Probablistic Prediction of the US Great Recession with Historical Expert

Some prominent economic experts have contended that (the early stages of) the Great Recession resembled the Great Depression. In this paper, we utilize an expert-based framework to produce probabilistic projections for output growth and in ation during the recent slump. We divide our US data prior to the Great Recession into ve distinct historical eras. Each expert estimates a vector autoregressive model (VAR) on data from a unique era, with epoch dates re ecting conventional timing assumptions adopted in the economic history literature. We nd that our Great Depression expert performs relatively well in terms of the logarithmic score averaged over the out of sample evaluation period from 2005Q1 to 2010Q4, when compared to a benchmark VAR estimated on Great Moderation data. However, other experts are competitive individually, along with a combination of experts from different eras. Given the Great Depression expert's forecast densities have statistically significant predictive content for output growth and in ation over the evaluation period, we investigate economic significance by adopting a cost-loss ratio approach. We find that the Great Depression expert outperforms the Great Moderation benchmark provided that unanticipated negative output growth events are relatively costly. More generally, for both output growth and for low in ation events, the Great Depression expert fails to beat the benchmark. Unfortunately, the Great Depression expert's projections lack confidence|stemming from the many uncertainties in the Great Depression era. Even for negative output growth events, the Great Depression expert gives too many false alarms. More confident historical experts, such as Bretton Woods, perform better overall. Hence, although the Great Depression helps predict the Great Recession, from a probabilistic perspective, other historical eras have economic relevance.