Yield Spread Selection in Predicting Recession Probabilities: A Machine Learning Approach
Not on the map. Why?
Abstract (arXiv)
The literature on using yield curves to forecast recessions customarily uses 10-year--three-month Treasury yield spread without verification on the pair selection. This study investigates whether the predictive ability of spread can be improved by letting a machine learning algorithm identify the best maturity pair and coefficients. Our comprehensive analysis shows that, despite the likelihood gain, the machine learning approach does not significantly improve prediction, owing to the estimation error. This is robust to the forecasting horizon, control variable, sample period, and oversampling of the recession observations. Our finding supports the use of the 10-year--three-month spread.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 0 of its 32 references that are in the map. First posted on arXiv 23 Jan 2021.
Builds on
0 of 32 references.
No references here yet.
Built on by
Not cited yet.