A Bayesian sample selection model with a binary outcome for handling residential self-selection in individual car ownership

IF 2.8 3区 经济学 Q1 ECONOMICS
Hajime Watanabe , Takuya Maruyama
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引用次数: 0

Abstract

Existing literature has applied the sample selection modeling approach to disentangle the influence of the built environment (BE) and residential self-selection (RSS) on travel behavior. However, a limitation of the existing sample selection models is that they can handle only continuous or ordinal outcomes. The contribution of this study is twofold. First, we develop a sample selection model that can handle binary travel behavior outcomes in the RSS context. When the travel behavior outcome is binary, this approach's potential parameter identification issue can become serious. We employ a non-flat prior and Watanabe-Akaike information criterion in the Bayesian framework to address this issue. Second, we apply this proposed model to travel survey data in Kumamoto City, Japan, to disentangle the BE influence of a neighborhood type and RSS on car ownership. The neighborhood type is defined as the neighborhood being either less than 1,500 m (A) or greater than 1,500 m (B) from a station. We reveal that the true influence of the neighborhood type results in a mere 2.1 percentage point decrease in the car ownership probability. Additionally, we find that the share of the total BE influence (including the RSS influence) owing to RSS on the householder's car ownership is 45.7%. The proposed model is a new and useful tool for quantifying the influence of BE and the relative influence of RSS on binary travel behavior.

二元结果贝叶斯样本选择模型,用于处理个人汽车所有权中的住宅自我选择问题
现有文献采用样本选择建模方法来区分建筑环境(BE)和居民自我选择(RSS)对出行行为的影响。然而,现有样本选择模型的局限性在于只能处理连续或序数结果。本研究有两方面的贡献。首先,我们建立了一个样本选择模型,可以处理 RSS 背景下的二进制旅行行为结果。当旅行行为结果为二元时,这种方法潜在的参数识别问题就会变得严重。我们在贝叶斯框架中采用了非平坦先验和 Watanabe-Akaike 信息准则来解决这一问题。其次,我们将所提出的模型应用于日本熊本市的出行调查数据,以厘清街区类型和 RSS 对汽车保有量的 BE 影响。街区类型被定义为距离车站小于 1,500 米(A)或大于 1,500 米(B)的街区。我们发现,邻里类型的真实影响仅导致汽车拥有概率下降 2.1 个百分点。此外,我们还发现,在整个 BE 影响(包括 RSS 影响)中,RSS 对户主汽车拥有率的影响占 45.7%。所提出的模型是量化 BE 和 RSS 对二元出行行为的相对影响的一个新的有用工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
4.10
自引率
12.50%
发文量
31
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