A multi‐country dynamic factor model with stochastic volatility for euro area business cycle analysis. (25th February 2020)

• Record Type: Journal Article
• Authors: Huber, Florian; Pfarrhofer, Michael; Piribauer, Philipp
• Is Part Of: Journal of forecasting. Volume 39:Number 6(2020)
• Page Start: 911
• Page End: 926
• Publication Date: 2020-02-25
• Subjects: dynamic factor model -- European business cycles -- factor stochastic volatility -- inflation forecasting; Forecasting -- Periodicals; Forecasting -- Mathematical models -- Periodicals; 003.2
• DOI: 10.1002/for.2667
• Languages: English
• ISSNs: 0277-6693

Abstract

Abstract: This paper develops a dynamic factor model that uses euro area country‐specific information on output and inflation to estimate an area‐wide measure of the output gap. Our model assumes that output and inflation can be decomposed into country‐specific stochastic trends and a common cyclical component. Comovement in the trends is introduced by imposing a factor structure on the shocks to the latent states. We moreover introduce flexible stochastic volatility specifications to control for heteroscedasticity in the measurement errors and innovations to the latent states. Carefully specified shrinkage priors allow for pushing the model towards a homoscedastic specification, if supported by the data. Our measure of the output gap closely tracks other commonly adopted measures, with small differences in magnitudes and timing. To assess whether the model‐based output gap helps in forecasting inflation, we perform an out‐of‐sample forecasting exercise. The findings indicate that our approach yields superior inflation forecasts, both in terms of point and density predictions.