Sabine Lautenschläger: 20 years of ESCB statistics - past
achievements and future challenges
Speech by Ms Sabine Lautenschläger, Member of the Executive Board of the European Central
Bank and Vice-Chair of the Supervisory Board of the European Central Bank, at the Ninth ECB
Statistics Conference "20 years of ESCB statistics: What's next", Frankfurt am Main, 10 July
2018.
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Ladies and gentlemen,
I believe the words of the late US politician Daniel Moynihan are a good starting point tonight. He
famously said, "Everyone is entitled to their own opinion, but not their own facts". I would add that
the best opinions are certainly rooted in facts. And, since we seem to have entered the age of
"alternative facts", I have been reflecting on what real facts are, and how to defend them.
And it's not just the age of "alternative facts"; it's also the age of "fake news". Still, neither of these
concepts is entirely new. For as long as there has been public discourse, people have been
tempted to propagate their own take on reality. And not all of them have been able to resist this
temptation. But still, something has changed. Today, Twitter and other tools allow almost anyone
to communicate with the general public. And fake news is most successful in creating alternative
facts when people stop trusting traditional sources of information.
This is what's happening right now, all around us. Traditional media have come under attack.
Some people place as much trust in an anonymous tweet or Facebook post as they do in an
article in the Financial Times, Le Monde or El País. Some people see "fake news" as real news
and "alternative facts" as a solid basis for taking decisions.
So, can data and statistics help to counter "alternative facts" and "fake news"? Can they help to
build a more solid base for making decisions?
Well, over the years, it has become somewhat fashionable to doubt the ability of statistics to
shed light on the facts, on the truth. I am sure that every statistician in the room has been told
more than once that "there are three kinds of lies: lies, damn lies and statistics". Ironically, the
quote has been attributed to so many different people that its true source is unknown. So tonight,
I think we should focus on how we can defend statistics and good data as a source of facts.
One of the key questions is how we can engage with those who doubt us. In my view, there are
two things we need to do.
The first is to admit that real-world statistics have their limits, and to be transparent about how
and when we use judgement. The second is to ensure that we, as institutions and as individual
experts, earn people's trust. Statistics is a discipline that is certainly aware of its own limits: it not
only acknowledges uncertainty, it quantifies it! But we must also admit that there is not just
scope, but also a need, to apply judgement when producing good data and statistics. And trust
plays a key role here. People can trust the ECB and the national central banks to apply expert
judgement when it is needed.
In my speech today, I will focus on key ingredients that have been crucial in building up the ECB's
good reputation over the past 20 years. The first is to have good data and to use them well when
taking decisions. The second is to ensure good cooperation. The third is to keep pace with
changing times.
Good data for good decisions
I am aware that the need for good data may seem self-explanatory, especially for an audience of
statisticians. But that doesn't make it less important, particularly in the case of the ECB. The
stakes are extremely high: whether for monetary policy or banking supervision, our decisions
impact the lives of over 340 million people. This gives the data we use, and the analysis we carry
out, enormous importance.
Our data need to be reliable and our statistics sound. Only then will they be able to form the
basis for good decisions. But not all data are created equal. Even well-collected data may fall
short of answering the burning questions of our experts. With the 2008 crisis, for example, we
learned the hard way why better and more granular data are necessary. Aggregate data provided
us with the big picture of the euro area economy and its financial markets. But the big picture
was too blurry. And, at times, it was downright misleading.
Money markets were a good example. After all, money markets are where the transmission of
monetary policy starts. Prior to the crisis, the ECB collected microdata on these markets through
the Euro Money Market Survey, the EMMS for short. This survey shed light on what was
happening in the money markets during the crisis. For example, in unsecured markets, we could
see that euro area banks were taking fewer counterparty risks with banks from other euro area
countries.
But our vision was limited. First, we didn't collect direct information on market rates, so we didn't
know how much each market participant was paying for liquidity. If we had had a full picture of
the dispersion of rates, we would have had less need to read between the lines. Second, we only
published the EMMS annually, which seriously limited the potential for research and analysis.
Research on a crisis that was developing by the hour could not be based on data published once
a year.
But we understood the shortcomings of the data and got to work. In 2016, we started to collect
money market statistical reporting, or MMSR, data. The MMSR data include trade-by-trade
granular data on four market segments. This means we receive full information on each trade -
the maturity date, the rate, the counterparty, the collateral and more. Data on the unsecured
market segment are published every six to eight weeks. With this project the ECB took an
important step towards the future, becoming a collector of "big data". But, of course, we didn't do
this on our own.
A tale of cooperation
Cooperation is often mentioned at conferences like this one. But in the field of statistics, it is
simply a reality that you won't get very far if you don't cooperate with others. Projects such as the
MMSR would never have come into being without good cooperation. In fact, the genesis of the
MMSR involved the central banks of four countries - Germany, France, Italy and Spain - and the
ECB. And of course, these institutions needed to cooperate with reporting banks. And
cooperation happens not only between institutions, but also within institutions: the constant
feedback loop between departments using the data and those preparing them leads to
highquality results.
But smooth cooperation has helped us from the start. It allowed the Eurosystem to achieve its
objectives from day one, 20 years ago. Thanks to a joint effort by the entire Eurosystem, we had
a set of harmonised euro area statistics from the very beginning of the ECB's existence. And
some 16 years later, when European banking supervision came into being, the Directorate
General Statistics was able to provide the supervisory data we needed right from the start -
thanks to another joint effort.
Indeed, as the ECB's functions have expanded, statistics have had to follow. And of course, as
we have found ourselves needing more data to do our job, banks have found themselves having
to report not only more data, but also more granular data. We try at all times to be mindful of the
reporting burden that banks have to bear. Regular merit and cost procedures are applied to new
data collections. More recently, we have started to hold public consultations on proposed new
statistical reporting requirements. This will help to ensure all stakeholders have the chance to
express their views.
Cooperation also helps us to make reporting more efficient, which in turn reduces the burden on
banks. And here, we have worked on two fronts. With the ESCB Integrated Reporting
Framework, we aim to aggregate and harmonise banks' reporting requirements. With the Banks'
Integrated Reporting Dictionary, the BIRD, we support banks in organising their data with a view
to reporting it more efficiently. Towards this end, experts from national central banks work with
experts from commercial banks to define the data and data transformations needed to comply
with the reporting requirements for AnaCredit and the Securities Holdings Statistics. So, banks
that choose to participate are being helped to do a job they would otherwise have had to do on
their own.
Cooperation with institutions beyond the ESCB has also been vital. The members of the ESCB
and the European Statistical System partnership have worked closely to ensure the production of
complete and coherent European statistics. We - central banks and statistical institutes - have
been doing this with remarkable results in the Committee for Monetary, Financial and Balance of
Payments Statistics since 1991. And since 2013, we also meet in the European Statistical
Forum to discuss topics of strategic cooperation with the heads of national statistical institutes.
Keeping pace
It's clear that cooperation is key to getting our job done. But these days, a job well done requires
much more than it used to. Central banks need to keep pace with a world that is changing at an
ever-faster pace. How do we do that? How do we keep pace? Well, for one thing, we need to be
open to new ways of doing things.
On this front, I am sure the two words on everyone's minds are "big" and "data". It's true that we
central bankers have not exactly been at the forefront of the big data revolution. After all, we are a
bit cautious by nature. And we know that big data means different things to different people; and
we know that we cannot yet say with certainty which big data applications will be truly useful
Big data are quite different from traditional, structured data. So we have much to learn and many
challenges to tackle. Collecting the data is only where the challenges start. We also need to
adapt verification processes to ensure that the data are of high quality. And this is where big data
already pay off, indirectly at least. Big data has brought us tools and techniques that can be
applied to rapidly process large sets of traditional data too.
This makes it much easier for us to realise projects like MMSR and AnaCredit and helps us to
keep pace with an ever-changing world. AnaCredit, for instance, involves immense sets of
extremely granular data, reflecting the far greater complexity and interconnectedness of today's
economy. To understand this complexity and assess the interconnections, we need a very
detailed view. And this is exactly what AnaCredit gives us. Thanks to the granular data it
provides, we will be better able to understand what is driving credit growth, making it easier to
know whether such growth is healthy or not.
MMSR, on the other hand, is about speed: money markets move fast and never stop. So taking a
snapshot every now and then does not suffice. We need much faster data, and that's what
MMSR provides. It allows us to constantly assess who lends how much money to whom in the
money market and at what rates. This gives us a very clear and quick picture of how the market
is structured, how exposed players are to one another and how vulnerable they are.
And MMSR helps us to keep pace in other ways too. Look at the important role benchmark rates
play. They provide anchors for contracts in financial markets and are important for the
transmission of monetary policy. The ECB thus decided to develop a benchmark rate: a new
daily euro short-term rate, also known as ESTER. This rate will complement existing rates by the
private sector and serve as a backstop to them. The ECB will start publishing ESTER by
October 2019. This project will entail significant challenges. Every working day, we will need to
produce a reliable rate, based on individual transactions. This will need to happen within a very
narrow time frame, while ensuring full quality control.
Leadership
Ladies and gentlemen, I have talked a lot about past achievements and future challenges. And I
have talked about the need to work together as a team. But, of course, all good teams need good
leaders. And speaking of good leaders brings me to Aurel Schubert. As Aurel is due to retire
soon, I would like to take the opportunity tonight to say a few words about what he has done for
this institution.
For eight years now, he has steered the ECB statistics ship with great competence. Aurel has
made invaluable contributions to some of our most ambitious projects: the granular Securities
Holdings Statistics, the MMSR and Anacredit. Thanks to his leadership, supervisory statistics
were available from the start of European banking supervision. He helped amend our statistical
legal framework to align it with international standards.
But, of course, his career started long before he became Director General of Statistics. He has
worked in the field since 1997. Over these past 21 years, he has participated in 90 meetings of
the Statistics Committee and chaired 34 of them. He has also been a Vice-Chair of the Irving
Fisher Committee, a Co-Chair of the European Statistical Forum, and Chair of the ESRB contact
group on data.
All these achievements are facts, of course. And they show that Aurel knows his subject, thinks
strategically and masters the politics. These are all important aspects of being a good leader.
But they are not the only things that are important. A leader cannot act alone; they rely on other
people. And Aurel is an outstanding people manager. I think he can teach us all a thing or two
when it comes to forming a team, keeping people motivated, managing change and, most
important of all, creating an atmosphere of trust and mutual respect. In that sense, I see him as a
role model. Aurel, I thank you very much.
Conclusion
Ladies and gentlemen,
In my speech tonight, I have reminded you of some of your many achievements, both recent and
past.
But what matters most is not the next big project or the latest database. What matters most are
the high professional standards which you have all maintained in your work. And, if we want to
keep fighting alternative facts with real facts and fake news with real news, you must continue on
this path with the same conviction as you started out with in 1998.
And now let me conclude with a fact of life that is all too true: dinner speeches are always too
long. There is no way to spin this any other way.
So thank you for all your good work, and thank you for your attention.