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

Citation

Hecq, A and Jacobs, JPAM and Stamatogiannis, MP, Testing for news and noise in non-stationary time series subject to multiple historical revisions, Journal of Macroeconomics, 60 pp. 396-407. ISSN 0164-0704 (2019) [Refereed Article]

Copyright Statement

Copyright 2019 Published by Elsevier Inc.

DOI: doi:10.1016/j.jmacro.2019.03.003

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 Details

Item Type:Refereed Article
Keywords:data revision, cointegration, news-noise tests, outlier detection
Research Division:Economics
Research Group:Econometrics
Research Field:Economic Models and Forecasting
Objective Division:Economic Framework
Objective Group:Macroeconomics
Objective Field:Macroeconomics not elsewhere classified
UTAS Author:Jacobs, JPAM (Dr Jan Jacobs)
ID Code:134091
Year Published:2019
Deposited By:Economics and Finance
Deposited On:2019-07-25
Last Modified:2020-01-10
Downloads:0

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