Measuring predictability: theory and macroeconomic applications
Article first published online: 13 DEC 2001
Copyright © 2001 John Wiley & Sons, Ltd.
Journal of Applied Econometrics
Volume 16, Issue 6, pages 657–669, November/December 2001
How to Cite
Diebold, F. X. and Kilian, L. (2001), Measuring predictability: theory and macroeconomic applications. J. Appl. Econ., 16: 657–669. doi: 10.1002/jae.619
- Issue published online: 13 DEC 2001
- Article first published online: 13 DEC 2001
- Manuscript Revised: 5 FEB 2001
- Manuscript Received: 15 JUL 1998
We propose a measure of predictability based on the ratio of the expected loss of a short-run forecast to the expected loss of a long-run forecast. This predictability measure can be tailored to the forecast horizons of interest, and it allows for general loss functions, univariate or multivariate information sets, and covariance stationary or difference stationary processes. We propose a simple estimator, and we suggest resampling methods for inference. We then provide several macroeconomic applications. First, we illustrate the implementation of predictability measures based on fitted parametric models for several US macroeconomic time series. Second, we analyze the internal propagation mechanism of a standard dynamic macroeconomic model by comparing the predictability of model inputs and model outputs. Third, we use predictability as a metric for assessing the similarity of data simulated from the model and actual data. Finally, we outline several non-parametric extensions of our approach. Copyright © 2001 John Wiley & Sons, Ltd.