##saggregated information in terms of national time series is more useful for forecasting than aggregated information ( area - wide time series ) in the euro area. 14 concerning the forecast methods, various approaches are employed, and the eurosystem pursues a suite - of - models approach. regarding the level of aggregation, the eurosystem employs econometric models for single euro area member countries in addition to area - wide approaches. traditional structural macroeconometric models still play a key role in forecasting – for example, the area - widemodel ( awm ) of the ecb – and the econometric models of the euro - area central banks. recently, dsge models have been developed in the eurosystem. some of these models are still under construction and some are already used for policy simulations. however, they have not been widely used for forecasting so far. in addition, eurosystem staff makes use of time series models for shortterm forecasting, such as different var models and large factor models. however, eurosystem forecasts are not fully model - based. in the forecast exercises conducted by the eurosystem, a complex interaction of information takes place between models and judgmental information from outside the models. 3. 1 the role of short - term interest rates in central bank projections one practical difficulty in forecast exercises is the appropriate conditioning of the forecasts. a particularly subtle problem for central banks concerns the appropriate choice of a consistent shortterm interest - rate projection. this topic plays a key role in the recent discussion on central bank forecasting. the short - term rate is the policy instrument under the control of the central bank ; via the expectation channel, its future path influences current economic circumstances and decisions. specifying a trajectory of future rates in today ’ s projections is therefore a delicate problem with regard to the signals about the future course of monetary policy given to outside observers. there are basically three ways of specifying the future interest rate path. firstly, a constant short - term interest rate ( cir ) assumption can be employed. the inflation projection being higher ( lower ) than the inflation target at some given horizon has been interpreted as indicating that, sooner or later, the instrument rate needs to be raised ( lowered ). 15 an advantage of this assumption is that it can easily be communicated. cir is an obviously technical assumption with no risk of central bank commitment to follow the assumed constant interest rate path. one drawback is that

when forecasts use the correct conditional expectation in a weakly - stationary process. in other words, a departure from perfect knowledge is necessary to explain gains from combination, see clements and hendry and timmermann ( 2005 ) : see granger and jeon ( 2004 ), pp. 324 - 5. see spanos ( 2001 ). taking into account more than one benchmark model makes the null of equal forecast accuracy harder to reject. see, for example, white ( 2000 ), table 1, p. 1113. construction of an mcs involves a sequence of tests for equal predictive ability. this restricts the set of candidate models by deleting models that are found to be significantly inferior, and the set of remaining models is the mcs. an mcs can be used to construct combination forecasts by pooling the forecasts of the models in the mcs. if the number of models in the mcs is large, a reasonable way to proceed is to weigh the individual forecasts equally. the reason for this is that the mcs consists precisely of the models that cannot be rejected as being equally good. see hansen, lunde and nason ( 2003 ), p. 841. • a pro - diversification argument states that some combination of two - model forecasts might perform better than either alone, if the two models provide partial, but not overlapping, explanations. 10 • owing to model uncertainty, using the correct conditional expectation for forecasting is unrealistic, and, in reality, departures from the correct model may be expected to be the rule rather than the exception. • if structural breaks occur, forecasts from individual models may be affected differently, possibly on account of differing degrees of misspecification. combinations of forecasts might then outperform forecasts from individual models. 11 to summarize : there are good reasons why monetary policy pursues fullinformation strategies and “ looks at everything ” in terms of a broad set of information from data and models. the recent sizable literature on robust policies in various model environments also emphasises the merits of model combination and averaging. 12 therefore, selecting a single model for monetary policy may be inappropriate, since conditioning monetary policy decisions on one model ignores the role of model uncertainty. it also disregards the favourable empirical results from the forecast combination literature, and thus leaves aside potentially important information. eurosystem forecasting the governing council of the eurosystem bases its comprehensive assessment of the risks