A method for the economic valuation of animal welfare benefits using a single welfare score

Unless the benefits to society of measures to protect and improve the welfare of animals are made transparent by means of their valuation they are likely to go unrecognised and cannot easily be weighed against the costs of such measures as required, for example, by policy-makers. A simple single measure scoring system, based on the Welfare Quality® index, is used, together with a choice experiment economic valuation method, to estimate the value that people place on improvements to the welfare of different farm animal species measured on a continuous (0-100) scale. Results from using the method on a survey sample of some 300 people show that it is able to elicit apparently credible values. The survey found that 96% of respondents thought that we have a moral obligation to safeguard the welfare of animals and that over 72% were concerned about the way farm animals are treated. Estimated mean annual willingness to pay for meat from animals with improved welfare of just one point on the scale was £5.24 for beef cattle, £4.57 for pigs and £5.10 for meat chickens. Further development of the method is required to capture the total economic value of animal welfare benefits. Despite this, the method is considered a practical means for obtaining economic values that can be used in the cost-benefit appraisal of policy measures intended to improve the welfare of animals.

Atrocities in theory and practice: An introduction

Classical counterinsurgency theory – written before the 19th century – has generally strongly opposed atrocities, as have theoreticians writing on how to conduct insurgencies. For a variety of reasons – ranging from pragmatic to religious or humanitarian – theoreticians of both groups have particularly argued for the lenient treatment of civilians associated with the enemy camp, although there is a marked pattern of exceptions, for example, where heretics or populations of cities refusing to surrender to besieging armies are concerned. And yet atrocities – defined here as acts of violence against the unarmed (non-combatants, or wounded or imprisoned enemy soldiers), or needlessly painful and/or humiliating treatment of enemy combatants, beyond any action needed to incapacitate or disarm them – occur frequently in small wars. Examples abound where these exhortations have been ignored, both by forces engaged in an insurgency and by forces trying to put down a rebellion. Why have so many atrocities been committed in war if so many arguments have been put forward against them? This is the basic puzzle for which the individual contributions to this special issue are seeking to find tentative answers, drawing on case studies.

Introduction: special issue on advances in brand management

This special issue of the Journal of Business Research contains 13 articles presented at the Spring 2007 Thought Leaders International Conference on Brand Management. Following a blind reviewing process 69 papers were presented at the conference then authors were invited to revise their papers for inclusion consideration for this special issue. A further round of blind reviewing resulted in the selection of those 13 articles. This introduction presents a review of the research into brand management.

Measuring the consumer benefits of improving farm animal welfare to inform welfare labelling

Policy makers in the European Union are envisioning the introduction of a community farm animal welfare label which would allow consumers to align their consumption habits with their farm animal welfare preferences. For welfare labelling to be viable the market for livestock products produced to higher welfare standards has to be sufficiently segmented with consumers having sufficiently distinct and behaviourally consistent preferences. The present study investigates consumers’ preferences for meat produced to different welfare standards using a hypothetical welfare score. Data is obtained from a contingent valuation study carried out in Britain. The ordered probit model was estimated using Bayesian inference to obtain mean willingness to pay. We find decreasing marginal WTP as animal welfare levels increase and that people’s preferences for different levels of farm animal welfare are sufficiently differentiated making the introduction of a labelling scheme in the form of a certified rating system appear feasible.

Estimating reliability and resolution of probability forecasts through decomposition of the empirical score

References (20)Cited By (1)Export CitationAboutAbstract Proper scoring rules provide a useful means to evaluate probabilistic forecasts. Independent from scoring rules, it has been argued that reliability and resolution are desirable forecast attributes. The mathematical expectation value of the score allows for a decomposition into reliability and resolution related terms, demonstrating a relationship between scoring rules and reliability/resolution. A similar decomposition holds for the empirical (i.e. sample average) score over an archive of forecast–observation pairs. This empirical decomposition though provides a too optimistic estimate of the potential score (i.e. the optimum score which could be obtained through recalibration), showing that a forecast assessment based solely on the empirical resolution and reliability terms will be misleading. The differences between the theoretical and empirical decomposition are investigated, and specific recommendations are given how to obtain better estimators of reliability and resolution in the case of the Brier and Ignorance scoring rule.

Evaluating raw ensembles with the continuous ranked probability score

The continuous ranked probability score (CRPS) is a frequently used scoring rule. In contrast with many other scoring rules, the CRPS evaluates cumulative distribution functions. An ensemble of forecasts can easily be converted into a piecewise constant cumulative distribution function with steps at the ensemble members. This renders the CRPS a convenient scoring rule for the evaluation of ‘raw’ ensembles, obviating the need for sophisticated ensemble model output statistics or dressing methods prior to evaluation. In this article, a relation between the CRPS score and the quantile score is established. The evaluation of ‘raw’ ensembles using the CRPS is discussed in this light. It is shown that latent in this evaluation is an interpretation of the ensemble as quantiles but with non-uniform levels. This needs to be taken into account if the ensemble is evaluated further, for example with rank histograms.