Credit spreads as predictors of real-time economic activity: a Bayesian Model-Averaging approach

Jon Faust (), Simon Gilchrist, Jonathan Wright and Egon Zakrajšek ()

No 2012-77, Finance and Economics Discussion Series from Board of Governors of the Federal Reserve System (U.S.)

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.

Date: 2012
New Economics Papers: this item is included in nep-ban and nep-for
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Related works:
Journal Article: Credit Spreads as Predictors of Real-Time Economic Activity: A Bayesian Model-Averaging Approach (2013)
Working Paper: Credit Spreads as Predictors of Real-Time Economic Activity: A Bayesian Model-Averaging Approach (2011)
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