Construction of Leading Economic Index for Recession Prediction using Vine Copulas

This paper constructs a composite leading index for business cycle prediction based on vine copulas that capture the complex pattern of dependence among individual predictors. This approach is optimal in the sense that the resulting index possesses the highest discriminatory power as measured by the receiver operating characteristic (ROC) curve. The model specification is semi-parametric in nature, suggesting a two-step estimation procedure, with the second-step finite dimensional parameter being estimated by QMLE given the first-step non-parametric estimate. To illustrate its usefulness, we apply this methodology to optimally aggregate the ten leading indicators selected by The Conference Board (TCB) to predict economic recessions in the United States. In terms of both the in-sample and out-of-sample performances, our method is significantly superior to the current Leading Economic Index proposed by TCB. JEL Classifications: C14, C15, C32, C43, C51, C53, E37