Quantile forecasts of inflation under model uncertainty

Bayesian model averaging (BMA) methods are regularly used to deal with model uncertainty in regression models. This paper shows how to introduce Bayesian model averaging methods in quantile regressions, and allow for different predictors to affect different quantiles of the dependent variable. I show that quantile regression BMA methods can help reduce uncertainty regarding outcomes of future inflation by providing superior predictive densities compared to mean regression models with and without BMA.

'Modern' Phillips Curves and the Implications For The Statistical Process of Inflation

'Modern' theories of the Phillips curve imply that inflation is an integrated, or near integrated process. This paper explains this implication and why these 'modern' theories are logically inconsistent with what is commonly known about the statistical process of inflation.