140 research outputs found

    Do labor market networks have an important spatial dimension?

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    We test for evidence of spatial, residence-based labor market networks. Turnover is lower for workers more connected to their neighbors generally and more connected to neighbors of the same race or ethnic group. Both results are consistent with networks producing better job matches, while the latter could also reflect preferences for working with neighbors of the same race or ethnicity. For earnings, we find a robust positive effect of the overall residence-based network measure, whereas we usually find a negative effect of the same-group measure, suggesting that the overall network measure reflects productivity-enhancing positive network effects, while the same-group measure may capture a non-wage amenity

    Social Capital Determinants and Labor Market Networks

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    We explore the links between determinants of social capital and labor market networks at the neighborhood level. We harness rich data taken from multiple sources, including matched employer-employee data with which we measure the strength of labor market networks, data on neighborhood homogeneity that has previously been tied to social capital, and new data – not previously used in the study of social capital – on the number and location of non-profit sector establishments at the neighborhood level. We use a machine learning algorithm to identify the potential determinants of social capital that best predict neighborhood-level variation in labor market networks. We find evidence suggesting that smaller and less centralized schools, and schools with fewer poor students, foster social capital that builds local labor market networks, as does a larger Republican vote share. The presence of establishments in a number of non-profit-oriented industries are identified as predictive of strong labor market networks, likely because they either provide public goods or facilitate social contacts. These industries include, for example, churches and other religious institutions, fire and rescue services including volunteer fire departments, country clubs and golf courses, labor unions, chamber music groups, hobby clubs, and schools

    The Conservation Reserve Program: Economic Implications for Rural America

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    This report estimates the impact that high levels of enrollment in the Conservation Reserve Program (CRP) have had on economic trends in rural counties since the program's inception in 1985 until today. The results of a growth model and quasi-experimental control group analysis indicate no discernible impact by the CRP on aggregate county population trends. Aggregate employment growth may have slowed in some high-CRP counties, but only temporarily. High levels of CRP enrollment appear to have affected farm-related businesses over the long run, but growth in the number of other nonfarm businesses moderated CRP's impact on total employment. If CRP contracts had ended in 2001, simulation models suggest that roughly 51 percent of CRP land would have returned to crop production, and that spending on outdoor recreation would decrease by as much as $300 million per year in rural areas. The resulting impacts on employment and income vary widely among regions having similar CRP enrollments, depending upon local economic conditions.Community/Rural/Urban Development, Land Economics/Use,

    Science in the Cloud: Accelerating Discovery in the 21st Century

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    A Switch in Hepatic Cortisol Metabolism across the Spectrum of Non Alcoholic Fatty Liver Disease

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    Context: Non alcoholic fatty liver disease (NAFLD) is the hepatic manifestation of the metabolic syndrome. NAFLD represents a spectrum of liver disease ranging from reversible hepatic steatosis, to non alcoholic steato-hepatitis (NASH) and cirrhosis. The potential role of glucocorticoids (GC) in the pathogenesis of NAFLD is highlighted in patients with GC excess, Cushing's syndrome, who develop central adiposity, insulin resistance and in 20% of cases, NAFLD. Although in most cases of NAFLD, circulating cortisol levels are normal, hepatic cortisol availability is controlled by enzymes that regenerate cortisol (F) from inactive cortisone (E) (11β-hydroxysteroid dehydrogenase type 1, 11β-HSD1), or inactivate cortisol through A-ring metabolism (5α- and 5β-reductase, 5αR and 5βR). Objective and Methods: In vitro studies defined 11β-HSD1 expression in normal and NASH liver samples. We then characterised hepatic cortisol metabolism in 16 patients with histologically proven NAFLD compared to 32 obese controls using gas chromatographic analysis of 24 hour urine collection and plasma cortisol generation profile following oral cortisone. Results: In patients with steatosis 5αR activity was increased, with a decrease in hepatic 11β-HSD1 activity. Total cortisol metabolites were increased in this group consistent with increased GC production rate. In contrast, in patients with NASH, 11β-HSD1 activity was increased both in comparison to patients with steatosis, and controls. Endorsing these findings, 11β-HSD1 mRNA and immunostaining was markedly increased in NASH patients in peri septal hepatocytes and within CD68 positive macrophages within inflamed cirrhotic septa. Conclusion: Patients with hepatic steatosis have increased clearance and decreased hepatic regeneration of cortisol and we propose that this may represent a protective mechanism to decrease local GC availability to preserve hepatic metabolic phenotype. With progression to NASH, increased 11β-HSD1 activity and consequent cortisol regeneration may serve to limit hepatic inflammation

    BioSimulators: a central registry of simulation engines and services for recommending specific tools

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    Computational models have great potential to accelerate bioscience, bioengineering, and medicine. However, it remains challenging to reproduce and reuse simulations, in part, because the numerous formats and methods for simulating various subsystems and scales remain siloed by different software tools. For example, each tool must be executed through a distinct interface. To help investigators find and use simulation tools, we developed BioSimulators (https://biosimulators.org), a central registry of the capabilities of simulation tools and consistent Python, command-line and containerized interfaces to each version of each tool. The foundation of BioSimulators is standards, such as CellML, SBML, SED-ML and the COMBINE archive format, and validation tools for simulation projects and simulation tools that ensure these standards are used consistently. To help modelers find tools for particular projects, we have also used the registry to develop recommendation services. We anticipate that BioSimulators will help modelers exchange, reproduce, and combine simulations
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