  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.
