A0408
Title: The time-varying evolution of inflation risks
Authors: Anthoulla Phella - University of Glasgow (United Kingdom) [presenting]
Dimitris Korobilis - University of Glasgow (United Kingdom)
Alberto Musso - European Central Bank (Germany)
Bettina Landau - European Central Bank (Germany)
Abstract: A Bayesian quantile regression model with time-varying parameters (TVPs) is developed for forecasting inflation risks. The proposed parametric methodology bridges the empirically established benefits of TVP regressions for forecasting inflation with the ability of quantile regression to model the whole distribution of inflation flexibly. In order to make our approach accessible and empirically relevant for forecasting, we derive an efficient Gibbs sampler by transforming the state-space form of the TVP quantile regression into an equivalent high-dimensional regression form. An application of this methodology points to a good forecasting performance of quantile regressions with TVPs augmented with specific credit and money-based indicators for the prediction of the conditional distribution of inflation in the euro area, both in the short and longer run, and specifically for tail risks.
