Uniform Inference for Parameters Identified by Conditional Quantile Restrictions
The paper develops methods for uniform inference when testing parameters using conditional quantile restrictions. It shows that penalized statistics converge uniformly to a limiting process plus a deterministic drift term, establishing consistency and providing robust tools for testing parameter restrictions across different quantile indices in complex models.