for forecasting business cycle turning points. When we allow for asymmetry in the long-run volatility component, we find …

One of the most robust stylized facts in macroeconomics is the forecasting power of the term spread for future real … activity. The economic rationale for this forecasting power usually appeals to expectations of future interest rates, which … affect the slope of the term structure. In this paper, we propose a possible causal mechanism for the forecasting power 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 …

the most relevant recent developments in this field of economic forecasting. To begin with, we analyze the problem of … resulting leading indicator based forecasts, and review the recent literature on the forecasting performance of leading …