2021/11/21 by Majed Dodin, Dodin, Majed
Biochemistry, Genetics and Molecular Biology · Decision Sciences · Mathematics · #Econometrics (econ.EM) #FOS: Economics and business #Genetic and phenotypic traits in livestock #Optimal Experimental Design Methods #Statistical Methods and Inference
paper · pdf · doi:10.48550/arxiv.2111.10713
openalex publication_date 2021/11/21 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
We propose a method to remedy finite sample coverage problems and improve upon the efficiency of commonly employed procedures for the construction of nonparametric confidence intervals in regression kink designs. The proposed interval is centered at the half-length optimal, numerically obtained linear minimax estimator over distributions with Lipschitz constrained conditional mean function. Its construction ensures excellent finite sample coverage and length properties which are demonstrated in a simulation study and an empirical illustration. Given the Lipschitz constant that governs how much curvature one plausibly allows for, the procedure is fully data driven, computationally inexpensive, incorporates shape constraints and is valid irrespective of the distribution of the assignment variable.