We propose an econometric procedure based mainly on the generalized random forests method. Not only does this process estimate the quantile treatment effect nonparametrically, but our procedure yields a measure of variable importance in terms of heterogeneity among control variables. We also...

In this study, we investigate the estimation and inference on a low-dimensional causal parameter in the presence of high-dimensional controls in an instrumental variable quantile regression. Our proposed econometric procedure builds on the Neyman-type orthogonal moment conditions of a previous...

This study examines the language effect on investing using the Google search records of Chinese- versus English-speaking searchers. First, we find that the attention of Chinese speakers induces that of English speakers, increases abnormal news coverage, and has better predictability on stock...

In this paper, we study the double machine learning (DML) approach of Chernozhukovet 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...

In this paper, we introduce an approach to building classifiers that bifurcate hedge funds into systematic and discretionary funds and evaluate their performance. This approach makes use of textual analysis and statistical learning methods that are free from the subjective judgment of investment...

We propose an econometric procedure based mainly on the generalized random forests method. Not only does this process estimate the quantile treatment effect nonparametrically, but our procedure yields a measure of variable importance in terms of heterogeneity among control variables. We also...

In this study, we investigate the estimation and inference on a low-dimensional causal parameter in the presence of high-dimensional controls in an instrumental variable quantile regression. Our proposed econometric procedure builds on the Neyman-type orthogonal moment conditions of a previous...

In this study, we estimate the effect of industry distress on recovery rates by using the unconditional quantile regression (UQR) proposed in Firpo, Fortin, and Lemieux (2009). The UQR provides better interpretative and thus policy-relevant information on the marginal effect of the covariates...

This paper considers the issues related to the asymptotic properties of estimators and test statistics in linear quantile regression with structural changes. We first address the issue of estimating a single structural change and derive the asymptotic properties of the estimated break point. The...