Short-Term GDP Forecasting With a Mixed-Frequency Dynamic Factor Model With Stochastic Volatility

Massimiliano Marcellino, Mario Porqueddu and Fabrizio Venditti

Journal of Business & Economic Statistics, 2016, vol. 34, issue 1, 118-127

Abstract: In this article, we develop a mixed frequency dynamic factor model in which the disturbances of both the latent common factor and of the idiosyncratic components have time-varying stochastic volatilities. We use the model to investigate business cycle dynamics in the euro area and present three sets of empirical results. First, we evaluate the impact of macroeconomic releases on point and density forecast accuracy and on the width of forecast intervals. Second, we show how our setup allows to make a probabilistic assessment of the contribution of releases to forecast revisions. Third, we examine point and density out of sample forecast accuracy. We find that introducing stochastic volatility in the model contributes to an improvement in both point and density forecast accuracy. Supplementary materials for this article are available online.

Date: 2016
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Citations: View citations in EconPapers (41)

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Related works:
Working Paper: Short-term GDP forecasting with a mixed frequency dynamic factor model with stochastic volatility (2013)
Working Paper: Short-term GDP forecasting with a mixed frequency dynamic factor model with stochastic volatility (2013)
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Persistent link: https://EconPapers.repec.org/RePEc:taf:jnlbes:v:34:y:2016:i:1:p:118-127

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DOI: 10.1080/07350015.2015.1006773

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