It must be clearly shown which principles we have based our monetary policy decisions on and what information our conclusions are based on. As monetary policy affects the economy with some time lag, the monetary policy decisions must be based on forecasts, as I mentioned at the start. Good bases for decisions in the form of accurate forecasts are thus an important factor in the success of monetary policy. But future developments in inflation and other variables are uncertain. For one thing, there is the uncertainty linked to the statistical methods and models, as certain fundamental parameters vary over time. For another thing, there are a number of other factors that can affect inflation  BIS Review 138/2007  1  in a way that is very difficult to predict. For instance, increased geopolitical unease can push up the oil prices, or an unexpected outbreak of a disease among animals can lead to a rapid rise in food prices. When central banks make forecasts, it is therefore increasingly common that they put a band around the forecasts that measures their uncertainty. These bands help provide information about the uncertainty in the forecasts and also make it easier to communicate the monetary policy alternatives that may arise in the future. But what do we know about the forecasting performance of the Riksbank? Forecasting performance is evaluated both internally and externally Forecasting performance can be evaluated in many different ways. There are a number of statistical methods that can be used to analyse how accurate the forecasts are.
For instance, the downswing in inflation in 2003 was captured to a greater extent than the upswing at the beginning of 2001. The inflation forecasts are on the whole more accurate than the time series models. The forecasting memory for the CPIX extends eight quarters ahead (Figure 8). The correlation between forecasts and outcome is almost 0.8 one year ahead and just over 0.5 two years ahead (see Figure 9). None of the other variables has as high a correlation two  7  We have earlier analysed this in the context of a structural model, Ramses. The evaluation appendix to Inflation Monetary Policy Report 2007:1 contains an analysis of, for instance, the effects of productivity shocks on the economy. 4  BIS Review 138/2007  years ahead. The fact that the correlation wanes in time is natural as the uncertainty in the forecasts increases. Is there any bias one or two years ahead in the forecasts? Let us now look at whether there is any bias, that is, systematic over-estimation or underestimation in the forecasts one and two years ahead. The smaller the bias a forecast has, the better it is. One year ahead the bias for annual GDP growth is very small. However, two years ahead the forecasts have been almost been four tenths too high on average, compared with the outcomes, which is not negligible (Figure 10). With regard to the annual development in employment, the bias is just under three tenths one year ahead and two tenths two years ahead.