50 resultados para évaluation directe

em CentAUR: Central Archive University of Reading - UK


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A new approach is presented that simultaneously deals with Misreporting and Don't Know (DK) responses within a dichotomous-choice contingent valuation framework. Utilising a modification of the standard Bayesian Probit framework, a Gibbs with Metropolis-Hastings algorithm is used to estimate the posterior densities for the parameters of interest. Several model specifications are applied to two contingent valuation datasets: one on wolf management plans, and one on the US Fee Demonstration Program. We find that DKs are more likely to be from people who would be predicted to have positive utility for the bid. Therefore, a DK is more likely to be a YES than a NO. We also find evidence of misreporting, primarily in favour of the NO option. The inclusion of DK responses has an unpredictable impact on willingness-to-pay estimates, since it impacts differently on the results for the two datasets we examine. Copyright (C) 2009 John Wiley & Sons, Ltd.

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This paper presents the method and findings of a contingent valuation (CV) study that aimed to elicit United Kingdom citizens' willingness to pay to support legislation to phase out the use of battery cages for egg production in the European Union (EU). The method takes account of various biases associated with the CV technique, including 'warm glow', 'part-whole' and sample response biases. Estimated mean willingness to pay to support the legislation is used to estimate the annual benefit of the legislation to UK citizens. This is compared with the estimated annual costs of the legislation over a 12-year period, which allows for readjustment by the UK egg industry. The analysis shows that the estimated benefits of the legislation outweigh the costs. The study demonstrates that CV is a potentially useful technique for assessing the likely benefits associated with proposed legislation. However, estimates of CV studies must be treated with caution. It is important that they are derived from carefully designed surveys and that the willingness to pay estimation method allows for various biases. (C) 2003 Elsevier Science B.V. All rights reserved.

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An increasing set of evidence has been reported on how consumers could potentially react to the introduction of genetically modified food. Studies typically contain some empirical evidence and some theoretical explanations of the data, however, to date limited effort has been posed on systematically reviewing the existing evidence and its implications for policy. This paper contributes to the literature by bringing together the published evidence on the behavioural frameworks and evidence on the process leading to the public acceptance of genetically modified (GM) food and organisms (GMOs). In doing so, we employ a set of clearly defined search tools and a limited number of comprehensive key words. The study attempts to gather an understanding of the published findings on the determinants of the valuation of GM food - both in terms of willingness to accept and the willing-to-pay a premium for non-GM food, trust with information sources on the safety and public health and ultimate attitudes underpinning such evidence. Furthermore, in the light of such evidence, we formulate some policy strategies to deal with public uncertainly regarding to GMOs and, especially GM food. (c) 2007 Elsevier Ltd. All rights reserved.

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This study analyzes the issue of American option valuation when the underlying exhibits a GARCH-type volatility process. We propose the usage of Rubinstein's Edgeworth binomial tree (EBT) in contrast to simulation-based methods being considered in previous studies. The EBT-based valuation approach makes an implied calibration of the pricing model feasible. By empirically analyzing the pricing performance of American index and equity options, we illustrate the superiority of the proposed approach.

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