Asymmetric Quantile Persistence and Predictability: The Case of U.S. Inflation

Abstract

The aim of this paper is to investigate the evidence and implications of time-variation and asymmetry in the persistence of U.S. inflation. We evaluate these features by comparing the out-of-sample forecast performance of two specifications, a Quantile Auto-Regressive (QAR) model and a parametric Auto-Regressive (AR) model in which the volatility of the errors depends on the level of inflation. The results of the comparison show that the parametric quantile forecasts are at least as accurate as the semi-parametric QAR model, in particular for the core inflation measures. This leads us to conclude that the persistence of core inflation can be considered constant and high, but declined for the headline inflation measures. In addition, we find that the recent findings of asymmetric persistence of inflation shocks can be mostly attributed to the positive relation between inflation level and its volatility.