Forecasts of key macroeconomic variables may lead to policy changes by governments, central banks and other economic agents. Such policy changes in turn lead to structural changes in macroeconomic time series. We describe this phenomenon in US inflation by introducing a logistic smooth transition autoregressive model where the regime switches depend on the Michigan Inflation Expectation Series. Our results show that (i) forecasts lead to regime changes and have an impact on the level of inflation; (ii) the absorption time of shocks in the forecast of inflation is about four quarters; and (iii) a positive (negative) shock in the forecast results in actions which increase (decrease) the inflation rate.

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Keywords Forecasting, Inflation, Nonlinear time series, Regime switching
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Journal International Journal of Forecasting
Bel, K, & Paap, R. (2016). Modeling the impact of forecast-based regime switches on US inflation. International Journal of Forecasting, 32(4), 1306–1316. doi:10.1016/j.ijforecast.2016.06.002