  The literature on using yield curves to forecast recessions typically
measures the term spread as the difference between the 10-year and the
three-month Treasury rates. Furthermore, using the term spread constrains the
long- and short-term interest rates to have the same absolute effect on the
recession probability. In this study, we adopt a machine learning method to
investigate whether the predictive ability of interest rates can be improved.
The machine learning algorithm identifies the best maturity pair, separating
the effects of interest rates from those of the term spread. Our comprehensive
empirical exercise shows that, despite the likelihood gain, the machine
learning approach does not significantly improve the predictive accuracy, owing
to the estimation error. Our finding supports the conventional use of the
10-year--three-month Treasury yield spread. This is robust to the forecasting
horizon, control variable, sample period, and oversampling of the recession
observations.
