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Inconsistent and Lexicographic Choices in Stated Preference Analysis

机译:陈述偏好分析中的不一致和词典选择

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摘要

In stated choice (SC) data inconsistent and lexicographic choice behavior is often observed. It is sometimes recommended to remove data with these characteristics from the analysis. In this paper we reconsider this recommendation. In our data many respondents have inconsistent choice patterns, which appear to be due to incidental mistakes. Moreover, a large number of the consistent respondents have lexicographic choice patterns. We show that the logit model, which is the most popular tool for analyzing SP data, is compatible with inconsistent and seemingly lexicographic choice behavior and that it offers precise predictions about the occurrence of such choices. In the data at our disposal the actual number of respondents who made different choices in two identical choice situations is substantially lower than that predicted by the model, whereas the number of respondents with lexicographic answers is much larger than predicted. The logit model is then ada! pted in various ways to bring it in better agreement with the facts. In particular, we introduce an effect of remembering the earlier choice when the same situation recurs, the presence of latent classes of lexicographic respondents and the presence of heterogeneity among respondents.
机译:在陈述选择(SC)数据中,经常会出现不一致和词典选择行为。有时建议从分析中删除具有这些特征的数据。在本文中,我们重新考虑了该建议。在我们的数据中,许多受访者的选择模式不一致,这似乎是由于偶然的错误造成的。此外,大量一致的受访者具有字典选择模式。我们表明,logit模型是用于分析SP数据的最流行工具,它与不一致且看似按字典顺序排列的选择行为兼容,并且可以为此类选择的发生提供精确的预测。在我们掌握的数据中,在两种相同选择情况下做出不同选择的受访者的实际数量大大低于模型所预测的数量,而具有字典式答案的受访者的数量则比预期的要大得多。这样就可以实现logit模型!以各种方式使其与事实更好地吻合。尤其是,当出现相同情况时,我们会引入一种记忆,即记住较早的选择,潜在的词典编目被访者类别以及被访者之间存在异质性。

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