Gradient wild bootstrap for instrumental variable quantile regressions with weak and few clusters

• Main Authors: WANG, Wenjie, ZHANG, Yichong
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2024
• Subjects: Gradient wild bootstrap; Weak instruments; Clustered data; Randomization test; Instrumental variable quantile regression; Econometrics; Multivariate Analysis; Numerical Analysis and Scientific Computing
• Online Access: https://ink.library.smu.edu.sg/soe_research/2788; https://ink.library.smu.edu.sg/context/soe_research/article/3787/viewcontent/2408.10686v1.pdf
• Institution: Singapore Management University

We study the gradient wild bootstrap-based inference for instrumental variable quantile regressions in the framework of a small number of large clusters in which the number of clusters is viewed as fixed, and the number of observations for each cluster diverges to infinity. For the Wald inference, w...