses’ attitudes towards breastfeeding (p < 0.05), nurses’ self-confidence in managing breastfeeding position and attachment (p = 0.09), and mothers attainment of breastfeeding goals was higher (p = 0.06) after the OBC program was implemented compared to data collected before the OBC program was implemented. CONCLUSION: A systematic approach to providing breastfeeding support in hospitals is important as no single health care practice was able to explain the variability in EBF rates as well as a collection of maternity care practices. In the primary care setting, a model of breastfeeding support, such as the OBC program, has the potential to positively influence mothers’ achievement of breastfeeding goals, nurses’ breastfeeding attitudes, and nurses’ self-confidence in providing breastfeeding support.

The effects of race, class, and residential segregation on housing values continue to be a major focus of sociological research. Nevertheless, there has yet to be a study that places these factors in the context of the great recession of 2008 and 2009. Accordingly, the purpose of this work is to assess the extent to which the great recession affected housing values for African Americans and whites relative to the joint effects of race, class, and residential segregation. The following research questions are addressed: (1) How do segregation and socioeconomic status (SES) affect racial differences in housing values? (2) What were the levels of racial disparity in housing values before, during, and after the great recession? and (3) Were the housing values of higher status African Americans insulated from the negative impact of segregation and the great recession compared with their lower status counterparts? Using the Integrated Public Use Micro-data Series, the 2010 metropolitan area dissimilarity and population density scores, and hierarchical linear modeling, the findings revealed that the great recession exacerbated racial differences in housing values most in the higher SES categories. Higher status African Americans were more disadvantaged relative to comparable whites than lower status African Americans compared with similar whites in terms of housing values. The article concludes with a discussion of the implications of the findings.

Objectives. To estimate the impact of Supplemental Nutrition Assistance Program (SNAP) participation on cost-related medication nonadherence (CRN) for older adults in the United States, with a particular focus on those who are food insecure and those threatened by hunger. Methods. We used propensity score matching to create matched intervention and comparison groups of SNAP-eligible US adults aged 60 years and older with data from the 2013–2015 National Health Interview Survey. Intervention group participants were identified on the basis of self-reported SNAP participation in the past year. Results. SNAP participants were 4.8 percentage points less likely to engage in CRN than eligible nonparticipants (P < .01). The effect of SNAP is about twice as large for older adults threatened by hunger (9.1 percentage points; P < .01), and considerable even for those who are food insecure (7.4 percentage points; P < .05). Conclusions. Findings point to a spillover “income effect” as SNAP may help older adults better afford their medications, conceivably by reducing out-of-pocket food expenditures. When prescribing treatment plans, health systems and payers have a vested interest in connecting older patients to SNAP and other resources that may help address barriers to care.

The foreign-born share of the U.S. population has been gradually rising in recent decades and is approaching its historic maximum. Areas that have not traditionally received immigrants have experienced greater increases in the foreign-born share than have other areas with persistently high levels of immigration. This raises clear questions about the macroeconomic impacts of immigration on native workers. Economic theory suggests that immigration shifts out labor supply, reducing wages for natives in the short run because labor demand is downward sloping, and raising unemployment among natives if wages do not fall. Although theoretically sound and widely cited in the U.S. immigration debate, this static view has received mixed support in the scientific literature. Researchers continue to debate whether influxes of immigrants like the Mariel Boatlift of 1980 reduced wages or employment among native workers in Miami, with a body of empirical evidence that often appears ambiguous. . .

State governments have been passing laws mandating insurers to allow young adults to stay on their parents' health insurance plans past the age of 19 since the 1970s. These laws were intended to increase coverage, but research has been inconclusive on whether they were successful. We reconsider the issue with an improved approach featuring three key elements: a new, accurate dataset on state mandates; recognition that effects could differ greatly by age due to take up rate differences; and avoidance of endogenous characteristics when identifying mandate eligible young adults. We find the impact of the state mandates was concentrated among the 19 to 22 age group, for which dependent coverage increased sharply by about 6 percentage points. Overall coverage increased by almost 3 percentage points, with the difference explained by crowd out of public insurance. Crowd out of coverage through young adults own jobs was negligible. For those above age 22, we find little evidence of changes in coverage. We incorporate these insights into analysis of the Affordable Care Act (ACA) dependent coverage mandate, showing its effects were focused among those whom were previously ineligible for state mandates, or were eligible but older than 22. We argue the ACA's impact was broader because it had fewer eligibility conditions that implied parental dependence; young adults could be on their parents' insurance but still be relatively independent.

This paper uses a mixed-methods approach to explore the increased use of domestic workers in the United States and the political economy around reforms to protect these workers from labor standards violations. Domestic workers are predominantly female with a high proportion of immigrants. Labor force survey data indicate that the number of home health aides has surpassed housekeepers and child care providers, and qualitative evidence points to multiple problems with wage and hour violations and poor working conditions. Case study evidence for New Jersey from a representative household survey indicates that the majority of household employers are unfamiliar with legislation that governs the wages and hours of their domestic workers. More in-depth interviews suggest that wage theft is the main concern among advocates for low-wage workers, which could be addressed by a "domestic worker bill of rights" as passed in eight other states or by targeted wage theft legislation that includes increased employer liability in wage recovery lawsuits.

Data integration is a common process for projects aiming at reporting. National Research Information Hub is an example of data integration projects, which aim to provide insight and uncover interdependencies in the education field in Finland. A part of this project - Research Infrastructure (RI) Databank Service - focuses on harvesting data related to research infrastructures. Recent changes in RI Databank Service scope introduced organizational and architectural challenges implying automated integrations with partner universities’ systems. This thesis aims to address new requirements by creating a prototype for the next improved version of RI Databank Service application. The goal of the prototype implementation is to evaluate architectural approach viability and to verify the technological compatibility of the software components. The thesis is a report of lessons learnt during the service development. The results show that the application created in this project is able to integrate with common data format used in universities’ systems. Also, it is capable of adjusting to the changing data model. Performance testing has confirmed that data transformation speed satisfies the requirements. In contrast with the previous service version, the prototype is simpler, despite the overall increase in the functionality. Usage of code generation tools . . .

The Army possesses vast amounts of administrative (archival) data about Soldiers. These data sources include screening tests, personnel action codes, training scores, global assessments, physical fitness scores, and more. However, the Army has yet to integrate these data to create a holistic operating picture. Our research focuses on repurposing Army administrative data to (1) operationalize social constructs of interest to the Army (e.g., Army Values, Warrior Ethos, Character) and (2) model the predictive relationship between these constructs and individual (i.e., Soldier) and team (i.e., unit) performance and readiness. The goal of the research is to provide people analytics models for the purposes of optimizing human capital management decisions. This presentation describes the theoretical underpinnings of our human performance model, drawing on disciplines such as social and industrial/organizational psychology, as well as our experience gaining access to, and working with Army administrative data sources. Access to the archival administrative data is provided through the Army Analytics Group (AAG), Person-event Data Environment (PDE). The PDE is a business intelligence platform that has two central functions: (1) to provide a secure repository for data sources on U.S. military personnel; and (2) to provide a secure collaborative work environment where researchers can access unclassified but sensitive military data.

Economists generally agree that more complete property rights lead to higher incomes, but rights are often constrained by other political and social goals. American Indian reservations provide a powerful example. Reservation poverty is often attributed to poor quality land as a result of expropriation and transfers to non-Indians, but a more complete explanation requires understanding how efforts to prevent further transfers shaped reservation land tenure. Under the Dawes Act of 1887, reservation lands were allotted to individual Indians, but held in trust by the federal government until allottees were deemed “competent” to hold fee-simple title. In 1934 the Indian Reorganization Act locked into trusteeship those lands that had not been released. We assess whether incomplete property rights resulting from trusteeship have affected reservation incomes using new panel data on income, land quality, and tenure. Our data reveal a U-shape between per capita income and the share of prime agricultural land on reservations. This is because reservations with relatively poor land were less likely to be allotted and, hence, remain under tribal control while reservations with high quality land were more likely to become fully privatized. Reservations with mid-quality land were allotted, but were less likely to be released from trusteeship. We conclude that incomplete property rights have stunted income growth for Native Americans, relative to local control, whether communal or private.

We use data from the 2003-2014 American Time Use Survey to estimate the effects of time allocated to work and extracurriculars on time spent in educational activities (class and homework) for live-at-home college students, who make up a large share of the college population. Our instrumental variables strategy indicates that students are more likely to substitute time away from homework than from class, and that the effects are generally stronger for work than for extracurriculars. These findings, which remain even after correcting for selection on unobservables through non-parametric matching methods, show that work leads to decreases in the amount of time spent in class by 47 min and on homework by 56 min, whereas extracurriculars lead to a loss of 22 min of homework time. Thus, while after-school activities (extracurriculars and work) may be beneficial with respect to human capital development, they may also have a counteracting, unintended effect due to students' substitution away from educational pursuits. [ABSTRACT FROM AUTHOR] Copyright of Applied Economics is the property of Routledge and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This dissertation studies how the spatial distributions of firms and consumers shape their interactions in local credit markets. For firms, proximity provides information about the preferences and credit quality of local consumers. For consumers, it facilitates gathering information about product availability and the prices at local firms. I explore these dynamics by developing stylized models that illustrate the key dynamics of interest and motivate empirical estimations that I take to data. In particular, this dissertation uses many novel big data assets that provide new insights into the functioning of local credit markets. In the first chapter, I study whether online retail is a complement or substitute to local offline economies by studying how consumers reorganize their trips to grocery stores and coffee shops after they become online grocery shoppers. To do so, I use new, detailed data on the daily online and offline transactions of millions of anonymized customers. My results show that consumer behaviors can create positive complementarities between online retail and some brick-and-mortar stores, creating both winning and losing stores and consumers to online retail. In the second chapter, I study the impact of branch presence on mortgage credit outcomes in the surrounding neighborhood using the density of nearby bank branch networks to instrument for actual branch presence. I find that lenders with branches lend more mortgages to borrowers in the surrounding neighborhood and that those operated by local lenders have the most positive impact for low socioeconomic-status borrowers. However, I show that branches disadvantage competing lenders by lowering the credit-quality of the competing lenders' applicant pool. This adverse selection causes an aggregate negative effect of branch presence on neighborhood mortgage outcomes. In the third chapter, co-authored with Benjamin J. Keys and Jane K. Dokko, we construct a novel county-level dataset to analyze the relationship between rising house prices and non-traditional features of mortgage contracts. We apply a break-point methodology and find that, in many markets, rising use of non-traditional mortgages predates the start of the housing boom and continues to rise thereafter.

In this section, we present an extensive series of recommendations for best practices based on the chapters in this volume and other sources. This summary of the key recommendations for this book makes this chapter a valuable reference guide for anyone wanting quick direction for best practices. While the text in this chapter is minimal, the references that are included provide opportunities for further investigation into the empirical basis for the recommendations.

Men make history, but not as they please. In his research on American education, the historian Lawrence Cremin crafted a narrative on US education and how it was influenced by historical events. It was a monumental task for which Cremin were amply rewarded. As an historian Cremin knew that historical events played a critical role in the development and shaping of institutions. The US educational system was one such institution. The present volume addresses a simple conjecture that emanates from Cemin’s research: the impact of historical events in American history that have shaped the demography of the US student population––directly or indirectly.