The relationship between inflation and predictors such as unemployment is potentially nonlinear with a strength that varies over time, prediction errors error may be subject to large, asymmetric shocks. Inspired by these concerns, we develop model for forecasting nonparametric both in the conditional mean using Gaussian Dirichlet processes, respectively. We discuss how features important produc...

The evidence in the inflation forecasting literature suggests that simple time series models are typically hard to outperform in predicting the dynamics of the first moment, and that using information about indicators of economic activity does not lead to out-of-sample forecasting gains. While most of the earlier literature focused on the ability of leading indicators (via the Phillips Curve PC...