Optimizing Time-series Forecasts For Inflation And Interest Rates Using Simulation And Model Averaging

Motivated by economic-theory concepts - the Fisher hypothesis and the theory of the term structure - the authors consider a small set of simple bivariate closed-loop time-series models for the prediction of price inflation and of long- and short-term interest rates. The set includes Vector AutoRegressions (VAR) in levels and in differences, a cointegrated VAR, and a non-linear VAR with threshold cointegration based on data from Germany, Japan, UK, and the U.S. Following a traditional comparative evaluation of predictive accuracy, they subject all structures to a mutual validation using parametric bootstrapping. Ultimately, they utilize the recently developed technique of Mallows model averaging to explore the potential of improving upon the predictions through combinations.