- Journal Article
This study systematically broadens the relevance of possible model performance asymmetries across business cycles in the spirit of the recent state-dependent forecast evaluation literature (e.g. Chauvet & Potter, 2013) to hundreds of macroeconomic indicators and deepens the forecast evaluation of the recent factor model literature on hundreds of target variables (e.g. Stock & Watson, 2012b) in a state-dependent manner. Our results are consistent with both strands of the literature and generalize the former to over 200 macroeconomic indicators and differentiate the latter across three levels of temporal granularity: We document systematic model performance differences in both absolute and relative terms across business cycles (longitudinal) as well as across variable groups (cross-sectional) and find these performance differences to be robust across several alternative specifications. The cross-sectional prevalence and robustness of state dependency shown in this article encourages economic forecasters to complement model performance assessments with astate-dependent evaluation of predictive ability. Show more
Journal / seriesJournal of Forecasting
Pages / Article No.
Subjectbig macroeconomic data sets; business cycle asymmetries; dynamic factor models; forecast evaluation; USA
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