Working Paper: CEPR ID: DP8896
Authors: Maximo Camacho; Gabriel Pérez-Quirós; Pilar Poncela
Abstract: To perform real-time business cycle inferences and forecasts of GDP growth rates in the Euro area, we use an extension of the Markov-switching dynamic factor models that accounts for the specificities of the day to day monitoring of economic developments such as ragged edges, mixed frequencies and data revisions. We provide examples that show the nonlinear nature of the relations between data revisions, point forecasts and forecast uncertainty. According to our empirical results, we think that the real-time probabilities of recession inferred from the model are an appropriate statistic to capture what the press call green shoots or to monitor the double-dip recession
Keywords: business cycles; time series; turning points
JEL Codes: C22; E27; E32
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| Markov-switching dynamic factor model (E17) | recession probabilities (E37) |
| recession probabilities (E37) | monitoring business cycles (E32) |
| Markov-switching dynamic factor model (E17) | tracking business cycle turning points (E32) |
| recession probabilities (E37) | actual economic downturns (F44) |
| recession probabilities (E37) | potential double-dip recessions (F44) |