Abstract
This paper presents a new procedure for forecasting recessions utilizing short-term (slope) dynamics present in the yield curve. Building on a large body of literature chronicling the relationship between the shape of the yield curve and the business cycle, this paper employs Dynamic Nelson-Siegel modeling to define the level, slope, and curvature characteristics of the term structure through time. Given these dynamics, the trend and cycle are extracted using various decomposition techniques. It is shown that cycles present within the slope factor are very robust predictors of recessions, correctly identifying recessions as much as eighteen months in advance. A “Predictive Power Score” is developed to quantify the procedure’s performance. This score shows the superiority of the procedure over other common leading indicators including the yield spread.
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