Forecasting and tracking real-time data revisions in inflation persistence

Heather Tierney

MPRA Paper from University Library of Munich, Germany

Abstract: This paper presents three local nonparametric forecasting methods that are able to utilize the isolated periods of revised real-time PCE and core PCE for 62 vintages within a historic framework with respect to the nonparametric exclusion-from-core inflation persistence model. The flexibility, provided by the kernel and window width, permits the incorporation of the forecasted value into the appropriate time frame. For instance, a low inflation measure can be included in other low inflation time periods in order to form more optimal forecasts by combining values that are similar in terms of metric distance as opposed to chronological time. The most efficient nonparametric forecasting method is the third model, which uses the flexibility of nonparametrics to its utmost by making forecasts conditional on the forecasted value.

Keywords: Inflation Persistence; Real-Time Data; Monetary Policy; Nonparametrics; Forecasting (search for similar items in EconPapers)
JEL-codes: C14 C53 E52 (search for similar items in EconPapers)
Date: 2011-11-01
New Economics Papers: this item is included in nep-cba, nep-ecm, nep-for and nep-mon
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https://mpra.ub.uni-muenchen.de/34439/1/MPRA_paper_34439.pdf original version (application/pdf)

Related works:
Working Paper: Forecasting and Tracking Real-Time Data Revisions in Inflation Persistence (2013)
Working Paper: Forecasting and Tracking Real-Time Data Revisions in Inflation Persistence (2013)
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Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:34439

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