2024/03/01 by Sukjin Han, Adam McCloskey, Han, Sukjin +1
Mathematics · #Advanced Statistical Methods and Models #Econometrics (econ.EM) #FOS: Economics and business
paper · pdf · doi:10.48550/arxiv.2403.00422
openalex publication_date 2024/03/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Interval identification of parameters such as average treatment effects, average partial effects and welfare is particularly common when using observational data and experimental data with imperfect compliance due to the endogeneity of individuals' treatment uptake. In this setting, the researcher is typically interested in a treatment or policy that is either selected from the estimated set of best-performers or arises from a data-dependent selection rule. In this paper, we develop new inference tools for interval-identified parameters chosen via these forms of selection. We develop three types of confidence intervals for data-dependent and interval-identified parameters, discuss how they apply to several examples of interest and prove their uniform asymptotic validity under weak assumptions.