Input-output evaluation of rural development: a forestry-centred application

The purpose of this paper is to analyse the role of forestry in the rural economy of Scotland. The Generation of Regional Input-Output Tables (GRIT) technique is applied to the estimation of input-output tables for rural Scotland. This is followed by a forestry-centred multiplier analysis. The results suggest that the forestry planting and harvesting sectors offer great potential for improving economic activity. However, their backward linkages with other rural industries seem to be limited. On the other hand, the backward linkages of wood-processing industries with the rest of the economy are strong. From this analysis, it is concluded that the joint development of forestry and wood-processing industries would promote economic development in rural Scotland.     

The Role of Cancer Risk in the Regulation of Industrial Pollution

The extent of carcinogen regulation under existing U.S. environmental statutes is assessed by developing measures of the scope and stringency of regulation. While concern about cancer risk has played an important political role in obtaining support for pollution control programs, it has not provided the predominant rationale for most regulatory actions taken to date. Less than 20% of all standards established to limit concentrations of chemicals in various media address carcinogens. Restrictions on chemical use are more frequently based on concerns about noncancer human health or ecological effects. Of the chemicals in commercial use which have been identified as potential human carcinogens on the basis of rodent bioassays, only a small proportion are regulated. There is an inverse relationship between the scope of regulatory coverage and the stringency of regulatory requirements: the largest percentages of identified carcinogens are affected by the least stringent requirements, such as information disclosure. Standards based on de minimis cancer risk levels have been established for only 10% of identified carcinogens and are restricted to one medium: water. Complete bans on use have affected very few chemicals. The general role that carcinogenicity now plays in the regulatory process is not dramatically different from that of other adverse human health effects: if a substance is identified as a hazard, it may eventually be subject to economically achievable and technically feasible restrictions.     

Mining the Data: Analyzing the Economic Implications of Mining for Nonmetropolitan Regions

Extractive industries such as logging and mining are generally expected to bring significant economic benefits to rural regions, but a growing number of findings have now challenged that common expectation. Still, it is not clear whether the findings of less–than–desirable economic outcomes are isolated or representative. In this article, we assemble literally all of the relevant quantitative findings on mining that we have been able to identify in published and/or technical literature from the United States. In the interest of rigor, we limit the assessment to cases in which strictly nonmetropolitan mining regions are compared against other nonmetropolitan regions and/or against those regions’ own experiences over time. Overall, 301 findings meet the criteria for inclusion. Contrary to the long–established assumptions, but consistent with more recent critiques, roughly half of all published findings indicate negative economic outcomes in mining communities, with the remaining findings being split roughly evenly between favorable and neutral/indeterminate ones. Positive findings are more likely to be associated with incomes than with poverty or (especially) unemployment rates, and they are more likely to come from the western United States, where much of the mining involves relatively large, new coal strip mines. Over half of all positive findings come from the years prior to 1982. In virtually all other categories, the plurality or majority of findings have been negative. When the patterns of findings are subjected to one–sample means tests, the only way to produce a significantly positive outcome is by combining all neutral/indeterminate findings with the positive ones, while focusing exclusively on incomes; by contrast, in the case of poverty or unemployment rates—as well as for the overall body of findings—the results are consistently and significantly negative, whether the neutral/indeterminate findings are combined with negative ones or omitted from the equations altogether. Until or unless future studies produce dramatically different findings, there appears to be no scientific basis for accepting the widespread, “obvious” assumption that mining will lead to economic improvement.     

A Comparison of Partially Adaptive and Reweighted Least Squares Estimation

The small sample performance of least median of squares, reweighted least squares, least squares, least absolute deviations, and three partially adaptive estimators are compared using Monte Carlo simulations. Two data problems are addressed in the paper: (1) data generated from non-normal error distributions and (2) contaminated data. Breakdown plots are used to investigate the sensitivity of partially adaptive estimators to data contamination relative to RLS. One partially adaptive estimator performs especially well when the errors are skewed, while another partially adaptive estimator and RLS perform particularly well when the errors are extremely leptokur-totic. In comparison with RLS, partially adaptive estimators are only moderately effective in resisting data contamination; however, they outperform least squares and least absolute deviation estimators.     

Sources of family violence

This paper suggests a direction for the exploration of the causes of family violence. Explanatory models of family violence were considered in this regard, with the recommendation that a multi-determined model should be considered to ensure the most accurate explanation. We suggest that family violence will be best understood and prevented or alleviated, if a model is used that considers the interaction of structural violence and the personality features of all the family members.     

On the existence and uniqueness of maximizers of two likelihood functions

While applying theclassical maximum likelihood method for a certain statistical inference problem, Smith and Weissman [5] have noted that there are conditions under which the likelihood function may be unbounded above or may not possess local maximizers. Ariyawansà and Templeton [1] have derived inference procedures for this problem using the theory of structural inference [2,3,4]. Based on numerical experience, and without proof, they state that the resulting likelihood functions possess unique, global maximizers, even in instances where the classical maximum likelihood method fails in the above sense. In this paper, we prove that under quite mild conditions, these likelihood functions that result from the application of the theory of structural inference are well-behaved, and possess unique, global maximizers. This research was supported in part by the Applied Mathematical Sciences subprogram of the U.S. Department of Energy under contract W-31-109-Eng-38 while the author was visiting the Mathematics and Computer Science Division of Argonne National Laboratory, Argonne, Illinois.     

Sampling Strategies for Toxic Air Contaminants

Annual concentrations of toxic air contaminants are of primary concern from the perspective of chronic human exposure assessment and risk analysis. Despite recent advances in air quality monitoring technology, resource and technical constraints often impose limitations on the availability of a sufficient number of ambient concentration measurements for performing environmental risk analysis. Therefore, sample size limitations, representativeness of data, and uncertainties in the estimated annual mean concentration must be examined before performing quantitative risk analysis. In this paper, we discuss several factors that need to be considered in designing field-sampling programs for toxic air contaminants and in verifying compliance with environmental regulations. Specifically, we examine the behavior of SO2, TSP, and CO data as surrogates for toxic air contaminants and as examples of point source, area source, and line source-dominated pollutants, respectively, from the standpoint of sampling design. We demonstrate the use of bootstrap resampling method and normal theory in estimating the annual mean concentration and its 95% confidence bounds from limited sampling data, and illustrate the application of operating characteristic (OC) curves to determine optimum sample size and other sampling strategies. We also outline a statistical procedure, based on a one-sided t-test, that utilizes the sampled concentration data for evaluating whether a sampling site is compliance with relevant ambient guideline concentrations for toxic air contaminants.     

Coaching für Führungskräfte im Krankenhaus Baustein einer Strategie zum Total Quality Management

Coaching of managers in hospitals as component of a total quality management strategy The author delineates the changed conditions of hospitals at the beginning of the new millenium. In order to be up to date with the growing challenges and the need for change a Total Quality Management (TQM) is necessary. This TQM sees the satisfaction of clients and of employees as crucial for all reorganization processes. The realization in everyday hospital life requires a total personnel development concept, with special regard to the managers and their specific needs for support by supervisors resp. coaches.     

Minority Poverty in Nonmetropolitan Texas*

Abstract Despite a high prevalence of poverty among minorities in nonmetropolitan areas, research and policy concerns regarding poverty have continued focusing on metropolitan minorities. This study uses a model integrating individual, household, and structural factors to examine poverty among Latinos, blacks, and Anglos in nonmetropolitan and, for comparative purposes, metropolitan areas, using data from the 1985 Special Texas Census TDHS 1987. The findings show that minorities in nonmetropolitan areas tend to have the highest poverty rates. In addition, consistent as well as divergent patterns exist among the six ethnic-resident groups with respect to the relationships among the various individual, household, and structural factors and poverty.