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Exploring Benefit Transfer: Disamenities of Waste Transfer Stations

机译：探索利益转移：废物转移站的弊端

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摘要

The benefit transfer method was developed as an alternative way to value externalities using values from studies of similar circumstances, carried out at similar sites somewhere else, given the challenges and high costs inherent in assessing the actual cost. Specifically, in order to test the performance of the benefit transfer method, employing hedonic price models, this study focused on estimates of disamenities associated with waste transfer stations at four different cities in Israel. The sites were intentionally selected to represent a variety of circumstances. We transferred the estimated benefit function from a "study site" to a "policy site". The goodness of fit was examined by comparing the calculated value, with actual data from the policy site. To test the sensitivity of the benefit transfer function to socioeconomic and housing characteristics, it was repeatedly applied to different sets of observations. The findings suggest that a relatively large number of alternative benefit functions are transferable. Statistical inequality outcome regarding the degree of similarity between samples does not unequivocally rule out the appropriateness of transferring environmental values across studies. Transfer errors varied between -21% and +29%, and the absolute average error for all transfers was 15.4%. Errors were lower for transfer between relatively similar cities in terms of size and location and between sub-samples that were similar in socioeconomic characteristics and housing type. However, when a site with very dissimilar data was involved, the average absolute error rose to 19%.
机译：受益于评估实际成本所固有的挑战和高成本，利益转移方法被开发为一种使用对类似情况进行研究的价值对外部性进行估值的替代方法，该研究是在其他地方的类似地点进行的。具体来说，为了测试采用享乐价格模型的收益转移方法的性能，本研究着重于与以色列四个不同城市的废物转移站相关的不满估计。故意选择了这些地点以代表各种情况。我们将估计利益函数从“研究站点”转移到“政策站点”。通过将计算值与策略站点的实际数据进行比较，检验了拟合优度。为了检验利益转移函数对社会经济和住房特征的敏感性，将其反复应用于不同的观察结果。研究结果表明，相对大量的替代利益函数是可以转移的。关于样本之间的相似程度的统计不平等结果并未明确地排除在研究之间转移环境价值的适当性。传输误差在-21％到+ 29％之间变化，所有传输的绝对平均误差为15.4％。就规模和位置而言，相对相似的城市之间以及在社会经济特征和住房类型相似的子样本之间进行转移时，误差较小。但是，当涉及到数据非常不同的站点时，平均绝对误差上升到19％。

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