Accounting for Response Biases in Latent-Class Models for Choices and Attitudes
提出一种校正响应偏差的潜在类别模型，用于分析包含态度问题的条件估值调查，识别不同抗议倾向的受访者类别，并发现忽略偏差会高估意愿支付差异130%。
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 €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%. <i></i>