Short-term forecasting of GDP with a DSGE model augmented by monthly indicators

Marianna Cervena and Martin Schneider ()

International Journal of Forecasting, 2014, vol. 30, issue 3, 498-516

Abstract: DSGE models are useful tools for evaluating the impact of policy changes, but their use for (short-term) forecasting is still in its infancy. Besides theory-based restrictions, the timeliness of data is an important issue. Since DSGE models are based on quarterly data, they suffer from the publication lag of quarterly national accounts. In this paper we present a framework for the short-term forecasting of GDP based on a medium-scale DSGE model for a small open economy within a currency area. We utilize the information available in monthly indicators based on the approach proposed by Giannone et al. (2009). Using Austrian data, we find that the forecasting performance of the DSGE model can be improved considerably by incorporating monthly indicators, while still maintaining the story-telling capability of the model.

Keywords: Nowcasting; Real time data; Mixed frequencies (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (6)

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Working Paper: Short-term forecasting GDP with a DSGE model augmented by monthly indicators (2010)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:intfor:v:30:y:2014:i:3:p:498-516

DOI: 10.1016/j.ijforecast.2014.01.005

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