论文标题
多元连续处理的因果效应估计
Causal Effect Estimation for Multivariate Continuous Treatments
论文作者
论文摘要
因果推论在各个领域（例如生物学，心理学和经济学等）中广泛使用。在观察性研究中，我们需要在估计因果效应之前平衡协变量。这项研究将一维熵平衡方法扩展到多个维度，以平衡协变量。提出了参数方法和非参数方法，以估算多变量连续处理的因果效应以及两种估计的理论特性。此外，模拟结果表明，在各种情况下，所提出的方法比其他方法更好。最后，我们应用方法来分析吸烟持续时间和频率对医疗支出的影响。结果表明，吸烟的频率大大增加了医疗支出，而吸烟的持续时间却没有。
Causal inference is widely used in various fields, such as biology, psychology and economics, etc. In observational studies, we need to balance the covariates before estimating causal effect. This study extends the one-dimensional entropy balancing method to multiple dimensions to balance the covariates. Both parametric and nonparametric methods are proposed to estimate the causal effect of multivariate continuous treatments and theoretical properties of the two estimations are provided. Furthermore, the simulation results show that the proposed method is better than other methods in various cases. Finally, we apply the method to analyze the impact of the duration and frequency of smoking on medical expenditure. The results show that the frequency of smoking increases medical expenditure significantly while the duration of smoking does not.
