We investigate the probability forecasting performance of a three-regime dynamic ordered probit model framework …-parametric dating algorithm for the identification of these three phases. We compare the pseudo-out-of-sample forecasting skills of an …-Operating-Characteristic (ROC) Kurve sowie zwei dazugehörige statistische Maße berechnet. …

and assess relative model performance based on the receiver operating characteristic (ROC) curve. While the Treasury term … significantly improve the precision of recession predictions, especially at horizons further out than one year. …

shapes and find the less frequent shapes intrinsically linked to the recessions in the post-WWII data. In forecasting … indicator than the spreads in studying the term structure. Key words: Business cycle, recession forecast, U.S. Treasury yield …

and assess relative model performance based on the receiver operating characteristic (ROC) curve. While the Treasury term … significantly improve the precision of recession predictions, especially at horizons further out than one year …

forecasting tool for business cycle turning points, includes several financial components. However, we argue that the coverage of … leading credit index can be helpful to estimate recession probabilities better than individual indicators, including some of …

Factor Forests (DFF) for macroeconomic forecasting, which synthesize the recent machine learning, dynamic factor model and … proposed in Zeileis, Hothorn and Hornik (2008). DFTs and DFFs are non-linear and state-dependent forecasting models, which … powerful tree-based machine learning ensembles conditional on the state of the business cycle. The out-of-sample forecasting …

ambition, or COVID-19 induced recession; it is China's fast acceleration in becoming a game changer in the world order that the …