The Potential Environmental Benefits of Co‐Operative Businesses Within the Climate Change Agenda

The economic benefits of agricultural co‐operatives are well rehearsed and have received significant attention in the literature, especially in regard to the resource efficiencies flowing from collective action that might be absent from investor‐owned firms. This article provides evidence to show how these resource efficiencies might also manifest themselves as environmental advantages, which may not be available through investor‐owned firms due to the different purpose of, and motivation for, business activity. Specifically, the article explores how co‐operative businesses may deliver climate change benefits by examining case studies of alternative co‐operative functions that provide a mix of qualitative and quantitative evidence. Results show that, where co‐operative businesses achieve efficiencies through economies of scale, knowledge and skills transfer, sharing of risks and other means, this can also lead to coincidental reductions in greenhouse gas emissions that may not be achieved if investor‐owned activity prevails. Whilst coincidental at present, the future exploitation of this phenomenon could lead to valuable market advantage or aid sustainable development policy. Copyright © 2011 John Wiley & Sons, Ltd and ERP Environment.     

LACK OF RIGOUR IN DEFENDING FAIRTRADE: A REPLY TO ALASTAIR SMITH

Alastair Smith (2009 ) claims to refute a few criticisms of Fairtrade. It is shown that his empirical evidence consists of anecdotes with no statistical or other evidential value, and that his economics is wrong. Though Fairtrade is an agricultural marketing system, he appears not to be aware of the literature on agricultural marketing or co‐operatives. Accordingly he makes statements not in accord with the accepted theory or evidence. He assumes, for instance, backward‐sloping supply curves and that the prices offered by state marketing boards are not affected by markets. There are ethical trading alternatives which avoid all the criticisms of Fairtrade.     

Small businesses and the environment: turning over a new leaf?

Previous studies on the environmental practices of small and medium‐sized enterprises (SMEs) in the UK and beyond have portrayed owner‐managers as laggards who underplay their firm's environmental impacts and resist environmental management due to its perceived cost. Yet a recent cross‐sector survey of 220 UK SMEs suggests that this intransigent stance may be slowly changing. Responses indicate a high percentage of owner‐managers actively involved in recycling, energy efficiency, responsible buying and selling, and efforts to reduce their carbon emissions. Owner‐managers saw it as their responsibility to help solve environmental problems and were reportedly willing to accept the costs of tougher environmental regulations and taxation. Business owners were motivated not just by the ‘push’ of legislation and environmental concern but by the ‘pull’ of potential cost savings, new customers, higher staff retention and good publicity for their firms. The survey also found that owner‐managers had resonance with the Stern Review's (2006) conclusions that the benefits of strong early action on climate change outweigh the costs, and that a transition to a low‐carbon economy will bring opportunities for business growth. This indicates that SMEs may be coming round to the idea that there is a business case for sustainability, although there is still some scepticism on the overall profitability of environmental action. Copyright © 2009 John Wiley & Sons, Ltd and ERP Environment.     

Threshold bipower variation and the impact of jumps on volatility forecasting

This study reconsiders the role of jumps for volatility forecasting by showing that jumps have a positive and mostly significant impact on future volatility. This result becomes apparent once volatility is separated into its continuous and discontinuous components using estimators which are not only consistent, but also scarcely plagued by small sample bias. With the aim of achieving this, we introduce the concept of threshold bipower variation, which is based on the joint use of bipower variation and threshold estimation. We show that its generalization (threshold multipower variation) admits a feasible central limit theorem in the presence of jumps and provides less biased estimates, with respect to the standard multipower variation, of the continuous quadratic variation in finite samples. We further provide a new test for jump detection which has substantially more power than tests based on multipower variation. Empirical analysis (on the S&P500 index, individual stocks and US bond yields) shows that the proposed techniques improve significantly the accuracy of volatility forecasts especially in periods following the occurrence of a jump.     

WHY FREE MARKETS SHOULD NOT BE BLAMED FOR THE CURRENT RECESSION

Interventionist thinkers are now claiming intellectual victory, blaming the free‐market system and its ideology for the current economic collapse. We find this thesis untenable, drawing on the Austrian Business Cycle Theory. Instead, we argue that the roots of our present downturn lie in the monetary system, whose institutional structure is far from any free‐market ideal. Moreover, several government policies have contributed to the problems.     

Contest success function with the possibility of a draw: Axiomatization

In imperfectly discriminating contests the contestants contribute effort to win a prize but the highest contributed effort does not necessarily secure a win. The contest success function (CSF) is the technology that translates an individual's effort into his or her probability of winning. This paper provides an axiomatization of CSF when there is the possibility of a draw (the sum of winning probabilities across all contestants does not add up to one).     

The Role of Behavioral Survey Methodologists in National Statistical

The expertise of behavioral survey methodologists is needed in national statistical agencies because of the necessity of using theory and research from the social sciences to reduce survey error. In this paper various social science based explanations for measurement error and nonresponse error are described in order to illustrate the conceptual foundations of such error reduction efforts. Three roles for behavioral survey methodologists in national statistical agencies are then discussed. They include: 1) bring an error reduction perspective to bear in an influential way for all aspects of designing and implementing agency surveys; 2) bring theoretical efficiency and effectiveness to experimental tests of alternative questionnaire designs and implementation procedures through the use of theories, concepts and pretests and findings of past behavioral science research; and 3) contribute to the expanding science of survey methodology.     

An alternative definition of individual bioequivalence

Several definitions of individual bioequivalence of two formulations of a medical treatment (drug) have been proposed recently. These definitions attempt to adapt the criterion of average bioequivalence, which would be deficient if substantive treatment heterogeneity were present. In some of the proposed definitions, relatively large differences of means can be compensated by differences in the measurement-error variances. We propose a definition based on a simple latent-variable model which overcomes this anomaly and need not involve the U.S. Food and Drug Administration's 80/125 rule. Our approach is based on a moment-matching estimator of the discrepancy between the outcomes underlying the subjects' responses. The distribution of this estimator is a linear combination of independent χ² variates; asymptotically, it can be approximated by a normal distribution. Evidence of individual bioequivalence corresponds to rejecting the hypothesis that the discrepancy is greater than a specified threshold. The approach is illustrated by reanalysing two bioequivalence trials.     

Time Series Analysis of Repeated Surveys: The State–space Approach

Cross sectional estimates from repeated surveys form a time series { y_t }. These estimates can be viewed as the sum y _t = Y _t + e _t of two processes, { Y _t }, the population process and { e _t }, the survey error process. Serial correlations in the latter series are usually present, mainly due to sample overlap. Other sources of data such as censuses, administrative records and demographic population counts are also available. The state–space modelling approach to the analysis of repeated surveys allows combining information from different sources, incorporating benchmarking constraints in a natural way. Results from these methods seem to compare favourably with those from X-11-ARIMA in filtering out survey errors.     

Cross Validation Calibration Based Shrinkage – Revisited for the Construction of Prognostic Indices

The use of shrinkage methods for the construction of prognostic indices has been paid increasing attention in the literature on medical statistics in the last years. One approach for the construction of a shrinkage factor is cross validation calibration as suggested by van H ouwelingen and le C essie (1990). We investigate this approach in more detail. First we try to clarify why shrinkage factors constructed by cross validation calibration tend to be smaller than 1. Second we explain why use of this shrinkage factor can result in an improvement of the average prediction error. Third we investigate the possible gain for constellations relevant in medical research by means of a simulation study, focusing on the dilemma, that the improvement on average has to be paid by distinct deteriorations for some patients. Finally we conclude that it is necessary to rethink the choice of loss functions in constructing prognostic indices before recommendations about the use of shrinkage methods can be made.