OBJECTIVES To determine the extent to which opioid prescribing rates vary across US congressional districts. METHODS In an observational cross-sectional framework using secondary data, we constructed 2016 congressional district-level opioid prescribing rate estimates using a population-weighted methodology. RESULTS High prescribing rate districts were concentrated in the South, Appalachia, and the rural West. Low-rate districts were concentrated in urban centers. CONCLUSIONS In the midst of an opioid overdose crisis, we identified congressional districts of particular concern for opioid prescription saturation. Public Health Implications. The congressional district geography represents a policy-relevant boundary and a politically important level at which to monitor the crisis and determine program funding. Furthermore, in the context of the opioid crisis, knowing how congressional districts rank across the country and in states is useful in the creation of policies targeted to areas in need.

“An Organized Inequity” counters the accepted narrative of JapaneseAmericans assimilating back into American society with ease. Franklin Delano Roosevelt’s signing of Executive Order 9066 allowed for Japanese Relocation, as well as the hardships yet to come for those of Japanese heritage in America. It takes into account personal testimonies from camp inmates, examines education repertoire for children within the camps, as well as graduation statistics from Japanese-American students within the camps in comparison to white students, and other minorities within the States. The essay endeavors to explicate the effect that poor living conditions and ineffective education within the camps, as well as discrimination faced after the war, had on the strive and success rate of JapaneseAmerican children after World War II.

In this article, I describe automatically linking newly accessible census data and World War I service records to enable a more holistic accounting of the connections between individual military experiences and emergent civilian population patterns. Employing models that can only be built from the individual level and examining relationships that are only traceable through linked data, I analyze how soldiers’ wartime experiences may have inflected postwar marital outcomes and explore how linkage decisions shape results. In so doing, I show how quantitative methods can be used to question the adequacy of traditional WWI narratives, and provide an example of how, even with limited resources, the usefulness of historical microdatasets can be leveraged through record linkage.

The earnings difference between black and white workers fell dramatically in the United States in the late 1960s and early 1970s. This paper shows that the extension of the minimum wage played a critical role in this decline. The 1966 Fair Labor Standards Act extended federal minimum wage coverage to agriculture, restaurants, nursing homes, and other services which were previously uncovered and where nearly a third of black workers were employed. We digitize over 1,000 hourly wage distributions from Bureau of Labor Statistics industry wage reports and use CPS micro-data to investigate the effects of this reform on wages, employment, and racial inequality. Using a cross-industry difference-indifferences design, we show that wages rose sharply for workers in the newly covered industries. The impact was nearly twice as large for black workers as for white. Within treated industries, the racial gap adjusted for observables fell from 25 log points pre-reform to zero afterwards. Using a bunching design, we find no effect of the reform on employment. We can rule out significant dis-employment effects for black workers. The 1966 extension of the minimum wage can explain more than 20% of the reduction in the racial earnings and income gap during the Civil Rights Era. Our findings shed new light on the dynamics of labor market inequality in the United States and suggest that minimum wage policy can play a critical role in reducing racial economic disparities.

This article advocates for broadening social science history to include an even larger horizon, to reach a new level of understanding of human society in the past. It builds on and shares insights from 20 years of research that integrates environmental knowledge and environmental science into a history of social change, while trying to understand in detail how people changed the environment. The focus of the research is the demographic, social, agricultural, and environmental history of the US Great Plains, from the 1870s to the end of the twentieth century. Beyond supporting the argument for a broader interdisciplinary vision of history, the article shows how the Great Plains environment was changed by human action, and the ways that the environment shaped human behavior in turn. The history of the plains shows that the impact of human action on the land was dramatic and unmistakable. People radically changed land cover, but their actions were only one factor in causing events like the Dust Bowl, and only one part of the measurable increase in greenhouse gases. At the same time, the environment also constrained and shaped human behavior, even though it had less to do with family organization than broad trends in social change in the late nineteenth and early twentieth centuries. The environment's most dramatic contribution was to spur out-migration in the 1930s when drought caused widespread agricultural failure, further confirmation of the importance of going beyond purely social factors to understand how people lived in the past.

A well-known limitation of commonly used segregation measures is their inability to describe patterns at multiple scales. Multi-level modeling approaches can describe how different levels of geography contribute to segregation, but may be difficult to interpret for non-technical audiences and have rarely been applied in the US context. This paper provides a readily interpretable description of multi-scale Black–non-Black segregation in the United States using a multi-level modeling approach and the most recent Census data available. We fit a three-level random intercept multi-level logistic regression model predicting the proportion of the population that is Black (Hispanic and non-Hispanic) at the block group level, with block groups nested in tracts and tracts nested in Metropolitan Statistical Areas (MSAs). For the 102 largest MSAs in the United States, we then estimated the extent to which micro- versus meso-level variability drives overall racial residential patterning within the MSA. Finally, we created a typology of racial residential patterning within MSAs based on the total proportion of the MSA population that is Black and the relative contribution of block groups (micro) versus tracts (meso) in driving variation. We find that nearly 80% of the national variation in the geographic concentration of Black residents is driven by within-MSA, tract-level processes. However, the relative contribution of small versus larger scales to within-MSA segregation varies substantially across metropolitan areas. We detect five meaningfully different types of metropolitan segregation across the largest MSAs. Multi-level descriptions of segregation may help planners and policymakers understand how and why segregated residential patterns are evolving in different places and could provide important insights into interventions that could improve integration at multiple scales.

In recent years military veterans have been attaining postsecondary education in increasing numbers. Little research has been performed however to compare veteran vs. non-veteran educational attainment rates of women, or Black and Hispanic males. Moreover, the increasing comparative gap ratios of these groups of veterans vs. non-veterans have not been studied. Additionally, differences among regional geographic divisions have not been studied beyond a cursory level. The present study is an examination of these issues and the testing of three related null hypotheses to determine whether there is a difference in the percentages of veteran vs. non-veteran postsecondary attainment at three academic levels: 1) one or more years without a degree; 2) associate's degree; and 3) bachelor's degree. Further, the study seeks to understand the possible differences that occur within the nine U.S. Census Bureau regional geographic divisions. Using 72 cross tabulations with Chi-square, independent-samples t-tests, matched pairs t-tests, and ANOVA, the study found that there were statistically significant differences between veteran and non-veteran educational attainment levels during the eleven year period from 2005-2015. The study also found that the participation rates and gap ratios increase over the years studied for both males and females and among Black and Hispanic males. Finally, ANOVA tests found no statically significant racial/ethnic differences among the regional geographic divisions.

We examine how, and to what extent, migrants in a host country attract foreign direct investment (FDI) from firms based in their country of origin (CO). Introducing the notion of institutional affinity, we argue that increased institutional affinity and increased connectedness of institutional environments of migrants’ CO and country of residence, make a location attractive to CO firms. Empirical analysis of FDI and migration panel data shows that in addition to the traditional factors influencing FDI patterns, there is a collective migrant effect on FDI, and this effect is statistically significant and economically meaningful for migrants from developing countries.

The available literature has shown a growing and a compelling interest amongst scholars and researchers to spatially measure neighborhood poverty concentration. Previous research has defined poverty measurement as an intricate process that involves analysis of the demographic and socioeconomic characteristics within a spatial environment (Rogers, 2015). Poverty measurement is, therefore, important for understanding the complexity of poverty and for assessing the effectiveness of poverty-mitigating policies (Rogers, 2015) Literature on measuring geographically concentrated poverty has focused on two main models: (1) the traditional global model that includes, for example, Ordinary Least Squares (OLS) classic regression, spatial autocorrelation (global Moran’s I); (2) the local geospatial model, mainly, Geographically Weighted Regression (GWR) (Anselin, 1995; Fotheringham & Brunsdon, 1999; Lloyd, 2010; Sandoval, 2015c). The global model measures the overall clustering of data and yields a single-value statistic for the whole study area. The local geospatial model, on the other hand, disaggregates global statistical data and yields multi-value statistics across different locations (Anselin, 1995; Lloyd, 2010; Sandoval, 2015c)...

This study examines how paid leave in the United States shapes working parents’ decisions along the family dimension of work-family interface. Specifically, I use data from the Current Population Survey, 1999 to 2009, and a difference-in-differences approach to estimate the impact of California’s Paid Family Leave (PFL) program on fertility behavior and whether the effect varies across socioeconomic status. Results indicate there is a positive effect of the policy on the probability a 25 to 40-year-old woman had a baby in the last year, which is equivalent to a 6.0 percent increase in birth likelihood after the PFL’s enactment. For women working fulltime, PFL increased birth likelihood by 7.6 percent. There is evidence of heterogeneity of stronger effect among women with earnings in the 25th to 75th percentile, high school graduates, and women in their 30s. In combination with previous research highlighting positive effects of PFL on labor market outcomes, these findings suggest the policy helps families combine work and childbearing.

This paper develops the first evidence on how individuals’ union membership status affects their net fiscal impact, the difference between taxes they pay and cost of public benefits they receive, enriching our understanding of how labor relations interacts with public economics. Current Population Survey data between 1994 and 2015 in pooled cross-sections and individual first-difference models yield evidence that union membership has a positive net fiscal impact through the worker-level channels studied.

Do customer-facing retail employees in the US have a higher prevalence of psychological distress? We examine psychological distress in a sample that includes 19,832 customer-facing retail employees from a sample of 1,115,280 employees of a cross-sectional National Health Interview Survey (NHIS) from 1997 through 2015. Our results show that customer-facing retail employees report significantly higher psychological distress than do employees in other industries and that its prevalence is increasing. These findings are consistent with mild and high levels of psychological distress. LASSO regression shows that, after self-reported health and poverty level, being a customer-facing retail employee is the third most important predictor of psychological distress.

This dissertation examines the economic causes and effects of changes in United States marriage law in the latter half of the twentieth century. It is composed of three papers which examine the causes of the no-fault divorce revolution and the effects of enforceable prenuptial agreements. My first paper, entitled "Economic Origins of the No-Fault Divorce Revolution", explores the causes of the no-fault divorce revolution in the United States. The no-fault revolution made divorce substantially easier by removing the requirement that a couple desiring a divorce convince a judge that grounds for a divorce existed—after the no-fault revolution, couples could divorce merely by mutual consent. The paper examines two sets of influences that militated for change – efficiency-based influences and interest-group influences. My second paper, entitled "Prenups", is an empirical investigation of the effect of prenuptial agreements on the divorce rate. Contrary to fears expressed when courts first began enforcing these agreements, my research shows that enforcing prenuptial agreements in fact lead to a substantial decline in the divorce rate. Finally, my third paper, entitled "Does Enforcing Prenuptial Agreements Encourage Marriage?", is an empirical investigation of the effect of prenuptial agreements on the marriage rate. Using certificate data from the National Vital Statistics Service (NVSS) and data from the Current Population Survey (CPS), I find that adoption of the UPAA increased marriage rates by approximately one-tenth of a standard deviation, or about one marriage per thousand persons per year and that these gains were strongest among people in their 30s and those with less than a high school education.

Building on neo-assimilation ideas, we conceptualise the ‘mainstream’ and then find compelling evidence of its expansion in the U.S. in the rising number of individuals who come from mixed minority–majority backgrounds. In terms of the contexts in which they are raised and their social identities and affiliations, on the whole they resemble whites more than they do minorities, and they marry whites at very high rates. Individuals who are partly black are exceptions to some of these patterns. We note an important similarity between this expansion and the one associated with post-World War II assimilation: both are connected with growing diversity of identity and ethnic expression in the mainstream. An equally important difference lies in the more modest magnitude of the current expansion. We close with a series of questions for future research raised by our argument.

Importance:Among adults with chronic disease, survivors of stroke have high out-of-pocket financial burdens. The US government enacted the Affordable Care Act (ACA) in 2010 and implemented the law in 2014 to provide more low-income adults with health insurance coverage. Objective:To assess whether ACA implementation is associated with cost-related nonadherence (CRN) to medication among adult survivors of stroke. Design, Setting, and Participants:This study analyzed data from the 2000 to 2016 National Health Interview Survey, an in-person household survey of the noninstitutionalized US population conducted annually by the National Center for Health Statistics. Conducted at the University of Michigan Medical School, Ann Arbor, from July 24, 2017, to February 28, 2018, the study had a sample of 13 930 survivors of stroke. Analyses were stratified by age (45-64 years vs ≥65 years). Time was treated as a continuous variable and as a categorical variable across 4 periods (2000-2005, historical control; 2006-2010, economic recession and peak unemployment; 2011-2013, before ACA implementation; and 2014-2016, after ACA implementation). Percentages are weighted to reflect US population estimates. Main Outcomes and Measures:The primary outcome was the self-report of CRN, defined as the inability to afford prescribed medications within the past 12 months. Results:Among the 13 930 total survivors of stroke, 38.1% were aged 45 to 64 years (50.5% were female and 49.5% were male, with a mean [SE] age of 56.0 [0.10] years), and 61.9% were aged 65 years or older (54.9% were female and 45.1% were male, with a man [SE] age of 76.2 [0.09] years). From 2011 to 2013 through 2014 to 2016, Medicaid increased (from 24.0% [95% CI, 21.0%-27.2%] in 2011-2013 to 30.8% [95% CI, 27.3%-34.6%] in 2014-2016; P < .001) and uninsurance decreased (from 13.7% [95% CI, 11.3%-16.4%] to 6.8% [95% CI, 5.3%-8.8%]; P < .001) among survivors of stroke aged 45 to 64 years. Among survivors aged 45 to 64 years, CRN increased over time before ACA implementation (from 18.6% [95% CI, 16.5%-20.9%] in 2000-2005, to 22.6% [95% CI, 19.7%-25.9%] in 2006-2010, to 23.8% [95% CI, 20.7%-27.3%] in 2011-2013) and decreased after ACA implementation to 18.1% (95% CI, 15.4%-21.3%; P = .01) in 2014 to 2016. The period after ACA implementation was associated with lower odds of CRN after adjustment for sociodemographics, year, and clinical factors (odds ratio [OR], 0.63; 95% CI, 0.47-0.85). The difference was attenuated after further adjustment for health insurance coverage (OR, 0.76; 95% CI, 0.56-1.03). Conclusions and Relevance:After the ACA implementation, health insurance coverage increased and CRN decreased among adult survivors of stroke, suggesting that further expansion of Medicaid coverage is likely to be advantageous for survivors.

In the United States, racial minorities generally experience poorer cardiovascular health compared to whites, and differences in alcohol consumption and sleep could contribute to these disparities. With a nationally representative sample of 187,950 adults in the National Health Interview Survey from 2004 to 2015, we examined the relationship between alcohol-drinking patterns and sleep duration/quality by race and sex. Using Poisson regression models with robust variance, we estimated sex-specific prevalence ratios for each sleep duration/quality category among blacks compared to whites within categories of alcohol-drinking pattern, adjusting for socioeconomic status and other potential confounders. Across alcohol drinking patterns, blacks were less likely than whites to report recommended sleep of 7–<9 h/day. Short (PR = 1.30 [95% CI: 1.22–1.39]) and long (PR = 1.30 [95% CI: 1.07–1.58]) sleep were 30% more prevalent among black-male infrequent heavy drinkers compared to white-male infrequent heavy drinkers. Short (PR = 1.27 [95% CI: 1.21–1.34]) sleep was more prevalent among black-female infrequent heavy drinkers compared to white-female infrequent heavy drinkers, but there was no difference for long sleep (PR = 1.09 [95% CI: 0.97–1.23]). Black female infrequent moderate drinkers, however, had a 16% higher (PR = 1.16 [95% CI: 1.01–1.33]) prevalence of long sleep compared to their white counterparts. Environmental, social, and biological factors contributing to these findings, along with their impact on disparate health outcomes, should be studied in greater detail.

It was an honor to be asked by Price Fishback to be the convener of the competition for the Allan Nevins Prize in American Economic History this year. Among the dissertations submitted, topics, methodologies, and geographic regions differed greatly. In addition to being varied, the dissertations were interesting and well researched. To say that it was a supreme challenge to discern the leading ones among them would be an understatement. It was refreshing and encouraging to observe what the future of economic history must hold, if these fertile lines of research are any indication of its trajectory. Three dissertations emerged as outstanding, and their innovations were derived in different ways. Two of these dissertations started with finding a meaningful gap in our understanding of economic history. All three uncovered very rich new historical data about which we can ask important economic questions. Both approaches are timehonored traditions in meaningfully contributing to our understanding of economic history. The three finalists were Vellore Arthi of Oxford University, Vincent Geloso of the London School of Economics and Political Science, and Carlos Hernandez of the University of California, Los Angeles. Before they explain their own research in their own words later, I will briefly provide some motivation and context for each.

Both the number and the geographic boundaries of the counties covering the territory of the United States changed frequently and significantly since 1790. In order to study the spatial aspects of the United States' economic history it is frequently necessary to create a consistent panel of spatial units, which are consistent over time. We provide such a cross-walk, that enables researchers to aggregate historical US county data for every decade since 1790 to current US counties and commuting zones. This note describes the details of our data construction and how to use this crosswalk in practice. A data package containing the decadal crosswalks since 1790 and the accompanying GIS files is available on our websites.

This paper documents the sources of data used in the construction of the estimates of the Levy Institute Measure of Economic Wellbeing (LIMEW) for the years 1959, 1972, 1982, 1989, 1992, 1995, 2000, 2001, 2004, 2007, 2010, and 2013. It also documents the methods used to combine the various sources of data into the synthetic dataset used to produce each year’s LIMEW estimates.

The following dissertation presents a narrative overview of Afghan immigration to the United States. It focuses on the manner in which political turmoil in Afghanistan influenced relations between the U.S. Afghan community and Afghanistan from 1890 to 2016. It also tests whether this relationship conforms to some of the most prominent scholarly models and theorizations of diasporas. In this study, the term “relations” encompasses individuals’ interactions and associations with Afghanistan’s society and government. This study finds a long history of diasporic relations between the United States and Afghanistan during this time-period. Historical events such as the British exit from South Asia in 1947, the 1978 coup in Afghanistan, and 2001 U.S. military intervention in Afghanistan have had profound effects on the U.S. Afghan community, influencing the feasibility of travel to Afghanistan, the nature of diasporic relations, and U.S policy toward Afghan immigration. As a result, U.S. Afghan diasporic relations can be broken x into generalizable eras between these critical historical events. Furthermore, the era’s politics influenced how the U.S. public perceived Afghans’ presence in the United States. This dissertation also examines how immigrants and ethnic communities such as Afghans in the United States have pursued activities they believed advanced the interests of both their country of origin and adopted country.