Vítor Constâncio: Financial stability - measurement and policy
Speech by Mr Vítor Constâncio, Vice-President of the European Central Bank, at the high
level conference on "Financial stability - methodological advances and policy issues",
Frankfurt am Main, 14 June 2012.
* * *
Ladies and gentlemen,
After a productive day, it is with great pleasure that I welcome you to this dinner. Before we
get started, let me offer a few thoughts regarding macro-prudential research, the current
stage of financial stability analysis at the ECB and policy conduct in Europe.
The sources and the propagation of the financial crisis highlighted the need for putting in
place robust policy infrastructures to safeguard financial stability and for macro-prudential
policies to address systemic risk. In this light, new institutions have been put in place, such
as the European System of Financial Supervision and the Financial Stability Oversight
Council in the United States, and regulatory reforms are taking shape, notably Basel III and a
host of other initiatives under the leadership of the Financial Stability Board.
This progress notwithstanding, it needs to be kept in mind that in the macro-prudential field
we are in a much less comfortable position than in the monetary policy field, in particular
concerning widely accepted scientific foundations and long experience with tested policy
instruments.
Against this background, I will start by providing a brief overview of the recent
macroprudential research. I will then focus on some of the main analytical tools for financial stability
analysis at the European Central Bank (ECB). I will conclude by referring to a key aspect of
our future regulatory framework in Europe, namely the set of macro-prudential policy
instruments embedded in the Capital Requirements Directive (CRD) IV, and how these
instruments should be made compatible with the requirements for both safeguarding financial
stability and further developing the Single Market for financial services.
1. Progress in macro-prudential and financial stability-oriented research
The theoretic foundations in the macro-prudential field are still at a largely rudimentary state
compared to other research areas. This notwithstanding, significant advances in
macroprudential research have been made in recent years; in particular fuelled by the lessons
learnt during the financial crisis which underscored the need to take a more systemic view to
monitoring and assessing risks and vulnerabilities within the financial system and beyond.
The papers presented at today and tomorrow's conference provide some useful snapshots of
the recent academic advances in the field of macro-prudential, and more broadly, financial
stability analysis.
One promising area of research deals with
early warning models and systemic risk
indicators, which was the theme of Sessions I and II this morning.
In recent years the value of early warning indicators has increased thanks to improved
methodologies and the use of less exploited data sources. It should also be added that from
a policy perspective the focus has been shifted somewhat from predicting crises to predicting
growing imbalances and highlighting underlying vulnerabilities. As I believe was also
illustrated by Atish Ghosh this morning, this change of focus has most likely contributed to
the greater effectiveness of new early warning tools.1
Recent research shows how the predictive information can be improved by using individual
balance sheet data of financial firms combined with traditional macro-financial variables. As
for example illustrated by Claudio Borio and co-authors and by Alessi and Detken, the merit
of private credit and liquidity gaps and the role of global variables in early warnings has been
confirmed, while the performance of bank solvency and liquidity ratios in this regard is still
under debate.2
For what concerns systemic risk indicators, valuable information for policy-makers comes
from the measurement of the current level of systemic financial stress. A popular means of
assessing the systemic importance of a financial institution is to look at the sensitivity of its
value at risk (VaR) - i.e. its tail dependence - to shocks to the whole financial system. This
has been proposed by the CoVaR approach of Adrian and Brunnermeier or by similar
models of cross-sectional measures, like the Co-Risk used by the IMF and based in CDS
premia3 or the Systemic Expected Shortfall (SES) predicted by the Marginal Expected
Shortfall (MES) of an institution and its leverage developed by Acharya and co-authors and
by Brownless and Engle.4 CoVar calculations are being used by the FSOC in the US. We at
the ECB use different types of indicators to try to gage systemic risk as I will explain in a
moment.
A key element of this kind of systemic risk indicators is to account for the network relations
and clusters of systemic risk spillovers, as for instance demonstrated by Nikolaus Hautsch
and Kay Giesecke in their presentations this morning.5 Importantly, allowing for
interconnectedness may also help improving the predictive power of early warning models.
This is clearly illustrated by the ECB presentation this morning by Peltonen et al6 which
shows the usefulness of adding contagion to a regular Early Warning Systems improves the
performance of the model proving that it would have been successful in predicting bank
distress when the financial crisis was approaching.
A second important research area deals precisely with the assessment of contagion risks,
which was addressed in Session III. Contagion within the financial system can occur in
several ways, as illustrated by Franklin Allen this afternoon.7 Most commonly, shock
propagation within the financial system is thought to occur via interbank networks or via
1
See IMF (2010) "The IMF-FSB Early Warning Exercise: Design and Methodologies Toolkit", September.
2
See e.g. Borio, C. and P. Lowe (2002), "Asset prices, financial and monetary stability: Exploring the nexus",
BIS Working Paper No. 114; Borio, C. and M. Drehmann (2011), "Towards an operational framework for
financial stability: "fuzzy" measurement and its consequences", BIS Working Paper No. 284.; Alessi, L. and
C. Detken (2009), "Real-time early warning indicators for costly asset price boom/bust cycles", ECB Working
Paper No. 1039.
3
IMF (2009) "Assessing the systemic implications of financial linkages" Global Financial Stability Report, April
2009, pages 73-110.
4
See, for instance, Adrian, T. and M. Brunnermeier, "CoVaR" (2008), Federal Reserve Bank of New York Staff
Reports, No 348, September; Acharya, V.V., L.H. Pedersen, T. Philippon and M. Richardson (2010),
"Measuring Systemic Risk", New York University Working Paper; Brownlees, C.T. and R.F. Engle (2010),
"Volatility, Correlation and Tails for Systemic Risk Measurement", New York University Working Paper.
5
See Hautsch, N., J. Schaumberg and M. Schienle (2012), "Financial network systemic risk contributions",
working paper.
6
See Betz, F., Oprica, S., Peltonen, T.A., Sarlin, P (2012) "Predicting bank distress and identifying
interdependencies among European Banks", mimeo.
7
See Allen, F., A. Babus and E. Carletti (2012), "Asset commonality, debt maturity and systemic risk", Journal
of Financial Economics, Vol. 104, pp. 519-534.
common asset exposures. Depending on the structure of the network, even small shocks to
central hubs in the network can result in serious propagation throughout the system.
In most cases, during normal times, financial network structures are typically fairly robust to
shocks and thus allow for a better diversification of risk. However, this notwithstanding,
shocks to particular elements of the network can trigger major contagion within the system.
This is a key feature of the so-called "robust yet fragile" complex networks; also alluded to by
Doyne Farmer this afternoon.8
From a broader financial stability perspective, it is however not sufficient to be able to
monitor systemic risks and their potential spillover effects within the financial system were
they to occur. Financial stability analysis, and macro-prudential policy actions, is as much
about assessing the implications of ruptures in the financial system on the wider economy.
From this viewpoint, the development of macro-financial models linking financial
instability and the performance of the economy is of the essence.
The global financial crisis has revealed important deficiencies of the standard
macroeconomic models in capturing financial instabilities. Realistic characterisations of such
instabilities include bank defaults, financial market illiquidity, extreme events, and related
non-linearities. Especially, the modelling of bank defaults within a general equilibrium
framework is crucial to allow for a proper characterisation of financial instability. However,
none of these elements feature in the macroeconomic models regularly used for forecasting
and monetary policy analysis and only recently has more emphasis been given to better
developing the role of financial sectors in these models.
Another fundamental link which until recently has been missing in macro-financial models is
to allow for heterogeneity, and interlinkages, between the agents within the financial sector .
Against this background, efforts by economists such as Gertler and Kiyotaki to incorporate
interbank markets within Dynamic Stochastic General Equilibrium (DSGE) models are much
welcome.9 Also worth noting is the model by Goodhart, Kashyap et al which includes the
presence of a shadow banking system holding securitised assets issued by the traditional
banking system that are subject to default.10
A lot of attention, for example illustrated in the analysis by Adrian-Shin11, has also been
devoted recently to the debt and leverage ratios of financial intermediaries and to their
variation over the business cycle. In answering to the question of which financial frictions
matter, Adrian, Colla and Shin (2012)12 point to the importance of including in a model with
financial-real feedbacks the pro-cyclical leverage cycle and the co-existence of loans and
bonds that tend to be substitutes in a recession even if spreads on both tend to increase.
Geanakoplos has shown that variations in leverage have a huge impact on asset prices
potentially contributing to economic bubbles and busts.13 Leverage cycles have only recently
started being incorporated in macro-financial models. One prominent example is the model
8
See Caccioli, F., J.D. Farmer, N. Foti and D. Rockmore (2012), "Stability of the Austrian banking system",
unpublished paper.
9
See Gertler, M. and N. Kiyotaki (2010), "Financial intermediation and credit policy in business cycle analysis",
in B. Friedman and M. Woodford (eds.), Handbook of Monetary Economics, Edition 1, Volume 3, October.
10
See Goodhart, C.A.E., A. Kashyap, D.P. Tsomocos, and A.P. Vardoulakis (2012), "Financial Regulation in
General Equilibrium", NBER Working Paper No. 17909.
11
See Adrian, T. and H.S. Shin (2010), "Financial intermediaries and monetary economics", in B. Friedman and
M. Woodford (eds.), Handbook of Monetary Economics, Edition 1, Volume 3, October.
12
Adrian, T., Colla, P. and Shin, H. S. (2012) "Which financial frictions? Parsing the evidence from the financial
crisis of 2007-09" Federal Reserve Bank of New York, Staff Reports, revised version March 2012.
13
See Geanakoplos, J. (2009), "The leverage cycle", in D. Acemoglu, K. Rogoff and M. Woodford (eds.), NBER
Macroeconomics Annual, Vol. 24.
by Brunnermeier and Sannikov which includes time-varying margin requirements set by
financial intermediaries and thus exacerbates the impact of asset prices over the business
cycle as they trigger "margin spirals" that may cause long-lasting adverse feedback loops
between the financial sector and the real economy.14
A final research area which I would like to highlight concerns the interactions between
macro-prudential policies, including financial regulation, and other policies such as
monetary policy as well as the impact these policies might have on the financial system and
the real economy. Monetary policy impacts in a fundamental way financial stability: it affects
asset prices; influences liquidity conditions and has a bearing on risk taking since low short
term interest rates lead directly to expectation of profitable exploitation of a steeper yield
curve and consequently tend to increase leverage with more risk.15 As Adrian and Shin
(2009) underline what is significant in this "risk-taking channel" (Borio and Zhu (2008)16) is
that the short term interest rate has a direct effect on monetary and financial conditions not
waiting for the indirect effect on medium term rates.
On the other hand, looking to historical experiences with macro-prudential tools, being
dynamic provisions in Spain or loan-to-Value ratios in Korea, or to the implications of
different models, one conclusion we can draw is that those instruments are not sufficiently
strong to tame the financial cycle. One interesting aspect of the model by Goodhart, Kashyap
et al (2012) , that I already quoted, is precisely that its simulations show that none of the
analysed instruments (dynamic provisions, loan-to-value ratios, capital requirements, liquidity
coverage ratios and margin requirements on repos used by shadow banks), would not be
enough, even combining some of them, to smooth the financial cycle. The difficulty comes
from the fact that the boom brings large increases in asset prices and this provides a
misplaced sense of wealth improvements and a temptation to further leveraging. In this
context, they nevertheless conclude that dynamic provisioning and liquidity requirements can
be the more effective tools but still insufficient as the Spanish experience shows. Banks
became more resilient but the bubble was not prevented.
All these points indicate that there must be a role for monetary policy to address financial
stability considerations even when the priority target of monetary policy is price stability as
this goal is affected in the medium term by financial instability. Traditionally monetary policy
is only concerned about price stability, particularly in the inflation targeting regime, even if
central banking has since the XIX century cared for financial stability in the form of
lender-oflast-resort for banks in times of liquidity distress. This asymmetric policy of only "mopping-up"
with liquidity in financial market downturns but ignoring the risks of the upside booms creates
moral hazard and provides a significant "liquidity subsidy" to the financial sector.
The arguments against doing otherwise have been centred in the difficulty of "identifying
bubbles" or in the danger of "pricking bubbles". Nevertheless the on-going debate is not
anymore about "pricking bubbles" but concerns the inclusion of financial conditions in the
optimal monetary rules as in the models developed by Christiano, Motto, Rostagno (2009),
14
See Brunnermeier, M. and N. Sannikov (2012), "A macroeconomic model with a financial sector", Working
paper.
15
See Adrian, T. and H.S. Shin (2010), "Financial intermediaries and monetary economics", in B. Friedman and
M. Woodford (eds.), Handbook of Monetary Economics, Edition 1, Volume 3, October.; Maddaloni, A. and
Peydro, J.-L. (2010), "Bank risk-taking, securitization, supervision and low interest rates: evidence
from US and Euro area lending standards", Review of Financial Studies,
http://www.ecb.europa.eu/pub/pdf/scpwps/ecbwp1248.pdf; Jimenez, G., Ongena, S., Peydro, J.-L. and
Saurina, J. (2012), "Credit Supply and Monetary Policy: Identifying the Bank Balance-Sheet Channel with
Loan Applications", American Economic Review, http://www.tilburguniversity.edu/webwijs/files/center/
ongena/preprints/jopscc.pdf.
16
See Borio, C., Zhu, H. "Capital regulation, risk-taking and monetary policy: a missing link in the transmission
mechanism?" BIS WP n. 268, December.
Curdia and Woodford (2010) or Gertler and Karadi (2011)).17 The new models are
nevertheless not mature enough and do not include all relevant financial frictions. A pure
"leaning against the wind" policy is possible but has limitations although, in any case,
monetary policy should become less asymmetric and complement the indispensable
regulatory and macro-prudential policies.
While these reflections only provided a snapshot of the plethora of research currently being
undertaken in the field of financial stability analysis, in my view these are some of the key
elements. It also broadly reflects our own efforts here at the ECB to further develop and
implement an appropriate financial stability analytical toolkit. This is the topic to which I now
turn.
2. The ECB's tools for financial stability analysis
Beyond the academic research, a lot more analytical macro-prudential work is undertaken
here at the ECB, as it's the case at other central banks. Our main aim with this work is to be
in a position to carry out systemic risk assessments in real time, directly and regularly
supporting policy discussions. For this purpose, we have at our disposal a number of tools
and techniques to help us form a comprehensive view of prevailing systemic risks and to
help assessing and quantifying the impact of these risks, were they to materialise, on the
banking sector and ultimately on the real economy.
More concretely, we structure our financial stability analysis in the usual way with three broad
elements. The first entails an identification of important sources of system-wide
vulnerabilities based on an analysis of the individual and collective strength of the different
parts of the financial system - institutions, markets and infrastructures. The second is an
assessment of the potential costs - to the real economy - should some combination of the
identified risks and vulnerabilities materialise. A proper indicator of systemic risk should entail
both of these properties, the probability of an adverse event occurring and the potential
impact of such an event occurring. A last element is methodologies examining network
fragilities and contagion.
Starting with the identification of potential sources of systemic risk, our analysis focuses on
two broad types of indicators:
The first set of indicators characterise the current state of financial stress in the financial
system, i.e. indicators that works as "thermometers" of the level of tension in the financial
system. As crises tend to exhibit many different manifestations, it is obvious that no single
metric can gauge the current level of systemic stress. In practice, we cross-check and report
on a variety of complementary indicators. Let me mention a few examples.
One class of approaches employed in practice here at the ECB can be classified as "market
based indicators" - that is, with a focus on signals from both financial markets and financial
institutions. At least four examples of distinct indicators in this category can be mentioned.
First, general financial market stress is quite accurately captured by the so-called coincident
indicator of systemic stress, or "CISS", which succinctly synthesises the interaction of stress
across key market segments also taking into account explicitly the correlation structure of
different segments.18 A second indicator in this class of measures focuses specifically on
systemic stress within the banking sector - examining the onset of systemic stress through
the lens of joint probabilities of default on the basis of CDS pricing of financial institutions.19 A
third group of market based indicators focus squarely on liquidity conditions - either in
specific market segments (e.g. the money market) or across financial market segments.20
Lastly, novel methods such as self-organising financial stability maps provide an alternative
means of gauging systemic stress through visual means - thereby providing a useful
complement to numerical signalling methodologies.21
Another separate class of indicators we regularly report characterising the current state of
financial stability can be classified as "structural indicators" - that is, examining potentially
excessive leverage and credit developments - as well as disequilibria in specific asset price
segments in specific economies or sectors. Examples of indicators in this category are
numerous, but clearly encompass models of credit booms as well as various estimates of
valuation in real estate markets.22 Both such sets of indicators can provide indications of
buildup of imbalances but suffer from one drawback. Assumptions need to be made about
what defines excessive developments. These assumptions, accordingly, must be robust as
otherwise they risk being challenged by addressees of policy recommendations.
The second set of indicators more explicitly strives to predict vulnerable states of the
financial system, i.e. early warning indicators - be in the form of univariate indicators,
multivariate models or early warning systems. The key feature of all the categories of early
warning indicators is that their signals are evaluated in an early warning framework, thus
historically measuring the performance in terms of correctness and timeliness of the signals,
potentially taking into account the relative preferences of the policy maker between type 1
and type 2 errors. This is an active field at the ECB - a representative example in this
respect would be the work of Alessi and Detken arguing that the global credit gap is the most
robust early warning indicator for costly aggregate asset price booms or the work of Lo Duca
and Peltonen building on systemic risks stemming from a combination of domestic and global
macrofinancial vulnerabilities.23
Of course, the triggers and exact timings of crises are extremely difficult to predict. However,
the underlying vulnerabilities, at least based on past experiences, seem often to be
detectable - one needs to at least control for "known knowns" or "known unknowns". Indeed,
many crises follow a very similar pattern featuring excessive leverage. Accordingly, the fact
that early warning seems possible has practically become part of the layman's lexicon - not
least given widespread even popular appeal of analyses on historical crises (e.g.
ReinhartRogoff). Despite these strides, much remains to be done until policymakers can be fully
confident enough to implement and make use of robust early warning systems.
Let me move to One of the major tools to perform financial stability
the assessment tools.
assessments is stress testing, primarily of the banking sector, but also conducted for the
insurance sector - including sensitivity and scenario analyses. Stress testing tools allow for
evaluating the impact on banking sector solvency of severe, but plausible macro-financial
19
See, for instance Box 8 in the June 2012 ECB Financial Stability Review, "Systemic Risk Measure - A
portfolio probabilistic perspective on measuring default risk".
20
See regime-switching methodology in Box 4 of the June 2012 Financial Stability Review, "Addressing stress in
interbank markets and the role of unconventional monetary policy measures" and general liquidity indicator in
Box 9 in ECB, Financial Stability Review, June 2007, "Understanding financial market liquidity".
21
See P. Sarlin and T.A. Peltonen, "Mapping the state of financial stability", ECB Working Paper Series,
No 1382, 2011.
22
On credit, see for instance Schwaab B, S Koopman and A Lucas (2011), "Systemic risk diagnostics:
coincident indicators and early warning signals" ECB Working Paper No 1327 (April); for commercial property
prices, see Box 6 in the December 2011 ECB Financial Stability Review or for residential property prices, see
Box 3 in ECB, Financial Stability Review, June 2011.
23
See Lo Duca M and T Peltonen (2011), "Macro-financial vulnerabilities and future financial stress: assessing
systemic risks and predicting systemic events", ECB Working Paper No 1311 (March).
scenarios that reflect key systemic risks. On this basis, we use our (top-down) stress test
tools to rank the impact of prevalent macro-financial risks in order to gauge the
resilience of the banking sector.
The top-down, or macro-prudential, stress-testing framework developed by the ECB has
proven particularly valuable during the financial crisis and the euro area sovereign debt
crisis. Systemic risks emerged, intensified and evolved rapidly, calling for a flexible and
operational tool that could deliver quantified impact assessments in a timely fashion. The tool
is comprehensive enough to cover individual banks and it incorporates real-financial
interactions as well as network models to assess contagion risk.
These features notwithstanding, and despite its increasing prominence in financial stability
analysis and communication, stress testing has its limits. Notably, even state-of-the-art
stress testing frameworks are characterised by substantial methodological limitations.
The major challenges facing stress testers today range from dealing with the inevitable
subjectivity related to scenario building, how to model and integrate in a consistent way
within the framework elements, such as endogenous bank responses, interbank spillover and
macroeconomic feedback effects. Many of the available models also have difficulties
capturing well the often non-linear tail risk effects that the scenarios are typically meant to
reflect. Finally, stress test results are which in particular
only as good as the data available,
for central banks and other macro-prudential authorities without supervisory access is a key
deficiency.
Finally, let me add that even though our top-down stress testing framework is far from perfect
and suffer from many deficiencies, it has proved a useful tool to challenge the more granular
bottom-up approaches, such as the EBA EU-wide stress tests, and especially to detect
outlier responses by individual banks in the latter case.
The last broad element of ECB financial stability analysis is the rapidly burgeoning literature
on contagion. I reviewed some ECB work in this area in a speech last October.24 In that
speech, I mentioned several analytical perspectives we use to examine contagion in all its
forms relevant for the ongoing sovereign crisis in the euro area - highlighting models
capturing the interaction between sovereigns, as well as that between sovereigns and banks.
Such models make use of multiple techniques to uncover contagion - namely, multivariate
frequency decompositions, regime-switching approaches and exploiting generalised
measures of risk aversion in entity-specific frameworks. Clearly, the issue of contagion is not
distinct from that of network analysis. While work in this area is broad, I can point to some
recent ECB work featured in our latest Financial Stability Review - in which tools and results
are presented regarding applications of network analysis both for actual collateral holdings
and simulated interbank networks.25 Ultimately, work in this field remains still relatively
nascent and I am sure more highly relevant applications will follow with time.
3. The macro-prudential policy framework and instruments in the EU Single
Market
Let me now turn to the design of a macro-prudential policy framework and the definition of a
policy toolkit that is expected to be available for authorities to address the identified systemic
risks in Europe.
Since the outbreak of the financial crisis, policy makers have gradually placed more and
more emphasis on a macro-prudential approach of financial regulation. The first step in this
process was the establishment of the Financial Stability Board as a global coordinating body
which was followed by setting up authorities with explicit macro-prudential mandates at the
national level as well. An important milestone in this process was the establishment of the
ESRB in Europe last year. Besides its role in facilitating discussion on macro-prudential
mandates and institutional set-up at the national level, the ESRB plays a key role in
developing a toolkit of macro-prudential policy instruments that national authorities can use
within the European legal framework.
In this context, a major policy challenge Europe is currently facing is the implementation of
the Basel III standards in a way that would allow authorities to use policy tools for
macroprudential purposes as well. I would like to highlight in this regard that Basel III already
includes some elements of a specific macro-prudential toolkit, such as the counter-cyclical
capital buffer, which requires banks to build up capital buffers in periods of excessive credit
growth. These buffers can then be released in stress situations, which would help institutions
to avoid becoming constrained by regulatory requirements and may thus enhance their ability
to maintain lending activity.
However, when having a closer look at the Basel III agreement, we have to acknowledge that
most elements of the new framework are traditionally considered as micro-prudential in
nature. The capital and liquidity rules are designed so as to address risks at the level of
individual institutions. Still, depending on how these instruments are calibrated, they could, in
principle, be also used to address macro-prudential concerns and mitigate systemic risks.
This is a topical issue from a policy perspective in Europe, given that discussions are at their
final phase on the implementation of Basel III through the so called "CRD IV", which includes
a proposal for a directive and a regulation. Importantly, the regulation will introduce a new
feature in financial regulation, namely that the prudential standards laid down in this
legislative proposal will be directly applicable in all EU member states.
You may already be aware of the concerns that have recently been raised by some
authorities and member states with regard to their ability to use the policy tools falling under
the regulation for macro-prudential purposes. Concretely, they claim that, if capital and
liquidity rules and other micro-prudential instruments are introduced as elements of a "single
rulebook", this would imply a "maximum harmonisation" of prudential requirements.
Consequently, member states may be legally prevented from adopting more stringent rules,
even if systemic risks would justify that.
I share these concerns. However, I would also like to highlight some issues that I consider as
a prerequisite for the conduct of efficient macro-prudential policy in a single market.
First, as regards the "single rulebook", the ECB has expressed on many occasions its
support towards this approach. We have underlined that the "single rulebook" contributes to
a consistent implementation of prudential measures in the Single Market, improves
transparency and ensures a level playing field for financial institutions. By avoiding regulatory
arbitrage and distortions to competition, the "single rulebook" is also beneficial from the
perspective of financial integration in Europe.
At the same time, however, let me also underline significant risks to financial stability can
emerge when systemic risks identified at the national level may impact other jurisdictions
through spillover effects and common exposures of financial institutions. It is therefore of
paramount importance that national authorities have the possibility to impose, in a well
identified subset of instruments, more stringent rules than those defined by the regulation.
Given that member states may well be at different stages of the economic and financial cycle
within Europe, and there are also significant differences in the structural features of the
financial sector across EU countries, authorities should have the control over an appropriate
set of tools to address both the cross-sectional and the time dimension of systemic risks as
well.
In my view, the appropriate macro-prudential regime in a single market should have three
main features:
First, adjustments in the prudential rules for the identified subset of instruments should only
be possible in the direction of strengthening the harmonised minima. These instruments
could include capital and liquidity ratios, leverage and limits to large exposures
(Loan-toValue or Debt-to Income ratios are not limited by the CRD IV).
Second, only calibrations should be subject to upward adjustment, while definitions should
remain intact so as to ensure that ratios are comparable across institutions and countries,
thus respecting the principle of a single EU rulebook.
Third, this macro-prudential regime should be subject to strict safeguards, under the
exante coordination of the ESRB in order to avoid, or at least to minimise, possible unintended
consequences and spill