Forecasting Inflation in Chile Using State-Space and Regime-Switching Models

The paper estimates two time-varying parameter models of Chilean inflation: a Phillips curve model and a small open economy model. Their out-of-sample forecasts are compared with those of simple Box-Jenkins models. The main findings are; forecasts that include the pre-announced inflation target as a regressor are relatively better; the Phillips curve model outperforms the small open economy model in out-of-sample forecasts; and although Box-Jenkins models outperform the two models for short-term out-of-sample forecasts, their superiority deteriorates in longer forecasts. Adding a Markov-switching process to the models does not explain much of the conditional variance of the forecast errors.