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

57 Pages Posted: 12 Feb 2013

See all articles by Massimiliano Giuseppe Marcellino

Massimiliano Giuseppe Marcellino

European University Institute; European University Institute - Robert Schuman Centre for Advanced Studies (RSCAS); Bocconi University - Department of Economics; Centre for Economic Policy Research (CEPR)

Mario Porqueddu

Bank of Italy

Fabrizio Venditti

Bank of Italy

Multiple version iconThere are 2 versions of this paper

Date Written: February 2013

Abstract

In this paper we develop a mixed frequency dynamic factor model featuring stochastic shifts in the volatility of both the latent common factor and the idiosyncratic components. We take a Bayesian perspective and derive a Gibbs sampler to obtain the posterior density of the model parameters. This new tool is then used to investigate business cycle dynamics and for forecasting GDP growth at short-term horizons in the euro area. We discuss three sets of empirical results. First we use the model to 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 design a pseudo out of sample forecasting exercise and examine point and density forecast accuracy. In line with findings in the Bayesian Vector Autoregressions (BVAR) literature we find that stochastic volatility contributes to an improvement in density forecast accuracy.

Keywords: Business cycle, Forecasting, Mixed-frequency data, Nonlinear models, Nowcasting

JEL Classification: C22, E27, E32

Suggested Citation

Marcellino, Massimiliano and Porqueddu, Mario and Venditti, Fabrizio, Short-Term GDP Forecasting with a Mixed Frequency Dynamic Factor Model with Stochastic Volatility (February 2013). CEPR Discussion Paper No. DP9334, Available at SSRN: https://ssrn.com/abstract=2215453

Massimiliano Marcellino (Contact Author)

European University Institute ( email )

Villa Schifanoia
133 via Bocaccio
Firenze (Florence), Tuscany 50014
Italy

European University Institute - Robert Schuman Centre for Advanced Studies (RSCAS) ( email )

Villa La Fonte, via delle Fontanelle 18
50016 San Domenico di Fiesole
Florence, Florence 50014
Italy

Bocconi University - Department of Economics ( email )

Via Gobbi 5
Milan, 20136
Italy

Centre for Economic Policy Research (CEPR) ( email )

London
United Kingdom

Mario Porqueddu

Bank of Italy ( email )

Via Nazionale 91
Rome, 00184
Italy

Fabrizio Venditti

Bank of Italy ( email )

Via Nazionale 91
00184 Roma
Italy

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