At the same time, just as a good meal not only requires high-quality ingredients but also an excellent cook and recipe, high-quality monetary policy analysis also requires excellent staff and an appropriate analytical framework. The importance of the latter can hardly be overstated. While central bankers around the world are “data fiends” in their heroic attempts to minimise errors of inference and to make robust decisions amidst uncertainty about the true structure of the economy, the availability of a vast wealth of raw data from diverse sources may mean that policy-makers become constantly bombarded by conflicting signals. Amidst such a flood of information, policy runs the risk of losing its bearings and of over-reacting to the latest indicator. It is against this background that the ECB decided to adopt an analytical framework within which all possible sources of information - statistical as well as judgemental - can be brought together in a coherent fashion while at the same time allowing for alternative and diverse models and perspectives of the workings of the economy. In our view, this framework enables a wealth of information to be “digested” routinely without compromising the ultimate objective: to maintain a clear sense of direction. In order to give a structure to the diverse sources of information, a structure that is consistent with our view of the monetary policy transmission mechanism, we have organised our analytical framework into “two pillars”. These consist of two complementary perspectives on the determination of price developments.
Let me elaborate a bit more on these three themes: the need for an encompassing and integrated set of data, the achievements of, and outlook for, euro area statistics and the ECB’s framework for analysing this information. Monetary policy and the need for an encompassing and integrated set of data If we lived in the world of macroeconomic textbooks, a few simple models with a limited set of variables would be a sufficient basis for monetary policy-making and the statistical requirements could be kept to a minimum. As we all know, the real world is much more complex and, therefore, information needs are much more elaborated. In such a world, a rich and integrated set of data is needed because macroeconomic models, synthetic indicators and unconnected statistical indicators are often too rough a guide to the current and likely future development of the economy. As mentioned before, central banks have to take decisions under conditions of constant uncertainty. The economy is never at rest. A multitude of disturbances of diverse nature affect the economy all the time: financial shocks, demand shocks, supply shocks etc., and these cannot easily be distinguished in real time, let alone foreseen. In their attempts to identify disturbances and track how they spread through the economy, central banks are assisted by models. But too often, existing models are not sufficiently sophisticated instruments to identify shocks. For one thing, their focus may be too narrow, in a way that makes them  BIS Review 67/2004  1  unduly selective.