Modelling attribute non-attendance in choice experiments for rural landscape valuation
研究了在陈述偏好调查中如何建模受访者对某些属性不关注的行为，提出了两种方法（潜类模型和贝叶斯随机属性选择），并用爱尔兰景观价值评估数据验证，发现考虑不关注能改善模型拟合且显著改变福利估计。
Non-market effects of agriculture are often estimated using discrete choice models from stated preference surveys. In this context we propose two ways of modelling attribute non-attendance. The first involves constraining coefficients to zero in a latent class framework, whereas the second is based on stochastic attribute selection and grounded in Bayesian estimation. Their implications are explored in the context of a stated preference survey designed to value landscapes in Ireland. Taking account of attribute non-attendance with these data improves fit and tends to involve two attributes one of which is likely to be cost, thereby leading to substantive changes in derived welfare estimates.