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Analyzing car ownership in Quebec City: a comparison of traditional and latent class ordered and unordered models

机译:分析魁北克市的汽车拥有量:传统和潜在类别有序和无序模型的比较

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摘要

Private car ownership plays a vital role in the daily travel decisions of individuals and households. The topic is of great interest to policy makers given the growing focus on global climate change, public health, and sustainable development issues. Not surprisingly, it is one of the most researched transportation topics. The extant literature on car ownership models considers the influence of exogenous variables to remain the same across the entire population. However, it is possible that the influence of exogenous variable effects might vary across the population. To accommodate this potential population heterogeneity in the context of car ownership, the current paper proposes the application of latent class versions of ordered (ordered logit) and unordered response (multinomial logit) models. The models are estimated using the data from Quebec City, Canada. The latent class models offer superior data fit compared to their traditional counterparts while clearly highlighting the presence of segmentation in the population. The validation exercise using the model estimation results further illustrates the strength of these models for examining car ownership decisions. Moreover, the latent class unordered response models perform slightly better than the latent class ordered response models for the metropolitan region examined.
机译:拥有私家车在个人和家庭的日常出行决策中起着至关重要的作用。鉴于人们越来越关注全球气候变化,公共卫生和可持续发展问题,因此该主题引起了决策者的极大兴趣。毫不奇怪,它是研究最多的运输主题之一。现有的有关汽车所有权模型的文献认为,外生变量的影响在整个人口中保持不变。但是,外源变量效应的影响可能在整个人群中有所不同。为了在汽车拥有的情况下适应这种潜在的人口异质性,本论文提出了有序(有序logit)和无序响应(多项式logit)模型的潜在类版本的应用。使用来自加拿大魁北克市的数据估算模型。与传统同类模型相比,潜在类模型提供了更好的数据拟合性,同时清楚地强调了群体中细分的存在。使用模型估计结果进行的验证练习进一步说明了这些模型在检查汽车拥有权决策方面的优势。此外,对于所研究的大都市区,潜在类无序响应模型的性能略好于潜在类有序响应模型。

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