A study of total beta specification through symmetric regression: the case of the Johannesburg Stock Exchange

A topic of recent interest is risk management in equity investments from emerging markets. One traditional measure for systematic risk of an asset is beta, which is constructed through ordinary least squares (OLS) regression between historical returns on an individual asset and an index representing the overall market. OLS regression assumes all the error lies within the asset returns. Tofallis (Eur J Oper Res 187(3):1358–1367, 2008) made the case for constructing a systematic risk measure through symmetric regression, where error is assumed to be present in the returns of both the asset and the index. In this paper, we construct a systematic risk measure using symmetric regression for the case of the Johannesburg Stock Exchange (JSE). This paper makes the case that the so-called ‘total beta’ parameter provides a more realistic and stable estimator for market-related risk and return. The total beta estimate, explicitly allowing for error in both variables, is less likely to underestimate the magnitude of the beta parameter.     

Development and Use of a Sedimentation Risk Index for Unpaved Road‐Stream Crossings in the Choctawhatchee Watershed1

Abstract: Unpaved road‐stream crossings increase sediment yields in streams and alter channel morphology and stability. Before restoration and sedimentation reduction strategies can be implemented, a priority listing of unpaved road‐stream crossings must be created. The objectives of this study were to develop a sedimentation risk index (SRI) for unpaved road‐stream crossings and to prioritize 125 sites in the Choctawhatchee watershed (southeastern Alabama) using this model. Field surveys involved qualitative and quantitative observations of 73 metrics related to waterway conditions, crossing structures, road approaches, and roadside soil erosion. The road‐stream crossing risk analyses involved elimination of candidate metrics based on redundancy, skewness, lack of data, professional judgment, lack of nonzero values, unbalanced box plots, and limited ranges of values. A final selection of 12 metrics formed the SRI and weighed factors involving soil erodibility, road sedimentation abatement features, and stream morphology alteration. The SRI was organized into narrative categories (excellent, good, fair, poor, and very poor) based on the distribution of scores. No excellent sites (scores ≥55) were found in this study, 17 (20.7%) were good (low sedimentation risk), 37 (45.1%) were fair (moderate sedimentation risk), 26 (31.7%) were poor (high sedimentation risk), and two (2.5%) were very poor (high sedimentation risk). There was no significant difference in SRI scores among crossing structure type (round culverts, box culverts, and bridges) (H = 4.31, df = 2, p = 0.058). A future study of the Choctawhatchee watershed involving the same study sites could assess the success of restoration plans and activities based on site score improvement or decline.     

INTERPRETATION OF “RESTRICTED VALIDITY” IRRIGATION PERMITS IN THE SVARTÅ RIVER BASIN,SWEDEN1

ABSTRACT: Irrigation permits in the Svartå River basin, Sweden, are issued with restricted validities by which irrigation is permitted only in those periods when the release from the primary regulation facility in the basin is greater than 2.0 m³/s. A “risk” measure describing the expected total duration of periods in which irrigation will not be permitted in the basin under a range of conditions has been formulated and applied to the basin. The measure recognizes only the period for which irrigation is not permitted and does not consider water availability as it is not a factor in this case. Comparison of the measure with a previously proposed approach shows that it provides a better measure of system behavior. The new measure is particularly useful for transferring to the nontechnical water user or manager an understanding of how well the overall irrigation system can be expected to perform.     

Assessment of potential groundwater contamination sources in a wellhead protection area

Determining the human health dangers from potential contamination sources, within a wellhead protection area (WHPA), requires that a risk analysis be undertaken. In this study, a desktop geographic information system and spreadsheet software are used to implement an EPA risk screening methodology for WHPAs called 'Managing Ground Water Contamination Sources in Wellhead Protection Areas--A Priority Setting Approach'. The methodology was applied to a WHPA in Gaston County, North Carolina. Results indicate that the risk of well contamination from an interstate highway and gas station with old steel underground storage tanks were comparatively high. Medium risks included a thoroughfare and highway, while low risks were assigned to machine shops, a body shop, septic systems and a gas station with new underground storage tanks and secondary containment. A sensitivity analyses of the Priority Setting Approach indicated that risk scores were extremely sensitive to hydrogeologic variables such as hydraulic conductivity. It is recommended that risk assessors utilize a range of hydrogeologic parameters to assess overall risk from each potential contamination source.     

The shadow price of substitutable sulfur in the US electric power plant: a distance function approach

Given restrictions on sulfur dioxide emissions, a feasible long-run response could involve either an investment in improving boiler fuel-efficiency or a shift to a production process that is effective in removing sulfur dioxide. To allow for the possibility of substitution between sulfur and productive capital, we measure the shadow price of sulfur dioxide as the opportunity cost of lowering sulfur emissions in terms of forgone capital. The input distance function is estimated with data from 51 coal-fired US power units operating between 1977 and 1986. The indirect Morishima elasticities of substitution indicate that the substitutability of capital for sulfur is relatively high. The overall weighted average estimate of the shadow price of sulfur is -0.076 dollars per pound in constant 1976 dollars.     

A method for assessing environmental risk: A case study of Green Bay,Lake Michigan,USA

The Science Advisory Board of the US Environmental Protection Agency has recommended that risk reduction strategies become the centerpiece of environmental protection. The goal in developing such strategies is to identify opportunities for greatest reduction of ecological risks. This is a perspective that is significantly more comprehensive than the traditional focus on human health risks arising from environmental degradation. The identification of ecological risks upon which environmental protection efforts should be focused requires an ecological risk assessment methodology that is based on anthropogenic stressors affecting an ecosystem and a set of impaired use criteria. A methodology based on this concept is developed and discussed in this article. The methodology requires that risk values be assigned to each ecosystem stressor-impaired use pair that reflect the degree to which the given stressor contributes to ecosystem risk as measured by the given impaired use criterion. Once these data are available, mathematical analyses based on concepts from fuzzy set theory are performed to obtain a ranking of ecosystem stressors. The methodology has been tested by applying it to a case study involving Green Bay of Lake Michigan. A workshop was held in which 11 persons with extensive knowledge of the Green Bay ecosystem determined risk values through a group-consensus process. The analytical portion of the methodology was then used to rank the ecosystem risks (stressors) from several perspectives, including prevention management and remediation management. The overall conclusion of the workshop participants was that the fuzzy set decision model is a useful and effective methodology for differentiating environmental risk.     

Uncertainty modelling in multi-criteria analysis of water safety measures

Water utilities must assess risks and make decisions on safety measures in order to obtain a safe and sustainable drinking water supply. The World Health Organization emphasises preparation of water safety plans, in which risk ranking by means of risk matrices with discretised probability and consequence scales is commonly used. Risk ranking enables prioritisation of risks, but there is currently no common and structured way of performing uncertainty analysis and using risk ranking for evaluating and comparing water safety measures. To enable a proper prioritisation of safety measures and an efficient use of available resources for risk reduction, two alternative models linking risk ranking and multi-criteria decision analysis (MCDA) are presented and evaluated. The two models specifically enable uncertainty modelling in MCDA, and they differ in terms of how uncertainties in risk levels are considered. The need of formal handling of risk and uncertainty in MCDA is emphasised in the literature, and the suggested models provide innovations that are not dependent on the application domain. In the case study application presented here, possible safety measures are evaluated based on the benefit of estimated risk reduction, the cost of implementation and the probability of not achieving an acceptable risk level. Additional criteria such as environmental impact and consumer trust may also be included when applying the models. The case study shows how safety measures can be ranked based on preference scores or cost-effectiveness and how measures not reducing the risk enough can be identified and disqualified. Furthermore, the probability of each safety measure being ranked highest can be calculated. The two models provide a stepwise procedure for prioritising safety measures and enable a formalised handling of uncertainties in input data and results.     

A Watershed-Scale Model for Predicting Nonpoint Pollution Risk in North Carolina

The Southeastern United States is a global center of freshwater biotic diversity, but much of the regions aquatic biodiversity is at risk from stream degradation. Nonpoint pollution sources are responsible for 70% of that degradation, and controlling nonpoint pollution from agriculture, urbanization, and silviculture is considered critical to maintaining water quality and aquatic biodiversity in the Southeast. We used an ecological risk assessment framework to develop vulnerability models that can help policymakers and natural resource managers understand the impact of land cover changes on water quality in North Carolina. Additionally, we determined which landscape characteristics are most closely associated with macroinvertebrate community tolerance of stream degradation, and therefore with lower-quality water. The results will allow managers and policymakers to weigh the risks of management and policy decisions to a given watershed or set of watersheds, including whether streamside buffer protection zones are ecologically effective in achieving water quality standards. Regression analyses revealed that landscape variables explained up to 56.3% of the variability in benthic macroinvertebrate index scores. The resulting vulnerability models indicate that North Carolina watersheds with less forest cover are at most risk for degraded water quality and steam habitat conditions. The importance of forest cover, at both the watershed and riparian zone scale, in predicting macrobenthic invertebrate community assemblage varies by geographic region of the state.     

RISK OF EXTREME EVENTS IN A MULTIOBJECTIVE FRAMEWORK1

ABSTRACT: This paper summarizes advances made in risk-based decisionmaking in water resources through use of the partitioned multiobjective risk method (PMRM). (Risk is a measure of the probability and severity of adverse effects.) In the PMRM, the risk of extreme events is differentiated from risk involving less extreme damage severity and is evaluated within a multiobjective framework. Study of the extreme-event risk function f₄(*) has addressed the following issues: methods for calculating f₄(*); the sensitivity of f₄(*) to various parameters, particularly to the partitioning point of the extreme-event range and the selection of probability density functions; insight provided by the statistics of extremes; and the impact of f₄(*) on risk management, for example, in the application of the PMRM to water resources problems. In particular, this paper shares with the reader recent research results on the PMRM, the relationship between the statistics of extremes and the conditional expected value, derived formulas for f₄(*), distribution-free estimates of f₄(*), documented case studies in dam safety, and future research directions.     

浅论新疆开发区的管理状况及其保护对策

文章主要对新疆各类开发区目前的环境管理状况及存在的问题作了分析,提出推动开发区区域环境规划或加强环境影响评价的对策.明确开发区环境保护的总体要求,合理规划开发区内外的总体布局,加强开发区的环境监督管理,建立跟踪监测制度,采取有效手段推进环保设施建设.控制开发区污染物总量的排放和加强开发区的生态环境建设,落实事故风险防范和应急措施,从而更有效地为开发区的企业提供服务.     

How Good? Ethical Criteria for a ‘Good Life’ for Farm Animals

The Farm Animal Welfare Council’s concept of a Good Life gives an idea of an animal’s quality of life that is over and above that of a mere life worth living. The concept needs explanation and clarification, in order to be meaningful, particularly for consumers who purchase farm animal produce. The concept could allow assurance schemes to apply the label to assessments of both the potential of each method of production, conceptualised in ways expected to enhance consumers’ engagement such as ‘naturalness’ and ‘freedom’; and the concept of a life worth living as a safeguard threshold below which no animal’s actual welfare should fall, based on each animal’s overall affective states. This may provide a framework for development of the Good Life concept, within scientific and sociological fields, in order to allow reliable and influential use by assessors, consumers and retailers.     

USE OF FIRST-ORDER UNCERTAINTY ANALYSIS TO OPTIMIZE SUCCESSFUL STREAM WATER QUALITY SIMULATION1

ABSTRACT: A first-order uncertainty technique is developed to quantify the relationship between field data collection and a modeling exercise involving both calibration and subsequent verification. A simple statistic (LTOTAL) is used to quantify the total likelihood (probability) of successfully calibrating and verifying the model. Results from the first-order technique are compared with those from a traditional Monte Carlo simulation approach using a simple Streeter-Phelps dissolved oxygen model. The largest single difference is caused by the filtering or removal of unrealistic outcomes within the Monte Carlo framework. The amount of bias inherent in the first-order approach is also a function of the magnitude of input variability and sampling location. The minimum bias of the first-order technique is approximately 20 percent for a case involving relatively large uncertainties. However the bias is well behaved (consistent) so as to allow for correct decision making regarding the relative efficacy of various sampling strategies. The utility of the first-order technique is demonstrated by linking data collection costs with modeling performance. For a simple and inexpensive project, a wise and informed selection resulted in an LTOTAL value of 86 percent, while an uninformed selection could result in an LTOTAL value of only 55 percent.     

论环境风险预防原则中的风险阈值

如何把环境风险预防原则确立为环境法的基本原则,一个重要的问题就是"环境风险"的界定。通过对法律意义上的环境风险进行分析,指出确立风险阈值的原因,即我国对"环境风险"的界定不清,环境风险的风险性缺乏法定依据以及不同种类的利益之间存在冲突等,进而从明确环境风险的类型、评估环境风险量度、明确责任归结三方面思考了风险阈值的确立问题。     

Governance of water supply systems in the Palestinian Territories: A data envelopment analysis approach to the management of water resources

This study demonstrates that data envelopment analysis (DEA) can be a useful tool to assess the relative efficiencies of water supply systems and to establish benchmarks with which to measure progress in the management of water resources. Frontier efficiency models measure the efficiency of water use in the Palestinian Territories (West Bank and the Gaza Strip). At the municipality level, sufficient data for the years 1999-2002 were available to estimate efficiency and stability scores. The Gaza Strip efficiency scores were considerably lower than those of the West Bank. Water losses were the major source of the inefficiency as indicated by the large slacks of this input. The relative sizes of the municipalities affect efficiency scores little. Palestinian policy makers should focus on rebuilding the infrastructure of the water networks, beginning with the most DEA inefficient municipalities in order to minimize water losses.     

Measuring environmental performance at niagara mohawk power

A system for measuring environmental performance is important to the success of a company's environmental excellence program. In 1991, Niagara Mohawk Power Corporation (NMPC) unveiled a new corporate policy on protection of the environment. To measure and communicate progress in achieving the goals and objectives embodied in the new policy, an environmental performance index (EPI) was developed. In this article the author shows how the EPI utilizes a weight and rating scheme to reflect environmental performance in three categories: emissions/wastes, regulatory compliance, and environmental enhancements. Performance goals have been established for the period 1992–1995, and actual performance data has been compiled for 1992 and 1993. While the EPI is designed to measure changes in NMPC's environmental performance over time, it does not provide information on how the company's performance compares to that of other electric utilities. Accordingly, NMPC is developing an environmental benchmarking program with a group of Northeast electric utilities that will allow comparisons of environmental performance between utilities.     

Using Count Data and Ordered Models in National Forest Recreation Demand Analysis

This research addresses the need to improve our knowledge on the demand for national forests for recreation and offers an in-depth data analysis supported by the complementary use of count data and ordered models. From a policy-making perspective, while count data models enable the estimation of monetary welfare measures, ordered models allow for the wider use of the database and provide a more flexible analysis of data. The main purpose of this article is to analyse the individual forest recreation demand and to derive a measure of its current use value. To allow a more complete analysis of the forest recreation demand structure the econometric approach supplements the use of count data models with ordered category models using data obtained by means of an on-site survey in the Bussaco National Forest (Portugal). Overall, both models reveal that travel cost and substitute prices are important explanatory variables, visits are a normal good and demographic variables seem to have no influence on demand. In particular, estimated price and income elasticities of demand are quite low. Accordingly, it is possible to argue that travel cost (price) in isolation may be expected to have a low impact on visitation levels.     

Application and sensitivity testing of a eutrophication assessment method on coastal systems in the United States and European Union

The Assessment of Estuarine Trophic Status (ASSETS) screening model has been extended to allow its application to both estuarine and coastal systems. The model, which combines elements of pressure, state and response, was tested on four systems: Maryland Coastal Bays and Long Island Sound in the United States and The Firth of Clyde (Scotland) and Tagus Estuary (Portugal) in the European Union. The overall scores were: Maryland Coastal Bays: Bad; Firth of Clyde: Poor; Tagus Estuary: Good. Long Island Sound was modelled along a timeline, using 1991 data (score: Bad) and 2002 data (score: Moderate). The improvement registered for Long Island Sound is a consequence of the reduction in nutrient loading, and the ASSETS score changed accordingly. The two main areas where developments are needed are (a) In the definition of type-specific ranges for eutrophication parameters, due to the recognition that natural or pristine conditions may vary widely, and the use of a uniform set of thresholds artificially penalizes some systems and potentially leads to misclassification; (b) In the definition and quantification of measures which will result in an improved state through a change in pressures, as well as in the definition of appropriate metrics through which response may be assessed. One possibility is the use of detailed research models where different response scenarios potentially produce changes in pressure and state. These outputs may be used to drive screening models and analyze the suitability of candidate metrics for evaluating management options.     

Measuring landscape integrity (LI): development of a hybrid methodology for planning applications

Landscape integrity data-sets represent a measure of a landscape's naturalness, or its inverse, the level of human modification. Generally referred to as human footprint modeling, a hybrid approach was developed here by incorporating distance, density, and spatially explicit fuzzy logic methods for quantifying the impacts of anthropocentric infrastructure on the landscape. Integrity scores varied markedly across this large and heterogeneous landscape. A comparative analysis among peer data products revealed that this model exhibited the highest level of correlation when compared to an independently derived expert survey of expected scores. Moreover, differences in correlation were found to be statistically significant in two cases indicating robust model performance. Data products such as these may be leveraged to quantify the nature and extent of human modifications on the landscape, identify highly natural areas for conservation purposes, and may serve as an overarching umbrella for guiding and coordinating large and local-scale planning efforts.     

Value of intelligence applied to networks

A methodology is proposed to complement the subjective “value” of intelligence with an objective metric of “impact” of information on network models. This is a deterministic one-way sensitivity analysis similar to value of information used in inference diagrams. It would measure the impact of a piece of information on a network’s metric, in this case being used to answer intelligence analyst questions. This methodology suggests that the sensitivity of each link to existing analysis implies that the link has an impact on the analysis. The impact of these links can be measured quantitatively. In this paper, we explore data of tweets and apply the methodology to the links between twitter users and use the network measure of betweenness centrality to determine their quantitative impact on the overall network.