R2 Bounds for Predictive Models: What Univariate Properties Tell us About Multivariate Predictability
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Publication Date
2019-10-02Journal Title
Journal of Business and Economic Statistic
ISSN
0735-0015
Publisher
Taylor & Francis
Language
English
Type
Article
Metadata
Show full item recordCitation
Robertson, D., Mitchell, J., & Wright, S. (2019). R2 Bounds for Predictive Models: What Univariate Properties Tell us About Multivariate Predictability. Journal of Business and Economic Statistic https://doi.org/10.1080/07350015.2017.1415909
Abstract
A long-standing puzzle in macroeconomic forecasting has been that a wide variety of multivariate models have struggled to out-predict univariate models consistently. We seek an explanation for this puzzle in terms of population properties. We derive bounds for the predictive R2 of the true, but unknown, multivariate model from univariate ARMA parameters alone. These bounds can be quite tight, implying little forecasting gain even if we knew the true multivariate model. We illustrate using CPI inflation data.
Keywords
Autoregressive moving average representations, Forecasting, Macroeconomic models, Nonfundamental representations, Preedictive regressions, Time-varying ARMA
Identifiers
External DOI: https://doi.org/10.1080/07350015.2017.1415909
This record's URL: https://www.repository.cam.ac.uk/handle/1810/279562
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