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Accounting for Response Biases in Latent-Class Models for Choices and Attitudes

机译:考虑潜在选择和态度的潜在模型中的响应偏差

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摘要

We propose a latent-class model (LCM) to analyze contingent-valuation surveys incorporating attitudinal questions capturing protest reasons to identify classes of respondents with similar preferences and attitudes. In contrast to a standard LCM, our model ensures that classes are not contaminated by different types of response biases. Using data regarding the preservation of a world-heritage recreation site, low- and high-protester classes are identified. The difference in estimated willingness to pay (WTP) in these classes is (sic)26, reflecting protest issues. If response biases were ignored, different classes would be identified and the corresponding difference in WTPs would be inflated by 130%. (JEL C35, Q51)
机译:我们提出了一个潜在类模型(LCM),以分析包含态度性问题的偶然性价值调查,这些问题捕获了抗议原因,以识别具有相似偏好和态度的应答者类别。与标准LCM相比,我们的模型可确保类别不会受到不同类型的响应偏差的污染。使用有关保护世界遗产娱乐场所的数据,确定了低抗议者和高抗议者的类别。在这些类别中,估计的支付意愿(WTP)的差异为(原文如此)26,反映了抗议问题。如果忽略了响应偏差,则将识别出不同的类别,相应的WTP差异将增加130%。 (JEL C35,Q51)

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