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

DSGE models are useful tools for evaluating the impact of policy changes but their use for (short-term) forecasting is still at an infant stage. Besides theory based restrictions, the timeliness of data is an important issue. Since DSGE models are based on quarterly data, they are vulnerable to a publication lag of quarterly national accounts. In this paper we propose a framework for a short-term forecasting of GDP based on a medium-scale DSGE model for a small open economy within a currency area that utilizes the timely information available in monthly conjunctural indicators. To this end we adopt a methodology proposed by Giannone, Monti and Reichlin (2009). Using Austrian data we find that the forecasting performance of the DSGE model can be improved considerably by conjunctural indicators while still maintaining the story-telling capability of the model.