We propose two robust bootstrap-based simultaneous inference methods for time series models featuring time-varying coefficients and conduct an extensive simulation study to assess their performance. Our exploration covers a wide range of scenarios, encompassing serially correlated,...

This paper introduces a new bootstrap approach to the construction of confidence regions for Average Treatment Effect (ATE) identified sets. Minimum Hausdorff distance bootstrap confidence regions are developed and shown to be valid under suitable regularity. A novel measure of the discrepancy...

This paper presents an optimization approach-residual-based bootstrap averaging (RBBA)-for different types of forecast ensembles. Unlike traditional residual-mean-square-error-based ensemble forecast averaging approaches, the RBBA method attempts to find optimal forecast weights in an ensemble...