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Downscaled climate projections need to be linked to downscaled projections of population and economic growth to fully develop implications for land, natural resources, and ecosystems for future scenarios. We develop an empirical spatiotemporal approach for jointly projecting population and income at the county scale in the United States that is consistent with neoclassical economic growth theory and overlapping labor markets and that accounts for labor migration and spatial spillovers. Downscaled projections generated for the five Shared Socioeconomic Pathways used to support global scenario analysis generally show growth focused around relatively few centers especially in the southeast and western regions, with some areas in the Midwest and northeast experiencing population declines. Results are consistent with economic growth theory and with historical trends in population change and convergence of per capita personal income across US counties. [ABSTRACT FROM AUTHOR]

Coastal risks are increasing from both development and climate change. Interest is growing in the protective role that coastal nature-based measures (or green infrastructure), such as reefs and wetlands, can play in adapting to these risks. However, a lack of quantitative information on their relative costs and benefits is one principal factor limiting their use more broadly. Here, we apply a quantitative risk assessment framework to assess coastal flood risk (from climate change and economic exposure growth) across the United States Gulf of Mexico coast to compare the cost effectiveness of different adaptation measures. These include nature-based (e.g. oyster reef restoration), structural or grey (e.g., seawalls) and policy measures (e.g. home elevation). We first find that coastal development will be a critical driver of risk, particularly for major disasters, but climate change will cause more recurrent losses through changes in storms and relative sea level rise. By 2030, flooding will cost $134–176.6 billion (for different economic growth scenarios), but as the effects of climate change, land subsidence and concentration of assets in the coastal zone increase, annualized risk will more than double by 2050 with respect to 2030. However, from the portfolio we studied, the set of cost-effective adaptation measures (with benefit to cost ratios above 1) could prevent up to $57–101 billion in losses, which represents 42.8–57.2% of the total risk. Nature-based adaptation options could avert more than $50 billion of these costs, and do so cost effectively with average benefit to cost ratios above 3.5. Wetland and oyster reef restoration are found to be particularly cost-effective. This study demonstrates that the cost effectiveness of nature-based, grey and policy measures can be compared quantitatively with one another, and that the cost effectiveness of adaptation becomes more attractive as climate change and coastal development intensifies in the future. It also shows that investments in nature-based adaptation could meet multiple objectives for environmental restoration, adaptation and flood risk reduction. [ABSTRACT FROM AUTHOR]

Background: Since the site of human subjects research has public health, regulatory, ethical, economic, and social implications, we sought to determine the global distribution and migration of clinical research using an open-access trial registry. Methods: We obtained individual clinical trial data including location of trial sites, dates of operation, funding source (United States government, pharmaceutical industry, or organization), and clinical study phase (1, 1/2, 2, 2/3, or 3) from ClinicalTrials.gov. We used the World Bank's classification of each country's economic development status ["High Income and a Member of the Organization for Economic Co-operation and Development (OECD)", "High Income and Non-Member of the OECD", "Upper-Middle Income", "Lower-Middle Income", or "Low Income"] and United Nations Populations Division data for country-specific population estimates. We analyzed data from calendar year 2006 through 2012 by number of clinical trial sites, cumulative trial site-years, trial density (trial site-years/106 population), and annual growth rate (%) for each country, and by development category, funding source, and clinical study phase. Results: Over a 7-year period, 89,647 clinical trials operated 784,585 trial sites in 175 countries, contributing 2,443,850 trial site-years. Among those, 652,200 trial sites (83%) were in 25 high-income OECD countries, while 37,195 sites (5%) were in 91 lower-middle or low-income countries. Trial density (trial site-years/106 population) was 540 in the United States, 202 among other high-income OECD countries (excluding the United States), 81 among high-income non-OECD countries, 41 among upper-middle income countries, 5 among lower-middle income countries, and 2 among low-income countries. Annual compound growth rate was positive (ranging from 0.8% among low-income countries to 14.7% among lower-middle income countries) among all economic groups, except the United States (-0.5%). Overall, 29,191 trials (33%) were funded by industry, 4,059 (5%) were funded by the United States government, and 56,397 (63%) were funded by organizations. Countries with emerging economies (low- and middle-income) operated 19% of phase 3 trial sites, as compared to only 6% of phase 1 trial sites. Conclusion: Human clinical research remains concentrated in high-income countries, but operational clinical trial sites, particularly for phase 3 trials, may be migrating to low- and middle-income countries with emerging economies. [ABSTRACT FROM AUTHOR]

We propose a diffusion process to describe the global dynamic evolution of credit operations at a national level given observed operations at a subnational level in a sovereign country. Empirical analysis with a unique dataset from Brazilian federate constituents supports the conclusions. Despite the heterogeneity observed in credit operations at a subnational level, the aggregated dynamics at a national level were accurately described by the proposed model. Results may guide management of public finances, particularly debt manager authorities in charge of reaching surplus targets. [ABSTRACT FROM AUTHOR]

In this paper, we extend some usual techniques of classification resulting from a large-scale data-mining and network approach. This new technology, which in particular is designed to be suitable to big data, is used to construct an open consolidated database from raw data on 4 million patents taken from the US patent office from 1976 onward. To build the pattern network, not only do we look at each patent title, but we also examine their full abstract and extract the relevant keywords accordingly. We refer to this classification as semantic approach in contrast with the more common technological approach which consists in taking the topology when considering US Patent office technological classes. Moreover, we document that both approaches have highly different topological measures and strong statistical evidence that they feature a different model. This suggests that our method is a useful tool to extract endogenous information. [ABSTRACT FROM AUTHOR]