This is a clear example of how the quality of the overall statistical system is higher than what the mere sum of independent products would be, were such products not well-connected. Micro data as the Holy Grail We can all agree that statistics have been undergoing a revolution in the last few years. Important technological advances have increased the ability to process huge amounts of data and productivity in this area has surged: policymakers and analysts have more and more information and details at their fingertips and now have the possibility of applying  1  more sophisticated models, designing more refined economic policy responses and answering more complex questions. Some of these changes stem from the experience of the Great Financial Crisis of the last decade. Then it was felt that only the availability of detailed information on economic agents’ positions (including cross-border ones) would allow the relevant policy authorities to thoroughly analyse the exposures of an increasingly interconnected global financial system and to better understand the monetary policy transmission mechanism and the massive deleveraging that followed. To close these gaps, the Eurosystem promoted a number of projects based on granular information. These included AnaCredit (to build up a Central Credit Register at the European level), the Securities Holding Statistics Database (which contains exhaustive security-by-security information on European portfolios) and Money Markets Statistical Reporting, where daily information at the transaction level is collected from financial institutions. In Spain, we also learned the lesson.

As I have stressed many times recently, and in particular over the last few months during the COVID crisis, the key to understanding the degree of success of policies or the occurrence of potential unexpected consequences is to proceed with proper and timely evaluations based on sufficient background information. This is the only way to ascertain to what extent policies are working or need adjustment in terms of their timing, magnitude and focus. Global authorities are now in uncharted waters in terms of the dimension of the crisis and its multiple ramifications, and it is very difficult to calibrate the response of economic policy. Only good and timely data can allow us to design an optimal policy reaction in such a complex context. The present crisis has also stressed the importance of having data in real time: in the last few months, information on the use of payment cards, traffic on roads and at airports, electricity consumption, mobility, Google searches and so on has been fundamental for assessing the magnitude of the economic slump and the subsequent timid recovery. These indicators will hardly join the compact and methodologically sound realm of official statistics; but I think we should also pay attention and invest some resources in understanding them, familiarising ourselves with their use and incorporating them into our forecasting models. Probably, some of these indicators could be temporarily considered “experimental statistics”, a label statistical institutions may use to explore new fields and to convey to users the as yet not fully sound nature of these data.