Government funding accounts for a large proportion of conservation and environmental improvements, and is often the result of citizen votes on state ballot measures. A key concern surrounding public investments in the environment is whether that funding serves lower-income communities, which are often the communities of greatest need. We applied three statistical methods to analyze the spatial distribution of conservation funding derived from California’s Proposition 84, which distributed nearly $4 billion across California between 2006 and 2015. First, we used hurdle models to ask if income, population density, urban coverage, or pollution could explain receipt of grants or magnitude of funding. Second, we compared the income levels of funded and unfunded communities for each chapter of the proposition. Finally, we examine two sections of the proposition that were intended to fund parks around the state and compare the attributes of funded and unfunded communities. Proposition 84 offers lessons for environmental legislation and future research. While there were general tendencies for more funding to flow to poor areas and areas with pollution problems, the language in Proposition 84 as a whole was vague with respect to the funding of disadvantaged areas, and as a result the targeting of these areas overall was at best modest. However, when enabling legislation (AB 31) defined specific “metrics of disadvantage” that had to be met by communities to receive funds from some sections of Proposition 84, the funds did flow much more selectively to poorer communities. This suggests that future ballot measures should be very explicit in their language if they want to promote equity in conservation investments, and that future research should investigate the extent to which technical workshops and outreach could further increase the number of funded grant proposals from low-income communities.

Current remote patient monitoring (RPM) systems are fully reliant on the Internet. However, complete reliance on Internet connectivity is impractical in low resource and remote environments where modern infrastructure is often lacking, power outages are frequent, and/or network connectivity is sparse (e.g. rural communities, mountainous regions of Ap-palachia, American Indian reservations, developing countries, and natural disaster situations). This paper proposes supplementing intermittent Internet with opportunistic communication to leverage the social behaviors of patients, caregivers, and society members to facilitate out-of-range monitoring of patients via Bluetooth 5 during intermittent network connectivity. The architecture is evaluated using U.S. Census Bureau, the National Cancer Institute's, and IPUMS ATUS sample data for Owingsville, KY, and is compared against a delay tolerant RPM case that is completely disconnected from the Internet. The findings show that with only 0.30 rural population participation, the architecture can deliver 0.94 of non-emergency medical information with at least half of the information having a latency of ∼5 hours. In addition, the paper provides insights on how supplemented networks can be used in real-world rural RPM (RRPM) systems for different domain applications. Index Terms-rural remote patient monitoring, mHealth, delay tolerant networks, mobile ad hoc networks, device-to-device, opportunistic communication, bluetooth

This paper explores the inequality implications of the evolution of occupations. It develops an equilibrium model of occupational choice, based on worker’s comparative advantage, in which jobs are bundles of tasks that a worker must perform. We bring this model to measures on the changing task contents of within occupations, and we find that shifts in the relative demand for tasks account for a large fraction of the increase in 90-10 earnings inequality observed over our sample period.

This chartbook illustrates the characteristics of the county’s 65-plus population in 2015*, and changes that have occurred since 2000. It also includes population characteristics, such as education, income level, and marital status, that are shown to be associated with the need for long-term services and supports. There are charts that compare the older population of the county to the state as a whole, and charts that illustrate change over time within the county. The data presented in this chartbook are intended to assist planners, decisions makers, and service providers to understand the growth in numbers and proportion of older adults, particularly those who will likely need assistance. An online interactive data center is available for you to define your own topic, county, and population of interest to see current figures and change over time. Please visit www.ohio-population.org.

Research suggests increased reliance upon natural resource development will lead to decreases in local income, increases in inequality, and elevated poverty in the United States of America. Natural resource development generally takes two forms, extractive (e.g. oil and gas, mining, timber) and non-extractive (e.g. tourism, recreation, real estate). However, research has largely focused on extractive development. This paper expands literature by demonstrating the non-linear impacts both extractive and non-extractive natural resource development—operationalized as county-level employment share—had on per capita income, local income inequality, and poverty in the rural counties of the contiguous United States from 2000 to 2015 using spatial Durbin fixed effects models. Findings suggest dependence upon neither form of natural resource development resulted in increased economic prosperity in rural America from 2000 to 2015, with the impacts of nonextractive development being far more negative than hypotheized.

A monetized tornado benefit model is developed for arbitrary weather radar network configurations. Geospatial regression analyses indicate that improvement of two key radar parameters—fraction of vertical space observed and cross-range horizontal resolution—leads to better tornado warning performance as characterized by tornado detection probability and false-alarm ratio. Previous experimental results showing faster volume scan rates yielding greater warning performance are also incorporated into the model. Enhanced tornado warning performance, in turn, reduces casualty rates. In addition, lower false-alarm ratios save costs by cutting down on work and personal time lost while taking shelter. The model is run on the existing contiguous U.S. weather radar network as well as hypothetical future configurations. Results show that the current radars provide a tornado-based benefit of ~$490 million (M) yr −1 . The remaining benefit pool is about $260M yr −1 , split roughly evenly between coverage- and rapid-scanning-related gaps.

The current trend towards outsourcing data storage and management to the cloud has largely been driven by the perceived simplicity and cost-effectiveness. Encrypting sensitive data before outsourcing preserves data privacy, but poses an obstacle to delegate search capabilities to the server. Symmetric searchable encryption (SSE) addresses this issue by allowing an untrusted server to answer queries over encrypted data while protecting the confidentiality of plaintext data and queries. The core of SSE is to meet three design goals, including a strong security guarantee, an efficient search performance and supporting rich types of queries. Usually, an SSE scheme needs to trade in security or efficiency for supporting more expressive queries. In this thesis, we study how to strike trade-offs among these design goals. As a motivation of strong security notions, we first study the potential risks of constructing SSE schemes based on an ad hoc security notion for the purpose of efficiently performing more expressive queries. We demonstrate several previous unknown security risks of widely used ad hoc secure SSE schemes to show that ad hoc security notion leaves room for unpredicted information leakage. To address this problem, our next two contributions focus on constructing practical SSE schemes . . .

This paper investigates post-2000 trends in homeownership rates in the US by immigrant status, race, and ethnicity. Homeownership rates for most groups examined rose during the housing boom of the early and mid-2000s but fell during and after the housing bust. By 2015 homeownership rates had fallen below year 2000 levels for most groups but not all. In particular, some Asian immigrant groups experienced sizable gains in overall homeownership rates and in regression-adjusted differences relative to white non-Hispanic natives. Some other immigrant and minority groups also made gains relative to white non- Hispanic natives. We document and discuss these trends.

This paper examines the importance of the occupational sorting of individuals in same-sex couples in explaining the economic position of lesbian women and gay men beyond controlling for occupation in the estimation of their respective wage gaps, as usually done in the literature. The analysis reveals that the distribution of partnered gay men across occupations brings them a monetary gain, with respect to the average wage of coupled workers, whereas the occupational sorting of partnered lesbian women only allows them to depart from the large losses that straight partnered women have. The results show that when controlling for educational achievements, immigration profile, racial composition, and age structure, the gain for gay men associated with their occupational sorting shrinks substantially. Moreover, the small gain that lesbian women derive from their distribution across occupations turns into an earning disadvantage when one controls for characteristics. This leaves them with a loss, with respect to the average wage of coupled workers, that is not too different from to the one partnered straight women have. It is their higher educational attainments and, to a lower extent, their lower immigration profile that protects workers in same-sex couples, revealing that gay men do not enjoy the privilege of straight partnered men and that lesbian women are not free from the mark of gender.

Over six years have now passed since the Supreme Court’s landmark decision which upheld the core provisions of the Affordable Care Act (ACA) but left the decision on Medicaid expansion to the states. Despite the generous Federal match rate structure (full federal funding for 3 years, gradually declining to 90% in 2020 and beyond) Alabama was one of 26 states which elected not to participate in Medicaid expansion prior to its inception in January 2014. Since that time, 9 additional states have expanded their programs. Louisiana Democratic Governor John Bel Edwards ran heavily on the issue -- and won -- expanding Medicaid by executive order on his second day of office in 2016. The Republican controlled Virginia legislature voted to expand Medicaid in April 2018, joining a growing list of states that expanded their programs with Republican support. The 2018 midterm elections provided further evidence of broad public support for Medicaid expansion, as voters in three reliably conservative states - - Idaho, Utah and Nebraska – approved ballot measures supporting expansion. Alabama is now one of just 14 states that have taken no action on Medicaid expansion under the ACA1 . In November 2012 -- over a full year prior to the implementation of expansion – my . . .

Affordable housing is an under researched area of residential attainment despite is importance and potentially consequences of households spending too much on housing—such as forced moves and financial instability. This study analyzes disparities in access to affordable housing between white, black and Hispanic households using 2005-2017 American Community Survey Microdata. Results show there are significant gaps between whites and the other groups regarding their access to affordable housing. Differential returns on socioeconomic status are also present, with Hispanics receiving minimal returns on education. Hispanic foreign-born headed uniquely households have greater access to affordable housing than their native-born headed households counterparts. When accounting for county-level ethnoracial composition there is mixed evidence regarding if households of any group are more likely to live in affordable housing if they live in a county with a high proportion of coethnic residents.

This study examines the incidence and impact of occupational licensing on immigrants using two sources of data: the Current Population Survey and the Survey of Income and Program Participation. We find that immigrants are much less likely to have a license than similar natives, and that this gap is largest for non-naturalized immigrants, men, and for workers in the highest education level. The licensing rate increases with years since migration and shows large variation by immigrant region of origin. A lack of English proficiency reduces the probability an immigrant has a license. The wage premiums to having a license are much larger for women than men but seem to be the same for natives and immigrants after controlling for English language ability.

Aedes albopictus is a viable vector for several infectious diseases such as Zika, West Nile, Dengue viruses and others. Originating from Asia, this invasive species is rapidly expanding into North American temperate areas and urbanized places causing major concerns for public health. Previous analyses show that warm temperatures and high humidity during the mosquito season are ideal conditions for A. albopictus development, while its distribution is correlated with population density. To better understand A. albopictus expansion into urban places it is important to consider the role of both environmental and neighborhood factors. The present study aims to assess the relative importance of both environmental variables and neighborhood factors in the prediction of A. albopictus’ presence in Southeast Pennsylvania using MaxEnt (version 3.4.1) machine-learning algorithm. Three models are developed that include: (1) exclusively environmental variables, (2) exclusively neighborhood factors, and (3) a combination of environmental variables and neighborhood factors. Outcomes from the three models are compared in terms of variable importance, accuracy, and the spatial distribution of predicted A. albopictus’ presence. All three models predicted the presence of A. albopictus in urban centers, however, each to a different spatial extent. The combined model resulted in the highest accuracy (74.7%) compared to the model with only environmental variables (73.5%) and to the model with only neighborhood factors (72.1%) separately. Although the combined model does not essentially increase the accuracy in the prediction, the spatial patterns of mosquito distribution are different when compared to environmental or neighborhood factors alone. Environmental variables help to explain conditions associated with mosquitoes in suburban/rural areas, while neighborhood factors summarize the local conditions that can also impact mosquito habitats in predominantly urban places. Overall, the present study shows that MaxEnt is suitable for integrating neighborhood factors associated with mosquito presence that can complement and improve species distribution modeling.

A massive shift is taking place in the makeup of the world population, and societies are already struggling to cope. By 2030, more people worldwide will be over the age of 60 than under 10.1 Realizing the benefits of an older population—while addressing the difficulties and realities—will be one of the great human challenges of the 21st century. Cities are ground zero for the demographic shift—eight in 10 US residents 65 and older already live in metropolitan areas,2 underscoring the need to view population aging with the same sense of urgency as climate change, public safety, homelessness, or any major urban priority. Healthy aging means living a long, productive, meaningful life and enjoying a high quality of life.3 Research demonstrates that older adults who adopt healthy behaviors, use preventive health services, and are involved with their family, friends, and communities are healthier and more independent...

Reproduction between individuals from different ancestral populations creates genetically admixed offspring. Admixture can have positive and negative impacts on individual health, feeding back to population health. Historical and forced migrations, and recent mobility, have brought formerly disparate populations of humans together. Here we sought to better understand how temporal changes in genetic admixture influence levels of heterozygosity and health outcomes. We evaluated variation in ancestry over 100 birth years in 35,842 individuals from a genetic database linked to health records in a population in the Southeastern United States. Analysis of 2,678 ancestrally informative markers revealed increased admixture and heterozygosity for all clinically-defined race groups since 1990. Most groups also exhibited increasing long-range linkage disequilibrium over time. A phenome-wide association study of clinical outcomes detected protective associations with female reproductive disorders and increased risk for diseases with links to autoimmunity dysfunction. These mixed effects have important ramifications for human health.

Across OECD countries, girls and young women often outperform their peers in educational attainment, and in testing achievements in almost all educational levels. This bachelor thesis investigates driving forces behind the phenomenon including variation between OECD member states and field of study. Since the issue of gender equality has arisen, the phenomenon of gender gaps in general has become increasingly relevant. Gender gaps in education and income are strong indicators for equality in a country’s society, which in turn delivers greater growth and inclusiveness. Although there are already several empirical studies about the growing gender gap in education in OECD member states as well as in other countries around the globe, it has been little empirical research done about the driving forces behind the phenomenon. The findings of this current thesis are in line with the few existing approaches. Mostly external, societal and economic factors were found to be driving forces behind the reversal of the gender gap in education and any variation across OECD countries. Whereas the interaction of external and internal factors explains why there is any female educational advantage possible at all. Against all odds, performance was not found to be responsible for gender variation in the field of study, rather motivation accounts for a bulk of gender differences in certain specialties.

I study the impact of transportation on health in the rural United States, 1820-1847. Measuring health by average stature, I find that greater transportation linkage, as measured by market access, in a cohort's county-year of birth had an adverse impact on its health. A one-standard-deviation increase in market access reduced average stature by 0.14 inches, and rising market access over the study period can explain 37 percent of the contemporaneous decline in average stature, known as the Antebellum Puzzle. I find evidence that transportation affected health by increasing population density, leading to a worse epidemiological environment.

Recently, local differential privacy (LDP), as a strong and practical notion, has been applied to deal with privacy issues in data collection. However, existing LDP-based strategies mainly focus on utility optimization at a single privacy level while ignoring various privacy preferences of data providers and multilevel privacy demands for statistics. In this paper, we for the first time propose a framework to optimize the utility of histogram estimation with these two privacy requirements. To clarify the goal of privacy protection, we personalize the traditional definition of LDP. We design two independent approaches to minimize the utility loss: Advanced Combination, which composes multilevel results for utility optimisation, and Data Recycle with Personalized Privacy, which enlarges sample size for an estimation. We demonstrate their effectiveness on privacy and utility, respectively. Moreover, we embed these approaches within a Recycle and Combination Framework and prove that the framework stably achieves the optimal utility by quantifying its error bounds. On real-world datasets, our approaches are experimentally validated and remarkably outperform baseline methods.

This paper considers equilibrium two-sided search with ex-ante heterogeneous agents, vectors of attributes, and idiosyncratic match draws. The analysis applies to a large class of models, from the non-transferable utility case to the collective household model with bargaining, for which transferable utility is a special case. The approach is powerful for it identifies a simple algorithm which, in our numerical application, is found to rapidly converge to equilibrium. Our application explores the impact of equal opportunities for women in the labor market on female match incentives and the timing of marriage.

We focus on a small but growing segment of the U.S. population, those who identify as Chinese, Japanese and Korean (CJK), and compare CJK fertility to other race/ethnic groups in the United States. CJK women in the U.S. exhibit a distinct, pervasive, and persistent pattern of late and low fertility with nearly all births occurring within marriage; this pattern displays a strong parallel to their counterparts in their countries of origin. To accompany this description, we offer a perspective on fertility difference that has broad applicability and that does not consistently predict that differences will disappear/remain. This discussion unites the literature on assimilation, segmented assimilation and pluralistic outcomes and processes. We also discuss the possible implications of these findings for country level policies to increase fertility. Most generally, these discussions are a corrective to demographer’s penchant for predicting secular change and convergence.