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Testing for news and noise in non-stationary time series subject to multiple historical revisions

Hecq, A, Jacobs, JPAM and Stamatogiannis, MP 2019 , 'Testing for news and noise in non-stationary time series subject to multiple historical revisions' , Journal of Macroeconomics, vol. 60 , pp. 396-407 , doi: 10.1016/j.jmacro.2019.03.003.

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Abstract

This paper focuses on testing non-stationary real-time data for forecastability, i.e., whether data revisions reduce noise or are news, by putting data releases in vector-error correction forms. To deal with historical revisions which affect the whole vintage of time series due to redefinitions, methodological innovations etc., we employ the recently developed impulse indicator saturation approach, which involves potentially adding an indicator dummy for each observation to the model. We illustrate our procedures with the U.S. real GNP/GDP series of the Federal Reserve Bank of Philadelphia and find that revisions to this series neither reduce noise nor can be considered as news.

Item Type: Article
Authors/Creators:Hecq, A and Jacobs, JPAM and Stamatogiannis, MP
Keywords: data revision, cointegration, news-noise tests, outlier detection
Journal or Publication Title: Journal of Macroeconomics
Publisher: Louisiana State Univ Pr
ISSN: 0164-0704
DOI / ID Number: 10.1016/j.jmacro.2019.03.003
Copyright Information:

Copyright 2019 Published by Elsevier Inc.

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