In this paper, we aim at assessing Markov switching and threshold models in their ability to identify turning points of economic cycles. By using vintage data updated on a monthly basis, we compare their ability to date ex post the occurrence of turning points, evaluate the stability over time of the signal emitted by the models and assess their ability to detect in real-time recession signals. We show that the competitive use of these models provides a more robust analysis and detection of turning points. To perform the complete analysis, we have built a historical vintage database for the euro area going back to 1970 for two monthly macroeconomic variables of major importance for short-term economic outlook, namely the industrial production index and the unemployment rate.
|Data di pubblicazione:||2013|
|Titolo:||Evaluation of Nonlinear time-series models for real-time business cycle analysis of the Euro area|
|Rivista:||JOURNAL OF FORECASTING|
|Digital Object Identifier (DOI):||http://dx.doi.org/10.1002/for.2260|
|Appare nelle tipologie:||2.1 Articolo su rivista |
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|BillioFGMazziFOR.pdf||Documento in Post-print||Accesso chiuso-personale||Open Access dal 01/11/2050|