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

52 Pages Posted: 8 Jan 2013

See all articles by Jon Faust

Jon Faust

Board of Governors of the Federal Reserve System

Simon Gilchrist

National Bureau of Economic Research (NBER)

Jonathan H. Wright

Johns Hopkins University - Department of Economics

Egon Zakrajšek

Federal Reserve Bank of Boston

Multiple version iconThere are 2 versions of this paper

Date Written: October 23, 2012

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.

Keywords: Forecasting, real-time data, Bayesian Model Averaging, credit spreads

JEL Classification: C11, C53

Suggested Citation

Faust, Jon and Gilchrist, Simon and Wright, Jonathan H. and Zakrajšek, Egon, Credit Spreads as Predictors of Real-Time Economic Activity: A Bayesian Model-Averaging Approach (October 23, 2012). FEDS Working Paper No. 2012-77, Available at SSRN: https://ssrn.com/abstract=2197492 or http://dx.doi.org/10.2139/ssrn.2197492

Jon Faust

Board of Governors of the Federal Reserve System ( email )

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Simon Gilchrist

National Bureau of Economic Research (NBER)

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Jonathan H. Wright

Johns Hopkins University - Department of Economics ( email )

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Egon Zakrajšek (Contact Author)

Federal Reserve Bank of Boston ( email )

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Boston, MA 02210
United States

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