The first-half of the 20th century is characterized by mass migration from Europe to the US and rapid technological progress. Exploiting national immigration policy changes together with historical settlement patterns of immigrants’ across US counties, I estimate the effect of skilled immigration on local patenting rates. I find that counties that received more skilled immigrants had no impact on total patenting rates, but that this null effect masks a positive effect on the growing electrical and chemical fields and a negative effect on the traditional mechanical and textiles fields. Furthermore, I find that most of the effect is due to skilled immigration from Non-English Speaking Countries and from Countries with long patenting traditions. I offer a mechanism by which skilled immigrants act as ”Transmitters of Knowledge”, that is, they impact innovation primarily by introducing new knowledge that did not exist in their destination prior to their arrival.

Information retrieval (IR) methods seek to locate meaningful documents in large collections of textual and other data. Few studies apply these techniques to discover descriptions in historical documents for physical geography applications. This absence is noteworthy given the use of qualitative historical descriptions in physical geography and the amount of historical documentation online. This study, therefore, introduces an IR approach for finding meaningful and geographically resolved historical descriptions in large digital collections of historical documents. Presenting a biogeography application, it develops a ‘search engine’ using a boosted regression trees (BRT) model to assist in finding forest compositional descriptions (FCDs) based on textual features in a collection of county histories. The study then investigates whether FCDs corroborate existing estimates of relative abundances and spatial distributions of tree taxa from presettlement land survey records (PLSRs) and existing range maps. The BRT model is trained using portions of text from 458 US county histories. Evaluating the model’s performance upon a spatially independent test dataset, the model helps discover 97.5% of FCDs while reducing the amount of text to search through to 0.3% of total. The prevalence rank of taxa in FCDs (i.e. the number of times a taxon is mentioned at least once in an FCD, divided by the total number of FCDs, then ranked) is strongly related to the abundance rank in PLSRs. Patterns in species mentions from FCDs generally match relative abundance patterns from PLSRs. However, analyses suggest that FCDs contain biases towards large and economically valuable tree taxa and against smaller taxa. In the end, the study demonstrates the potential of IR approaches for developing novel datasets over large geographic areas, corroborating existing historical datasets, and providing spatial coverage of historic phenomena.

Females live longer than males in most parts of the world today. Among OECD nations in recent years, the difference in life expectancy at birth is around four to six years (seven in Japan). But have women always lived so much longer than men? The answer is that they have not. We ask when and why the female advantage emerged. We show that reductions in maternal mortality and fertility are not the reasons. Rather, we argue that the sharp reduction in infectious disease in the early twentieth century played a role. The primary reason is that those who survive most infectious diseases carry a health burden that affects organs, such as the heart, as well as impacting general well-being. We use new data from Massachusetts containing information on causes of death from 1887 to show that infectious diseases disproportionately affected females between the ages of 5 and 25. Increased longevity of women, therefore, occurred as the burden of infectious disease fell for all. Our explanation does not tell us why women live longer than men, but it does help understand the timing of the increase.

In the division of fiscal responsibilities between central and local governments, it is usually argued that income insurance and inequality should be dealt with by the central government. This paper explores the extent to which the US federal tax and transfer system is able to provide uniform social insurance to a prototype family in different states, given variations in state tax and transfer policies. We simulate the combined response of federal and state taxes and transfers to a negative pre-tax income shock, and compare the results for different states. We find large differences in the level of insurance experienced by households in different states, particularly for low income households, and that these differences are mostly driven by state policies. We would like to thank´Arpád´Abrahámthank´ thank´Arpádthank´Arpád´ thank´Arpád´Abrahám, Jérôme Adda, Manuel Arellano, Juan Dolado, AxelleFerrì ere, Ramon Mari-mon, Gaston Navarro and Dominik Sachs for useful comments and suggestions. We would also like to thank participants of the June 2017 ADEMU Summer School in Toulouse, the April 2018 workshop on Risk Sharing and Macroeconomic Interdependencies hosted by CERGE-EI and the May 2018 ADEMU Final conference hosted by the EUI, the 2018 ZEW Local Finance conference, as well as members of the EUI Macro Working Group for comments on an earlier version of this project. We are very grateful to Hilary Hoynes and Erzo Luttmer for generously sharing their calculators for Medicaid and AFDC/TANF benefits.

Diabetes is an epidemic that has started to capture political attention in the United States because of the devastating health care costs associated with the disease. Researchers in other studies have concluded that additional education face-to-face (FTF) and FTF with alternative forms of diabetes communication (FTF plus) have been beneficial. However, there is very little information on the comparison of the two groups as mentioned above when comparing chronic limitations, self-perception, health status, and healthcare satisfaction as circumscribed by specific demographic population. This study was an investigation of the above variables and explored how specific demographic characteristics (age, gender, educational level, and race/ethnic background) may have an identifiable association with each diabetes education type, either FTF or FTF plus. This research involved the use of the social cognitive theory and the health belief model to help explain self-care behavior changes. This quantitative, cross-sectional study used secondary data from the 2016 National Health Interview Survey for analysis. A simple . . .

For the first time since comparable data was first collected in 2008, the nation’s steady progress in reducing the number of children without health insurance reversed course. The number of uninsured children under age 191 nationwide increased by an estimated 276,000 to about 3.9 million (3,925,000) in 2017, according to newly-available data from the U.S. Census Bureau (Figure 1). The rate of uninsured children ticked upward from the historic low of 4.7 percent in 2016 to 5 percent in 2017 (Figure 2). Both of these changes were large enough to be statistically significant. Also notable was the lack of any statistically significant progress on children’s coverage in any state across the country in 2017, with the exception of the District of Columbia. Nine states saw statistically significant increases in the rate of uninsured children in 2017. In order of magnitude of change, they are: South Dakota, Utah, Texas, Georgia, South Carolina, Florida, Ohio, Tennessee, and Massachusetts. No state saw its number of uninsured children decline, except for DC.

Population projection is essential to governments, businesses, and research communities for many purposes. Although projection performance is often evaluated, we know very little about what factors affect projection accuracy. It is important to understand these factors in order to utilise the projections knowledgeably. This study fills this gap in the literature by comprehensively investigating the possible factors associated with population projection accuracy in 2010 for the continental U.S. counties. The results indicate that the counties whose populations are more predictable tend to be desirable places—places with abundant employment opportunities, reliable public transportation infrastructure, easy access to work, and/or high land development potential; their neighbouring counties tend to have a well-educated population and a higher income level. Also, projection accuracy is highly spatially associated. The findings provide important insights for population projection users to understand the characteristics of counties and their neighbouring counties associated with their projection accuracy.

In this paper, we study the effects of immigration on natives’ marriage, fertility, and family formation across US cities between 1910 and 1930. Instrumenting immigrants’ location decision by interacting pre-existing ethnic settlements with aggregate migration flows, we find that immigration raised marriage rates, the probability of having children, and the propensity to leave the parental house for young native men and women. We show that these effects were driven by the large and positive impact of immigration on native men’s employment and occupational standing, which increased the supply of “marriageable men”. We also explore alternative mechanisms - changes in sex ratios, natives’ cultural responses, and displacement effects of immigrants on female employment - and provide evidence that none of them can account for a quantitatively relevant fraction of our results.

Recent trends in income segregation in metropolitan regions show that, after a decline in the 1990s, there was an increase in 2000–2010 that reinforced concerns about the overall growth in U.S. income inequality since the 1970s. Yet the evidence may be systematically biased to exacerbate the upward trend because the effective sample for the American Community Survey (ACS) is much smaller than it was for the 2000 census to which it is being compared. Apparent changes in disparities across census tracts may result partly from a higher level of sampling variation and bias due to the smaller sample. This study uses 100% microdata from the 1940 census to simulate the impact of different sampling rates and applies those approaches to publicly available data for 2000 and 2007–11. The reduction in sample sizes associated with the ACS appears to exaggerate the evidence for increasing income segregation for all measures tested here.

This extensive database project provides demographic data for workers, both in terms of where they live and where they work, for 39 U.S. Metropolitan Statistical Areas (MSAs). Planners and researchers can use this database to assess the extent to which transit stations and station areas are associated with economic and demographic change, and to forecast similar magnitudes of change through proposed new or expanded transit systems. Specific data elements include job numbers based on job sector, earnings, race, education, sex, and distance of census blocks to transit separated by mode type. Data were extracted as part of a larger project that examines the impact of transit on a large number of societal factors, including economic development and demographic dynamics

Distributed solar photovoltaic (DPV) systems that generate energy in behind-the-meter applications for residential, commercial, and other end-use sectors are a growing—and potentially disruptive—development in the U.S. power system. While less than 1% of all electricity generation in the United States came from DPV systems in 2016 (EIA 20171 ), this technology has experienced rapid growth in recent years and, as of the end of 2017, over 1.6 million DPV systems had been installed (GTM 2017). Given this, projecting distributed solar deployment is increasingly pertinent—yet remains highly uncertain. The traditional U.S. power system has historically consisted of large, centralized baseload generators connected to demand centers via a hub-and-spoke network of synchronized voltage transmission and distribution lines. Utilities have also historically financed most infrastructure with charges apportioned among customers on a volumetric basis. DPV systems disrupt both prior foundations of the U.S. electric power system. Not only are DPV systems typically low capacity, but their generation directly offsets on-site electricity consumption or is exported to the grid in the case of excess, thereby reducing electricity sales. Recent declines in DPV costs has prompted questions regarding the conditions in which consumers might find electricity sourced from DPV more economically compelling than grid-sourced electricity. Sometimes termed “grid parity”, this phenomenon could accelerate DPV adoption. Clarity about whether DPV might achieve grid parity, the timing and extent of this transition, and future levels of DPV deployment are important factors to consider for power system operational conditions, engineering and financial risk, and long-term planning of the U.S. electric grid.

This paper studies the eect of home-owners' migration costs on unemployment in an economy where workers move both for work-and non-work-related reasons. To this end, a search model with heterogeneous locations is developed and calibrated to the US economy. Both the employment and unemployment exit rates are endogenous. Migration costs imply that home-owners quit their jobs less often than renters and nd jobs at a higher rate. Consistent with the empirical evidence, the model predicts that home-owners have a lower unemployment rate than renters. seminar participants at the ASSET. Financial support from the Departamento de Educación, Política Lingüística y Cultura del Gobierno Vasco (IT869-13) and the Ministerio de Ciencia e Innovación (BES-2008-004549) are gratefully acknowledged.

Part-time MBA programs, designed specifically for the busy, early-to-mid-career working professional, are for many Americans what first comes to mind at the mention of "going to business school." In recent years the overall demand for part-time MBA programs in the United States appears to have stagnated. Since 2009, each year most programs have reported either down or flat application volumes. Through a wide-ranging examination of Graduate Management Admission Council® (GMAC®) data, this paper explores this apparent stagnation; highlights shifting candidate needs and approaches some programs have taken to innovate; evaluates the current part-time MBA value proposition; and identifies opportunities and strategies for US part-time MBA programs to stay relevant and plan for their programs' sustainable futures.

In 1950, 80% of American newspapers were owned by independent families. By 1980, only 30% of American newspapers were owned by independent families. Between 1950 and 1980, the majority of independent newspapers were purchased by newspaper chains, firms owning several newspapers. I use newly collected data to study the effects of transitions from independent to chain ownership on news content. I find that while chain transitions have little effect on news content, chain transitions lead to a larger newspaper by approximately 4.2 pages, but approximately 15% fewer words per page, indicating that chains are able to finance a new printing technology and add more advertising to the newspaper. Additionally, I find that transitions to chain ownership lead to a 12% increase in the share of advertisements which are for chain or publicly-owned businesses, as opposed to local businesses. 1 * The most recent version is available here. 1 I thank my dissertation committee-Joel Mokyr, Joseph Ferrie, and Ben Jones-for their support on this project. Additionally, many thanks to the Economic History Association and the Balzan foundation for supporting this project.

Urban historians and historical geographers have a long tradition of mapping demographic data to study residential patterns, the assimilation or segregation of immigrants and minorities, and processes of neighborhood change, despite the difficulty of working from printed or microfilm copies of city directories and census manuscripts and drawing maps by hand. Dubois’ study of Philadelphia was one of the earliest research of this type, including a detailed survey of the predominantly black Seventh Ward to depict the patchwork of poorer and more well-to-do blocks [1]. The early Chicago School sociologists used census data and data from many other sources to map the social characteristics of Chicago neighborhoods in the 1920s and 1930s. Radford (1976) plotted locations of black and white residents in 1880 in Charleston, distinguishing between those residing on streets, in backyards, and on alleys [2]. Rabinowitz (1978) mapped the streets block by block in four Southern cities to show the degree of racial segregation [3]. Groves and Muller (1975) similarly studied black residential concentrations in post-bellum Washington, DC [4]. Others have focused on white ethnic residential patterns in cities such as New York [5] and Detroit [6].

The scope of linguistic demography as I envision it is suggested by the table of contents of this book. Specifically, I deal with such topics as the sources and quality of the data on, and methods of, linguistic demography; the concept of ethnicity and its relation to language, religion, and race; the history of inquiries on language use in the United States; the language situation in the United States and around the world, including the role of bilingualism; the families of languages and national and official languages; the factors determining the acquisition of a host country’s national language and their measurement; the role of ethnolinguistic differences in group conflict and in national independence movements; and variations in language usage according to various demographic and socioeconomic characteristics, including social networks. Separate attention is devoted to the language situation among indigenous and preliterate populations, sensory-impaired and mentally impaired populations, and religious communities. Throughout the book literacy has been incorporated as a topic of intrinsic relevance to the study of linguistic demography.

Alabama’s unemployment rate has steadily decreased since 2011. Yet, compared with other states, Alabama fares poorly on standard measures of economic growth, and economic output (measured by gross domestic product, or GDP) has not kept pace with the national average. For these reasons, Alabama tends to rank among the bottom 20 states on comparative analyses of economic activity. Projections indicate that the state will continue to gain jobs and grow at a moderate pace. Alabama’s slow recovery is expected to continue, driven by the state’s auto manufacturing and wood manufacturing, leisure and hospitality, and health-care industries. In addition to experiencing tepid growth, Alabama’s growth has also been unequal, deepening economic divides by race and gender. Key indications that Alabama’s growth has been unequal are described below.

Background Pediatric asthma is a common chronic condition that can be exacerbated by environmental exposures, and unconventional natural gas development (UNGD) has been associated with decreased community air quality. This study aims to quantify the association between UNGD and pediatric asthma hospitalizations. Methods We compare pediatric asthma hospitalizations among zip codes with and without exposure to UNGD between 2003 and 2014 using a difference-in-differences panel analysis. Our UNGD exposure metrics include cumulative and contemporaneous drilling as well as reported air emissions by site. Results We observed consistently elevated odds of hospitalizations in the top tertile of pediatric patients exposed to unconventional drilling compared with their unexposed peers. During the same quarter a well was drilled, we find a 25% increase (95% CI: 1.07, 1.47) in the odds of being hospitalized for asthma. Ever-establishment of an UNGD well within a zip code was associated with a 1.19 (95% CI: 1.04, 1.36) increased odds of a pediatric asthma hospitalization. Our results further demonstrate that increasing specific air emissions from UNGD sites are associated with increased risks of pediatric asthma hospitalizations (e.g. 2,2,4-trimethylpentane, formaldehyde, x-hexane). These results hold across multiple age groups and sensitivity analyses. Conclusions Community-level UNGD exposure metrics were associated with increased odds of pediatric asthma-related hospitalization among young children and adolescents. This study provides evidence that additional regulations may be necessary to protect children's respiratory health from UNGD activities.

This paper analyzes differences in the return on education between non-Hispanic whites and four groups of Hispanics: Puerto Ricans, Mexicans, Cubans, and other Latin Americans. For Mexi-cans, Cubans, and other Latin Americans, we also distinguish between native-born in the U.S. and foreign-born immigrants. We use data from the American Community Survey 2008-2013 to estimate the differences in the return on education by comparing income relative to educational attainment across ethnic and immigrant groups. The analyses account for age, education, English skills, citizenship status, union status, year, metro area residence, and region of residence, as well as time spent in the U.S. for the foreign-born. We find that the returns on schooling are lower for Hispanics relative to NH whites, but that there is also a gap in earnings between U.S. and foreign-born Hispanics. The loss of wages experienced by Hispanic immigrants is greater at higher levels of education, and for women.