Forecasting inflation using univariate continuous‐time stochastic models
Journal of Forecasting | Wiley | Published : 2020
In this paper we investigate the applicability of several continuous‐time stochastic models to forecasting inflation rates with horizons out to twenty years. While the models are well‐known, new methods of parameter estimation and forecasts are supplied, leading to rigorous testing of out‐of‐sample inflation forecasting at short and long time horizons. Using US CPI data we find that over longer forecasting horizons, i.e. those beyond five years, the lognormal index model having Ornstein‐Uhlenbeck drift rate provides the best forecasts.
This research is supported by an Australian Government Research Training Program Scholarship.