Time-varying parameter (TVP) models often assume that the TVPs evolve according to a random walk. This assumption, however, might be questionable since it implies coefficients change smoothly and in an unbounded manner. assumption is relaxed by proposing flexible law of motion for large-scale vector autoregressions (VARs). Instead imposing restrictive walk evolution latent states, hierarchical ...