A Bayesian instrumental variable model for multinomial choice with correlated alternatives
A Bayesian instrumental variable model for multinomial choice with correlated alternatives
复制标题
具有相关选项的多项选择的贝叶斯工具变量模型
DOI：
10.1016/j.jocm.2023.100400
复制
发表时间：
2023
影响因子：
2.4
通讯作者：
Maruyama Takuya
中科院分区：
文献类型：
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作者：
Watanabe Hajime;Maruyama Takuya
内生性和相关替代是旅游行为分析中需要解决的主要问题。然而，在先进的离散选择模型中很少同时处理这些问题。本研究提出了一种结合工具变量方法的多项概率模型，即多项选择的全参数工具变量模型。该模型具有以下三个特点：(1)允许二元和/或连续内生变量；(2)它允许在每个备选方案中使用任意数量的工具变量；(3)它允许任何选择之间的正相关性和/或负相关性。对于参数估计，我们还提出了一种贝叶斯马尔可夫链蒙特卡罗算法，该算法可以适用于更扩展的模型结构。仿真研究表明，所提出的模型解决了内生性问题，同时允许选择方案之间的相关性。同时，模拟还表明，当感兴趣的内生变量为二值变量时，即使样本量适中，用户也需要注意先验分布的设置。所提出的模型将是一个有用的工具，在这两个内生性和相互关系的选择方案是主要关注的学科。
Endogeneity and correlated alternatives are major concerns to be addressed in travel behavior analysis. However, these issues have rarely been dealt with simultaneously in advanced discrete choice models. This study proposes a multinomial probit model that incorporates the instrumental variable method, namely, a fully parametric instrumental variable model for a multinomial choice. The proposed model has the following three characteristics: (1) it allows binary and/or continuous endogenous variables; (2) it allows any number of instrumental variables in each alternative; and (3) it allows positive and/or negative correlations between any choice alternatives. For parameter estimation, we also propose a Bayesian Markov chain Monte Carlo algorithm that can be accommodated in more extended model structures. The simulation study demonstrates that the proposed model addresses endogeneity while allowing correlations between the choice alternatives. Meanwhile, the simulation also implies that the users need to pay attention to the setting of the prior distribution when an endogenous variable of interest is binary, even if the sample size is moderate. The proposed model will be a useful tool in disciplines in which both endogeneity and correlations between choice alternatives are major concerns.