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Measuring predictability: theory and macroeconomic applications

Author

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  • Francis X. Diebold
  • Lutz Kilian

Abstract

The authors 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 stationary or nonstationary data. The authors propose a simple estimator and suggest resampling methods for inference. They then provide several macroeconomic applications. First, on the basis of fitted parametric models, the authors assess the predictability of a variety of macroeconomic series. Second, they analyze the internal propagation mechanism of a standard dynamic macroeconomic model by comparing predictability of model inputs and model outputs. Third, they use predictability as a metric for assessing the similarity of data simulated from the model and actual data. Finally, the authors sketch several promising directions for future research.

Suggested Citation

  • Francis X. Diebold & Lutz Kilian, 1997. "Measuring predictability: theory and macroeconomic applications," Working Papers 97-23, Federal Reserve Bank of Philadelphia.
  • Handle: RePEc:fip:fedpwp:97-23
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    References listed on IDEAS

    as
    1. Francis X. Diebold & Lee E. Ohanian & Jeremy Berkowitz, 1998. "Dynamic Equilibrium Economies: A Framework for Comparing Models and Data," Review of Economic Studies, Oxford University Press, vol. 65(3), pages 433-451.
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    11. Atsushi Inoue & Lutz Kilian, 2002. "Bootstrapping Smooth Functions of Slope Parameters and Innovation Variances in VAR (∞) Models," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 43(2), pages 309-332, May.
    12. Stephen G. Cecchetti, 1995. "Inflation Indicators and Inflation Policy," NBER Chapters, in: NBER Macroeconomics Annual 1995, Volume 10, pages 189-236, National Bureau of Economic Research, Inc.
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      • Diebold, F.X. & Kilian, L. & Nerlove, Marc, 2006. "Time Series Analysis," Working Papers 28556, University of Maryland, Department of Agricultural and Resource Economics.
    14. Francis X. Diebold & Marc Nerlove, 1988. "Unit roots in economic time series: a selective survey," Finance and Economics Discussion Series 49, Board of Governors of the Federal Reserve System (U.S.).
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    More about this item

    Keywords

    Forecasting;

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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