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Modeling self-censoring of polluter pays protest votes in stated preference research to support resource damage estimations in environmental liability

机译:在确定的偏好研究中,对污染者的自我审查模型进行建模会引起抗议,以支持对环境责任中资源损害的估计

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摘要

The identification and treatment of protest response in stated preference (SP) research such as contingent valuation is an underdeveloped area. Protest related to the polluter pays principle (PPP) is expected to pose an important hurdle to the application of SP research in environmental liability claims, for instance under the European Environmental Liability Directive. Our main objective is to test the effect of PPP induced protest votes on welfare measures for lost passive use value using different treatment procedures. We argue for a more reliable and defensible indicator of willingness to pay (WTP) in environmental liability litigation cases than current standard removal practices in cases where protest votes affect sample representativeness. Analyzing the impact of PPP-based protest response on WTP values with the help of a Full Information Maximum Likelihood sample selection model, a significant correlation is found between the decision to participate in the CV market and the WTP bids. Self-censoring biases average WTP and is correlated with factors such as respondent use of the resource and disposition towards its future protection. Simply removing protest response from the sample is indefensible and results in a biased estimation of WTP.
机译:在陈述优先(SP)研究(例如或有估值)中识别和处理抗议响应是一个不发达的领域。与污染者付费原则(PPP)有关的抗议活动有望对SP研究在环境责任索赔中的应用构成重要障碍,例如,根据欧洲环境责任指令。我们的主要目标是使用不同的处理程序,测试PPP引发的抗议投票对失去被动使用价值的福利措施的影响。我们主张在环境责任诉讼案件中,有更可靠,更具辩护性的支付意愿(WTP)指标,而在抗议投票影响样本代表性的情况下,该指标要比当前的标准清除做法更为合理。在完全信息最大似然样本选择模型的帮助下,分析基于PPP的抗议响应对WTP值的影响,发现参与CV市场的决定与WTP出价之间存在显着相关性。自我审查会使平均WTP产生偏差,并且与诸如响应者对资源的使用以及对未来保护的处置等因素相关。简单地从样本中删除抗议响应是无法辩护的,并且会导致WTP的估算偏差。

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