In this paper we employ an autoregressive GARCH-in-mean-level process with variable coefficients to forecast inflaation and investigate the behavior of its persistence in the United States. We propose new measures of time varying persistence, which not only distinguish between changes in the dynamicsof inflation and its volatility, but are also allow for feedback between the two variables. Since it is clear from our analysis that predictability is closely interlinked with (first-order) persistence we coin the term persistapredictability. Our empirical results suggest that the proposed model has good forecasting properties.

(2022). Forecasting Inflation: A GARCH-in-Mean-Level Model with Time Varying Predictability [working paper]. Retrieved from http://hdl.handle.net/10446/212692

Forecasting Inflation: A GARCH-in-Mean-Level Model with Time Varying Predictability

Zanetti Chini, Emilio
2022

Abstract

In this paper we employ an autoregressive GARCH-in-mean-level process with variable coefficients to forecast inflaation and investigate the behavior of its persistence in the United States. We propose new measures of time varying persistence, which not only distinguish between changes in the dynamicsof inflation and its volatility, but are also allow for feedback between the two variables. Since it is clear from our analysis that predictability is closely interlinked with (first-order) persistence we coin the term persistapredictability. Our empirical results suggest that the proposed model has good forecasting properties.
Canepa, Alessandra; Karanasos, M; Paraskevopoulos, A. G.; Zanetti Chini, Emilio
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/10446/212692
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