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Over the Great Moderation period in the United States, we find that corporate credit spreads embed crucial information about the one-year-ahead probability of recession, as evidenced by both in-and out-of-sample fit. Furthermore, the incidence of false positive predictions of recession is dramatically reduced by utilizing a bivariate model that includes a measure of credit spreads along with the slope of the yield curve; indeed, these bivariate models provide much better forecasting performance than any combination of univariate models. We also find that optimal (Bayesian) model combination strongly dominates simple averaging of model forecasts in predicting recessions.
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Stored only when both papers are in the corpus — 49 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
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