The lack of longitudinal studies of the relationship between the built environment and travel behavior has been widely discussed in the literature. This paper discusses how standard propensity score matching estimators can be extended to enable such studies by pairing observations across two dimensions: longitudinal and cross-sectional. Researchers mimic randomized controlled trials (RCTs) and match observations in both dimensions, to find synthetic control groups that are similar to the treatment group and to match subjects synthetically across before-treatment and after-treatment time periods. We call this a two-dimensional propensity score matching (2DPSM). This method demonstrates superior performance for estimating treatment effects based on Monte Carlo evidence. A near-term opportunity for such matching is identifying the impact of transportation infrastructure on travel behavior.

中文翻译：

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纵向准实验研究的二维倾向得分匹配方法：关注旅行行为和建筑环境

文献中广泛讨论了缺乏对建成环境与出行行为之间关系的纵向研究。本文讨论了如何通过将纵向和横截面两个维度的观察配对来扩展标准倾向得分匹配估计量以实现此类研究。研究人员模仿随机对照试验 (RCT) 并匹配两个维度的观察结果，以找到与治疗组相似的合成对照组，并在治疗前和治疗后的时间段内综合匹配受试者。我们称之为二维倾向得分匹配（2DPSM）。该方法展示了基于蒙特卡罗证据估计治疗效果的优越性能。