This paper proposes a generalized Phillips curve in order to forecast Brazilian inflation over the 2003:M1–2013:M10 period. To this end, we employ the Dynamic Model Averaging (DMA) method, which allows for both model evolution and time-varying parameters. The procedure mainly consists in state-space representation and by Kalman filter estimation. Overall, the dynamic specifications deliver good inflation predictions for all the forecast horizons considered, underscoring the importance of time-varying features for forecasting exercises. As to the usefulness of the predictors on explaining the Brazilian inflation, there are evidences that the short- and long-term Phillips curve relationship may be rejected for Brazil while short- and medium-term exchange rate pass-through apparently has been decreasing in the last years.
Keywords:
Phillips Curve; Inflation; Forecast; Time-Varying Parameter
Notes: UNEMP = unemployment rate; CPU = industrial capacity utilization; GDP = real GDP growth; NER = nominal exchange rate; INFEXP = inflation expectations (t + 1); STIR = short-term interest rate; COMPRICE = commodities price index; IPI = import price index.
Notes: UNEMP = unemployment rate; CPU = industrial capacity utilization; GDP = real GDP growth; NER = nominal exchange rate; INFEXP = inflation expectations (t + 1); STIR = short-term interest rate; COMPRICE = commodities price index; IPI = import price index.
Notes: UNEMP = unemployment rate; CPU = industrial capacity utilization; GDP = real GDP growth; NER = nominal exchange rate; INFEXP = inflation expectations (t + 1); STIR = short-term interest rate; COMPRICE = commodities price index; IPI = import price index.
