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Credit Spreads as Predictors of Real-Time Economic Activity: A Bayesian Model-Averaging Approach

Author

Listed:
  • Jon Faust

    (Johns Hopkins University, Federal Reserve Board, and NBER)

  • Simon Gilchrist

    (Boston University and NBER)

  • Jonathan H. Wright

    (Johns Hopkins University and NBER)

  • Egon Zakrajšsek

    (Federal Reserve Board)

Abstract

Employing a large number of financial indicators, we use Bayesian model averaging (BMA) to forecast real-time measures of economic activity. The indicators include credit spreads based on portfolios, constructed directly from the secondary market prices of outstanding bonds, sorted by maturity and credit risk. Relative to an autoregressive benchmark, BMA yields consistent improvements in the prediction of the cyclically sensitive measures of economic activity at horizons from the current quarter out to four quarters hence. The gains in forecast accuracy are statistically significant and economically important and owe almost exclusively to the inclusion of credit spreads in the set of predictors. (No rights reserved. This work was authored as part of the Contributor's official duties as an Employee of the United States Government and is therefore a work of the United States Government. In accordance with 17 U.S.C. 105, no copyright protection is available for such works under U.S. law.)

Suggested Citation

  • Jon Faust & Simon Gilchrist & Jonathan H. Wright & Egon Zakrajšsek, 2013. "Credit Spreads as Predictors of Real-Time Economic Activity: A Bayesian Model-Averaging Approach," The Review of Economics and Statistics, MIT Press, vol. 95(5), pages 1501-1519, December.
  • Handle: RePEc:tpr:restat:v:95:y:2013:i:5:p:1501-1519
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    References listed on IDEAS

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    3. Ben S. Bernanke, 1990. "On the predictive power of interest rates and interest rate spreads," New England Economic Review, Federal Reserve Bank of Boston, issue Nov, pages 51-68.
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    More about this item

    Keywords

    forecasting; real-time data; Bayesian Model Averaging; credit spreads;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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