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Performance of Markov-Switching GARCH Model Forecasting Inflation Uncertainty

Raihan, Tasneem (2017): Performance of Markov-Switching GARCH Model Forecasting Inflation Uncertainty.

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Abstract

This paper seeks to uncover the non-linear characteristics of uncertainty underlying the US inflation rates over the period 1971-2015 within a regime-switching framework. Accordingly, we employ two variants of a Markov regime-switching GARCH model, one with normally distributed errors (MS-GARCH-N) and another with t-distributed errors (MS-GARCH-t), and compare their relative in-sample as well as out-of-sample performances with those of their standard single-regime counterparts. Consistent with the findings in existing studies, both of our regime-switching models are successful in identifying the year 1984 as the breakpoint in inflation volatility. Among other interesting results is a new finding that the process of switching to the low volatility regime started around April, 1979 and continued until mid 1983. This time frame is matched with the period of aggressive monetary policy changes implemented by the then Fed chairman Paul Volcker. As regards the performance in forecasting uncertainty, for shorter horizons spanning 1 to 5 months, MS-GARCH-N forecasts are found to outperform all other models whereas for 8 to 12-month ahead forecasts MS-GARCH-t appears superior.

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