Forecasting Austrian GDP using the generalized dynamic factor model
In this paper, a generalized dynamic factor model is utilized to produce short-term forecasts of real Austrian GDP. The model follows the frequency domain approach proposed by Forni, Hallin, Lippi and Reichlin (2000, 2003). The forecasting performance of the model with a large data set of 143 variables has been assessed relative to simple univariate time-series forecasts. The results show that the factor model can barely outperform the much simpler benchmark model, given the usuall levels of significance. Thus we followed a line of research proposed by Boivin and Ng (2003) and Watson (2000), who suggested that the use of a small data set may increase the forecasting performance. The main finding from our extensive out-of-sample forecasting experiment that we have conducted is that the best forecasting performance can be achieved with small data sets with a handful of variables only. These models perform signifi- cantly better than the large model. This result seems to contradict the basic idea of dynamic factor models, which have been constructed to exploit the potentially useful information of a large data set.
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- Michael Artis & Anindya Banerjee & Massimiliano Marcellino, "undated".
"Factor forecasts for the UK,"
203, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
- Artis, Michael J & Banerjee, Anindya & Marcellino, Massimiliano, 2002. "Factor Forecasts for the UK," CEPR Discussion Papers 3119, C.E.P.R. Discussion Papers.
- Michael ARTIS & Anindya BANERJEE & Massimiliano MARCELLINO, 2001. "Factor Forecasts for the UK," Economics Working Papers ECO2001/15, European University Institute.
- Boivin, Jean & Ng, Serena, 2006. "Are more data always better for factor analysis?," Journal of Econometrics, Elsevier, vol. 132(1), pages 169-194, May.
- Altissimo, Filippo & Bassanetti, Antonio & Cristadoro, Riccardo & Forni, Mario & Hallin, Marc & Lippi, Marco & Reichlin, Lucrezia & Veronese, Giovanni, 2001.
"EuroCOIN: A Real Time Coincident Indicator of the Euro Area Business Cycle,"
CEPR Discussion Papers
3108, C.E.P.R. Discussion Papers.
- Mario Forno & Marco Lippi & Lucrezia Reichlin & Filippo Altissimo & Antonio Bassanetti, 2003. "Eurocoin: A Real Time Coincident Indicator Of The Euro Area Business Cycle," Computing in Economics and Finance 2003 242, Society for Computational Economics.
- Gonzalo Camba-Mendez & George Kapetanios & Richard J. Smith & Martin R. Weale, 2001. "An automatic leading indicator of economic activity: forecasting GDP growth for European countries," Econometrics Journal, Royal Economic Society, vol. 4(1), pages 1-37.
- Dr Martin Weale, 1999. "An Automatic Leading Indicator of Economic Activity: Forecasting GDP Growth for European Countries," NIESR Discussion Papers 149, National Institute of Economic and Social Research.
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