Hierarchical Gaussian Process Models for Regression Discontinuity/Kink under Sharp and Fuzzy Designs
清晰与模糊断点及折点设计中的层级高斯过程模型
We propose nonparametric Bayesian estimators for causal inference exploiting Regression Discontinuity/Kink (RD/RK) under sharp and fuzzy designs. Our estimators are based on Gaussian Process (GP) regression and classification. The GP methods are powerful probabilistic machine learning approaches that are advantageous in terms of derivative estimation and uncertainty quantification, facilitating RK estimation and inference of RD/RK models. These estimators are extended to…