Double machine learning with gradient boosting and its application to the Big N audit quality effect
梯度提升双重机器学习及其对大型审计机构质量效应的应用
In this paper, we study the double machine learning (DML) approach of Chernozhukov et al. (2018) for estimating average treatment effect and apply this approach to examine the Big N audit quality effect in the accounting literature. This approach relies on machine learning methods and is suitable when a high dimensional nuisance function with many covariates is present in the model. This approach does not suffer from the “regularization bias” when a learning method with a…