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Evaluating Exclusion-from-Core Measures of Inflation using Real-Time Data

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Author Info
Tierney, Heather L.R.

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Abstract

Using parametric and nonparametric methods, inflation persistence is examined through the relationship between the exclusions-from-core measure of inflation and total inflation for two sample periods and five in-sample forecast horizons ranging from one to twelve quarters over fifty vintages of real-time data in two measures of inflation: personal consumption expenditure and the consumer price index. This paper finds that core inflation is only able to capture the overall trend of total inflation for the twelve-quarter in-sample forecast horizon using the consumer price index in both the parametric and nonparametric models in the longer sample period. The nonparametric model outperforms the parametric model for both data samples and for all five in-sample forecast horizons.

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File URL: http://mpra.ub.uni-muenchen.de/17856/
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Publisher Info
Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 17856.

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Date of creation: Aug 2009
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Handle: RePEc:pra:mprapa:17856

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Related research
Keywords: Inflation Persistence; Real-Time Data; Monetary Policy; Nonparametrics; In-Sample Forecasting;

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Find related papers by JEL classification:
C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Other Model Applications
C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Semiparametric and Nonparametric Methods
E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy

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  7. Clive W.J. Granger, 2008. "Non-Linear Models: Where Do We Go Next - Time Varying Parameter Models?," Studies in Nonlinear Dynamics & Econometrics, Berkeley Electronic Press, vol. 12(3). [Downloadable!]
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