|
|
The system and processes for producing statistics that are used directly for monetary policy purposes are well advanced in terms of their accuracy, timeliness and coverage. The compelling question is therefore whether these statistics could also serve the needs of financial stability policies and macro-prudential supervision.
Monetary statistics tend to provide us with aggregated data. There are, of course, very good reasons why this is the case, but for the purposes of macro-prudential analysis, it would be more useful if the data were also consolidated at the level of individual banking groups. In addition, not only banks, but also insurance companies, pension funds and ideally the entire financial system, including the shadow banking sector, should be covered in order to effectively help policymakers identify potential sources of systemic risk. Furthermore, data with sufficient granularity are instrumental in macro-prudential analysis in order to take both averages and distributions into account. In turn, the microfoundations of aggregates must be explored.
When considering the different ways in which we can try to close the existing data or information gaps, there are essentially three options: i) launch a new data collection effort; ii) make better use of existing data; and, perhaps most importantly, iii) revisit the data collection processes that are currently in place. We are fully aware that, irrespective of whether the first or second options are adopted, we will in any case have to review our existing data collection processes.
A strategic shift towards granular, multi-purpose data collection and more integrated data production processes can effectively reduce the burden on reporting agents and, at the same time, deliver more information to data users. Indeed, in attempting to collect more micro data (such as through the ongoing Eurosystem project to collect securities holding statistics on a security-by-security basis), we will face the challenge of finding ways to adapt more flexibly to new user demands without imposing additional reporting requirements on data reporting agents. These efforts should be reinforced by establishing harmonised data collection frameworks common to central banks and supervisory authorities. The trade-off between the reporting burden and the amount of information available has to be tackled at its roots, owing to the ever-growing likelihood of additional, unforeseeable requests for data on an ad hoc or regular basis. Multi-purpose data collection offers a viable solution to this problem and, given the present scarcity of resources, there is virtually no alternative avenue to enable central banking statistics to successfully serve both Eurosystem mandates.