Andreas Dombret: Macroprudential surveillance and statistical
challenges
Speech by Dr Andreas Dombret, Member of the Executive Board of the Deutsche
Bundesbank, at the Sixth ECB Statistics Conference, Frankfurt am Main, 17 April 2012.
* * *
1 Introduction
Ladies and gentlemen
Thank you for inviting me to speak to you tonight. Many of the statistical challenges that are
related to macroprudential surveillance have already been addressed this afternoon. Allow
me to offer some thoughts from the point of view of a macroprudential practitioner, who is
also involved in statistics.
It is a crucial aspect of macroprudential surveillance, as we see it in Europe, that the
macrofinancial analysts receive all the information relevant for them to do their job. From my
point of view, four aspects stand out:
1. Data requests must be analytically driven.
2. Micro and macro-views should be reconcilable.
3. Single entity and consolidated data are equally important.
4. The Data gaps issue needs to stay on top of the agenda.
2 The significance of macroprudential surveillance
There is, more than ever, a strong case for mutual understanding and close ex ante
coordination, because in recent years we have witnessed nothing less than a significant
change in the paradigm of macroprudential surveillance. Three steps can be distinguished.
As a first step, in spring of 2009, an international reform agenda has been agreed upon, and
the Financial Stability Board has been assigned a key function.
Then, at the beginning of 2011, the European Systemic Risk Board has taken up its work.
And, as a last step, we are in the process of national macroprudential mandates being
drafted in several European countries. Actually, at the end of last year, the ESRB released
an explicit recommendation on the macro-prudential mandate of national authorities.
Macroprudential surveillance, at the European level, can be characterized by a
threepronged approach.
- Firstly: A legal mandate exists for safeguarding financial stability. Europe is setting
standards with respect to macroprudential policy.
- Secondly: Macroprudential surveillance pursues an indirect approach to
surveillance. This means that macrofinancial analysts are entitled to receive the
totality of relevant information in order to be able to deliver early warnings and clear
recommendations. Meanwhile, all operative, microprudential instruments remain in
the hands of the relevant supervisory agencies.
- Thirdly: Central banks are to take on additional responsibilities.
The draft of an act to strengthen German financial supervision that was released just a few
days ago follows exactly along these lines.
However, the indirect approach, which is a crucial element in the European concept of
macroprucential surveillance, is far from being completely implemented. It remains an
important challenge to find a system of rules and procedures for applying macroprudential
instruments to address country-specific or sectoral risks. It is important to reconcile the goal
of completing a Single Market for financial services with the need for sufficient
macroprudential flexibility.
Moreover, formidable challenges refer to the acquisition of what I have called the totality of
relevant information. It is against this very background that statistics enter the stage.
Statistics, together with IT, are probably the most important means for macrofinancial
analysts to meet their information needs.
3 Conceptual challenges
The G20 Data Gaps Initiative aims at both strengthening existing statistics and at developing
new ones. As regards the development of new statistics, the task is quite challenging. Take,
for instance, the initiatives on enhancing information on financial linkages, on mapping
exposure and funding patterns or on identifying the activities of non-bank financial
institutions, just to mention a few. Off-the-rack blueprints on how to proceed do not exist. The
legal framework for data collection needs to be broadened in some countries. Confidentiality
issues will have to be addressed. And, last but not least, analytical guidance is necessary for
the collection of data and for prioritization and coordination of statistical activities.
3.1 Data requirements need to be based on sound arguments
Any request for statistical data should be analytically driven. To be provocative: "Do you
really need the data that we do not have?" This means that the goal of any research must be
clearly defined, and that at least some preliminary ideas of how to proceed must be
developed in advance. It is a prerequisite for statisticians to set priorities when employing
their resources in their search for data that is fit for purpose. For the macro-prudential
analyst, though, it is often the other way around: developing good ideas needs having at
least some stylized facts before theorizing. This is a prerequisite for macro-prudential
analysts.
However, it has to be recognized that financial stability cannot be defined bluntly. To give an
example: The measurement of financial distress requires a broad and open concept having
many dimensions which evolve over time. What is necessary, therefore, is an iterative
approach that addresses individual aspects of financial stability step by step and tackles the
subject from a number of different directions.
3.2 Marrying micro and macro data
Macroprudential surveillance has a lot to do with gaining a bird's eye view of the individual
market players and their interlinkages. Consequently, what the analysts need is an approach
that appropriately integrates micro and macro data.
This observation presents a case for a more in-depth use of statistical micro data. To give an
example: When we look at the balance sheet of a bank as reported to statistics, we know
that it is precisely this data that is used to derive national and euro-zone money and credit
aggregates, financial accounts referring to the banking sector, external positions, BIS
locational banking statistics and so forth. This guarantees a high degree of consistency for
analytical purposes. Not least for this reason, statisticians have begun to put additional
emphasis not only on the provision of aggregates but also more and more on the provision of
granular data that can likewise be used for micro and macro analysis. A case in point is the
ESCB's well established Centralised Securities Database and the new ESCB project of a
Securities Holdings Statistics Database.
3.3 Reconciling single entity and consolidated data
If macroprudential analysts are to rely more heavily on statistical micro data, statisticians will
have to adopt a two-way approach. They will have to provide data on a single-entity as well
as on a consolidated basis. Both approaches are necessary to get the full picture.
Ideally, the analysis of consolidated data would be compatible with single entity analysis.
This would enable us to take a look from the corporate perspective while keeping in focus the
interrelationship between branches and subsidiaries. It is up to the statisticians to develop
viable solutions.
4 Filling important data gaps
As to the issue of data gaps, there are two areas which both from a statistical and from an
analytical point of view appear particularly challenging. These are the scarcity of data on the
shadow banking system and the unsatisfactory progress being made in building a broader
database on the insurance sector.
4.1 Shadow banking system
Credit intermediation via shadow banking has been producing serious financial distress,
which contributed to the crises and which continues to be a risk factor for the stability of the
financial system. Moreover, risks for the financial system tend to be systematically stemming
from this sector, making its macroprudential analysis very important but difficult to handle,
statistically as well as conceptually. This situation presents extraordinary challenges for
supervisory and regulatory authorities as highlighted in a FSB report to the G20 in October of
last year, and, only recently, in the European Commission's Green Paper on Shadow
Banking. The immanent concern with shadow banking is thus its lack of transparency. What
are our options for the territory of shadow banking to be charted?
Shadow banking involves entities and activities outside the regular banking system, and
statistical data collection in many parts is still quite sketchy. Obviously, there is an urgent
need for central banks to be given an extended mandate for the collection of data not only
from banks but also from non-bank financial institutions.
What can be done in the short term? As you know, there are two standard prescriptions
frequently recommended as an initial remedy. The first of these is an extended analysis of
flow of funds data. The second is an evaluation of counterparty information from balance
sheet statistics. As regards the flow of funds, these transmit an idea of the main structures of
the financial system: no more, but no less. Building on this feature, the G20 Data Gaps
Initiative suggests that flow of funds information be amended by detailed sectoral accounts in
the form of "from-whom-to-whom" tables, and, in fact, the IMF has already presented a pilot
by submitting a standardized report form, based on what they call the "Balance Sheet
Approach". A similar project is under way in the ESCB with promising results. Nevertheless,
the critical point is that our basic statistics on financial institutions outside the regular banking
system be improved.
As regards counterparty information from balance sheets, these allow the mapping of
exposures between the reporting institutions and financial entities elsewhere. In order to
shed more light on shadow banking activities, a more disaggregated sectoral breakdown is
needed. Initiatives have been launched, for instance, in the context of the BIS Consolidated
Banking Statistics, where we will see positions vis-à-vis "other financial institutions" being
broken out separately. There also exists a considerably more ambitious attempt at collecting
detailed counterparty data in some other BIS surveys, notably the OTC Derivatives Statistics,
where you can find data on credit default swaps broken down, among others, into positions
vis-à-vis insurance firms, SPVs- and hedge funds. The problem here is that operational
definitions - say, for hedge funds - have proven to be difficult to agree on, and, therefore,
the issue of classification has been left to the discretion of reporters. This is far from being an
optimal solution. The Bundesbank therefore is calling for the development of an international
business register.
4.2 Insurance sector
Insurance companies are in the focus of macroprudential surveillance because of their
function as risk brokers and their role as financial intermediaries. However, there is a striking
contrast between the economic and financial relevance of insurance companies and the
relatively scarce amount of statistical data at hand. This has prompted the Eurosystem to
launch an initiative geared to setting up new statistics on insurance companies and pension
funds at the European level. Actually, initial sets of data have been produced, but, as many
central banks lack their own data collection systems for insurance data, much of the
information has to be imported, on an aggregated basis, from supervisory sources. This
necessitates the data having to be heavily supported, for analytical purposes, by in-house
estimates. But, to be clear on this point: Statisticians have to abstain from becoming
"nowcasters" or "forecasters".
Even after the implementation of Solvency II blind spots will continue to exist. For instance,
there will be no new data on pension funds. Moreover, data timeliness and data frequency
will have to be significantly improved. This means that there is still need for an additional
ECB regulation on insurance statistics.
5 A strong case for statistical cooperation
The days when statistics was just about number crunching clearly are history. I regard a
statistician as someone who is confident of his skills, well trained in economic analysis, and
closely integrated in an institutional network ruled by proven, time-honored principles.
Moreover, a cooperative spirit is called for, paired with a sense of accountability and
responsibility. And these are the same construction principles to be followed when it comes
to building stable bridges between the various statistical fora and systems. Seen against the
background of the current debate on the future of the Committee on Monetary, Financial and
Balance of Payments statistics (CMFB), let me express my hope that everyone in Europe
fully appreciates the high value of good partnership. In that respect, the CMFB is not only a
body, but rather a concept. I am sure that no one in Europe would understand why it should
be a good idea to abolish the CMFB, especially in times like these, when a strengthening of
its role is absolutely necessary.
6 Concluding remarks
Let me summarize my main messages:
 Europe is setting standards with respect to macroprudential policy. Germany is
about to implement national macroprudential oversight.
 Macro analysts are entitled to receive all relevant information in order to be able to
deliver early warnings and clear recommendations.
 Statistics are the most important means for macrofinancial analysts to meet their
information needs.
 Micro and macro data should be happily married.
 A two-eyed approach is needed: Single entity and consolidated data are equally
important.
 Enlightening the shadow banking system and the insurance sector requires our
special attention.
 There is no alternative to good partnership, between statistical institutions and
systems.
 Politicians should back our work.
At the end of the day, there can be no question that macroprudential surveillance is
dependent on a solid statistical groundwork. On the basis of the discussed prerequisites,
priorities and principles, I am confident that we will master the future of macroprudential
statistics.
Thank you for your attention.