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A multi‐country dynamic factor model with stochastic volatility for euro area business cycle analysis

Florian Huber, Michael Pfarrhofer () and Philipp Piribauer

Journal of Forecasting, 2020, vol. 39, issue 6, 911-926

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.

Date: 2020
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https://doi.org/10.1002/for.2667

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Working Paper: A multi-country dynamic factor model with stochastic volatility for euro area business cycle analysis (2020) Downloads
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