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Forecasting by factors, by variables, by both or neither?

Abstract:

We consider forecasting with factors, variables and both, modeling in-sample using Autometrics so all principal components and variables can be included jointly, while tackling multiple breaks by impulse-indicator saturation. A forecast-error taxonomy for factor models highlights the impacts of location shifts on forecast-error biases. Forecasting US GDP over 1-, 4- and 8-step horizons using the dataset from Stock and Watson (2009) updated to 2011:2 shows factor models are more useful for now...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1016/j.jeconom.2013.04.015

Authors


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Institution:
University of Oxford
Division:
SSD
Department:
Economics
Role:
Author
More by this author
Institution:
University of Oxford
Division:
SSD
Department:
Economics
Sub department:
EMOD
Role:
Author
Publisher:
Elsevier
Journal:
Journal of Econometrics More from this journal
Volume:
177
Issue:
2
Pages:
305-319
Publication date:
2013-04-17
DOI:
ISSN:
0304-4076
Keywords:
Pubs id:
pubs:403061
UUID:
uuid:fe19b17e-fdcc-42dd-99ee-d9655398cb12
Local pid:
pubs:403061
Source identifiers:
403061
Deposit date:
2016-12-16

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