2,369 research outputs found

    Computer simulation of the primary recoil spectra and damage cross section of Fe₃Al using ENDF/B II data

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    A computer program, using Evaluated Nuclear Data File (ENDF/B II) information, was used to develop energy-exchange kernels which delineate the energy transfer probabilities between neutrons and Fe3Al lattice atoms. The kernels combine all available information on elastic and inelastic scattering contained in the ENDF/B II data. The computer program used to generate the primary recoil spectra is SAKI, a modified version of RICE (1). SAKI is designed to calculate energy-exchange probabilities in any binary alloy as well as damage cross sections and optimum cutoff energies for use in comparing displacement effects in different reactor spectra. --Abstract, page ii

    Utah State University Botanical Center Stream Master Plan

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    The Utah State University Botanical Center Stream Master Plan is a design to assist Utah State University Botanical Center (USUBC) administration in fulfilling their goals of community outreach and education, implementing sustainable practices and creating aesthetically beautiful areas for public enjoyment. These goals are met through updating the USUBC master plan to account for the newly built man-made stream as well as other future buildings. Trails, overlooks and information nodes are part of the new master plan. The planting plan includes representations of six natural plant communities found in Northern Utah. Additionally, the stream design improves the water quality of USUBC ponds on site. All of these designs will contribute to USUBC goals. The Utah State University Botanical Center Master Plan and Planting Plan is a plan B thesis project

    The Impact of Climate Change on Marine Recreational Fishing with Implications for the Social Cost of Carbon

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    We estimate the effects of temperature and precipitation on marine recreational fishing days over a 20 year time period. The data are from the National Survey of Fishing, Hunting and Wildlife-Associated Recreation. Our results suggest that temperature and precipitation have positive effects on marine recreational fishing days in the United States. To determine changes in economic value we simulate the effects of climate change on fishing days with changes in U.S. average temperature and precipitation developed from climate models. We use benefit transfer to estimate the value of fishing days. Considering a 4.5F temperature change and a 7% precipitation change, we find that marine recreational fishing days will increase by 27% and the welfare change is $2.5 billion. This suggests that impacts of climate change on marine recreational fishing could have implications for accurate estimation of the social cost of carbon

    Labor Relations for Multinational Corporations Doing Business in Europe

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    An Examination of the Small-Firm Effect within the REIT Industry

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    Real estate investment trusts (REITs) offer investors the ability to more easily include real estate-related assets in their investment portfolios. Certain REIT characteristics may allow some REITs to outperform others. Empirical research in the financial literature indicates that small firms earn higher average rates of return than large firms after accounting for risk. This research tests for the existence of the small-firm effect within the REIT industry. REITs provide an opportunity to examine the small-firm effect and its possible explanations using a relative homogeneous group of securities. The evidence supports a small-firm effect for REITs over the time period examined even after considering the possible explanations identified in the financial efficient markets literature.

    The Health Effects of Medicare for the Near-Elderly Uninsured

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    We study how the trajectory of health for the near-elderly uninsured changes upon enrolling into Medicare at the age of 65. We find that Medicare increases the probability of the previously uninsured having excellent or very good health, decreases their probability of being in good health, and has no discernable effects at lower health levels. Surprisingly, we found Medicare had a similar effect on health for the previously insured. This suggests that Medicare helps the relatively healthy 65 year olds, but does little for those who are already in declining health once they reach the age of 65. The improvement in health between the uninsured and insured were not statistically different from each other. The stability of insurance coverage afforded by Medicare may be the source of the health benefit suggesting that universal coverage at other ages may have similar health effects.

    Use of Propensity Scores in Non-Linear Response Models: The Case for Health Care Expenditures

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    Under the assumption of no unmeasured confounders, a large literature exists on methods that can be used to estimating average treatment effects (ATE) from observational data and that spans regression models, propensity score adjustments using stratification, weighting or regression and even the combination of both as in doubly-robust estimators. However, comparison of these alternative methods is sparse in the context of data generated via non-linear models where treatment effects are heterogeneous, such as is in the case of healthcare cost data. In this paper, we compare the performance of alternative regression and propensity score-based estimators in estimating average treatment effects on outcomes that are generated via non-linear models. Using simulations, we find that in moderate size samples (n= 5000), balancing on estimated propensity scores balances the covariate means across treatment arms but fails to balance higher-order moments and covariances amongst covariates, raising concern about its use in non-linear outcomes generating mechanisms. We also find that besides inverse-probability weighting (IPW) with propensity scores, no one estimator is consistent under all data generating mechanisms. The IPW estimator is itself prone to inconsistency due to misspecification of the model for estimating propensity scores. Even when it is consistent, the IPW estimator is usually extremely inefficient. Thus care should be taken before naively applying any one estimator to estimate ATE in these data. We develop a recommendation for an algorithm which may help applied researchers to arrive at the optimal estimator. We illustrate the application of this algorithm and also the performance of alternative methods in a cost dataset on breast cancer treatment.
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