Can the Term Spread Predict Output Growth and Recessions? A Survey of the Literature

By David C. Wheelock, M. Wohar. 2009

227 citations recorded by the source corpus.

This article surveys recent research on the usefulness of the term spread (i.e., the difference between the yields on long-term and short-term Treasury securities) for predicting changes in economic activity. Most studies use linear regression techniques to forecast changes in output or dichotomous choice models to forecast recessions. Others use time-varying parameter models, such as Markov-switching models and smooth transition models, to account for structural changes or other nonlinearities. Many studies find that the term spread predicts output growth and recessions up to one year in advance, but several also find its usefulness varies across countries and over time. In particular, many studies find that the ability of the term spread to forecast output growth has diminished in recent years, although it remains a reliable predictor of recessions.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/82966dad6c71ca8797415f3817e042f53a5c83d9

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Citations in the corpus

Do Credit Shocks Matter? A Global Perspective (2010, background): “A number of studies discuss the predictive value of interest rates for output fluctuations and the timing of recessions and recoveries (see Wheelock and Wohar, 2009).”
The Impact of Unconventional Monetary Policy on Firm Financing Constraints: Evidence from the Maturity Extension Program (2015, unknown): “Indeed, because movements in the term spread generally reflect broader factors, such as expected business cycle movements or consumption smoothing motives, which might also shape firm behavior, distinguishing the direct impact of the term spread on firm behavior and asset prices from these broader f”
Variance and Skewness in Density Predictions: A World GDP Growth Forecast Assessment (2017, unknown): “This is in line with the following authors: Harvey (1989), Estrella and Hardouvelis (1991), Haubrich and Dombrosky (1996), Stock and Watson (2003), Wheelock and Wohar (2009), Aretz and Peel (2010), and Kao, Kuan, and Chen (2013), among others.”
Generalized Forecast Error Variance Decomposition for Linear and Nonlinear Multivariate Models (2014, unknown): “In particular, the term spread above has often been found the best leading indicator in the surveys of Stock and Watson (2003) and Wheelock and Wohar (2009), and Estrella (2005) for a rational expectations model that justi es the predictive power of the term spread by expectations of future…”