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

journal contribution
posted on 2023-05-20, 05:51 authored by Hecq, A, Jacobs, JPAM, Stamatogiannis, MP
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.

History

Publication title

Journal of Macroeconomics

Volume

60

Pagination

396-407

ISSN

0164-0704

Department/School

TSBE

Publisher

Louisiana State Univ Pr

Place of publication

Baton Rouge, USA, La, 70893

Rights statement

Copyright 2019 Published by Elsevier Inc.

Repository Status

  • Restricted

Socio-economic Objectives

Macroeconomics not elsewhere classified

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