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

Alessandra Canepa, Menelaos Karanasos (), Athanasios Paraskevopoulos () and Emilio Zanetti Chini ()

Department of Economics and Statistics Cognetti de Martiis. Working Papers from University of Turin

Abstract: In this paper we employ an autoregressive GARCH-in-mean-level process with variable coe¢ cients to forecast in?ation 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 dynamics of in?ation 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 (?rst-order) persistence we coin the term persistapredictability. Our empirical results suggest that the proposed model has good forecasting properties.

Pages: pages 51
Date: 2022-09
New Economics Papers: this item is included in nep-ecm, nep-ets, nep-for and nep-mon
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Persistent link: https://EconPapers.repec.org/RePEc:uto:dipeco:202212

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