Graeme Wheeler: Meeting demand for statistics in a fast moving world
Remarks by Mr Graeme Wheeler, Governor of the Reserve Bank of New Zealand, to the
Official Statistics User Forum, Wellington, 26 March 2014.
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Introduction
It's a pleasure to be here today and talk about the Reserve Bank's experience as a user of
official statistics. Like many central banks, we're a major user and producer of statistics.
We're a big user of economic statistics so I'll start by talking about some of our needs in this
area. I'll then go on to discuss our role in collecting, using and disseminating statistics on the
financial system and some of the changes we're facing. And I'll offer a central banker's view
of some of the challenges that statisticians face in meeting the growing demands from users
of these statistics.
At the Reserve Bank, we rely heavily on a broad range of economic data. Statistics New
Zealand produces many of the statistics we use but we also rely on data from other domestic
and offshore sources. Once every quarter, we undertake an in-depth forecast to arrive at our
best projection of where the economy and inflation are headed in the future. This in turn
helps guide our policy decisions. We use a range of economic models, all of which rely
heavily on data, and apply lots of judgment.
Our assessment of the economy is very comprehensive. When we look at the external
economy, we consider the economies of our major trading partners, the terms of trade, the
exchange rate and the current account. When we look at the domestic economy we consider
household and business spending, savings, credit trends and confidence. When we assess
inflation pressures, we consider the economy's growth potential alongside its actual growth
rate and take into account the labour market, import prices and other factors that influence
prices.
Let me give you an idea of just how reliant we are on economic statistics. Our system for
processing, storing and managing time series data is known as the Financial Sector
Information System (FSIS). We developed it about six years ago and it provides us with a
robust database for nearly all the data we produce or use. Today, FSIS holds around
36,000 time series. Around 20,000 of these are macro-economic time series relating to New
Zealand and the global economy. Statistics New Zealand would produce the lion's share of
those 20,000 series.
You'll be relieved to hear that I'm not going to talk about all 20,000 statistics but let me make
a few comments about what matters to us as a large scale user. Timeliness and reliability are
obviously important when we're trying to assess the economy in real time. So too is good
quality guidance on how the statistics are compiled or what the statisticians call "metadata".
When we encounter puzzles in the data, it is essential to be able to have open and honest
conversations with Statistics New Zealand about what might be causing them. Revisions
need to be handled carefully. Most data are revised from time to time, but if revisions are
large enough to re-write history, the original data would have had the potential to mislead
policymakers. The earlier we can learn about upcoming revisions and what is driving them
the better.
Another thing that matters for us and for all users of Official Statistics is harmonisation. The
economic data Statistics New Zealand produces should ideally be consistent with the
financial data the Reserve Bank produces. There is real value in working off a common
business register when we are putting together institutional statistics. That has real benefits
for all users.
What would be our top four 'wants' from Statistics New Zealand? We'd like sector balance
sheets that would tell us who owes what to whom across the economy and with the rest of
the world. We'd like a quarterly income-based measure of GDP, which would provide a
useful alternative perspective on output to the existing production and expenditure-based
measures. We'd like GDP to be rebased at the very least every 10 years to capture structural
change in the economy. And we would love a monthly CPI to enable more timely analysis
and forecasting of inflation.
We recognise that there are many statistical needs and resources are limited. But nor should
we lose sight of their value. New Zealand's annual GDP is more than $220 billion so better
quality or more timely decisions that result in a very slight improvement in economic
performance could easily be worth millions of dollars per annum.
We greatly value having a voice in Statistics New Zealand's data development process and
the opportunity to engage at a point in the process where our views can be taken into
account. By all accounts, our relationship with Statistics New Zealand is in a good shape but
both parties need to work hard and keep improving it.
The Reserve Bank's financial statistics
Turning now to financial statistics, the Bank is a major user of data on the financial system,
most of which we produce in-house, drawing on the powers under the Reserve Bank Act
(1989) to collect data from financial institutions. These data account for most of the other
16,000 time series in our FSIS database and include institutional data collected for prudential
purposes, data on the financial markets, data on notes and coins, and published financial
system statistics.
Our survey respondents include banks and other financial institutions and this "micro-data" is
used in our role as a prudential regulator and supervisor. Commercial confidentiality means
that this data isn't generally published, but we use it to compile broader financial system
statistics. We've a well-established practice of constructing and publishing these statistics.
An example would be the Standard Statistical Return for the banking system, which provides
comprehensive information on the banking system's balance sheet. Some of our statistics
act as inputs in the production of Statistics New Zealand's own statistics, including the
national accounts.
Table 1
Some key Reserve Bank Financial Sector Statistics
Collection Coverage
Standard Statistical Return Banks and Non-bank lending institutions
(SSR)
Credit card survey Credit card issuers
Liquidity survey Banks
LVR new commitments Banks with residential mortgage lending
Trade weighted indexes Major trading partner currencies
Planned/Under Development
Insurance data collection Licensed insurers
Managed funds survey Investment and superannuation funds managed by NZ fund
managers
Income statement survey Banks
Bank balance sheet survey Banks
NZ Securities database Securities issued in the New Zealand market
Financial statistics since the global financial crisis
Our financial data collections have grown substantially in recent years for three reasons.
First, the intensity of our prudential oversight has increased since the Global Financial Crisis
of 2008/09. We've sought to strengthen our prudential regime for banks for example.
As elsewhere, the GFC showed that risks around bank liquidity and funding in a period of
financial turmoil were potentially much greater than anyone had expected. In 2010, we
introduced new standards for banks requiring new minimum liquid asset requirements and a
minimum core funding ratio. Introducing these new standards meant that we needed new
liquidity and funding data to monitor compliance with the new standards at both an individual
bank and financial system level.
Another example of stronger prudential standards has been the introduction of temporary
speed limits on the banks' high-loan-to-value (LVR) lending reflecting our concern at the
growing risks in the housing sector. This, in turn, required us to collect additional data on
banks' housing lending broken down by LVR.
A second driver expanding our need for statistics has been the expansion of our regulatory
responsibilities in recent years.
Since 2008, the Reserve Bank has been given responsibility for the prudential regulation of
the Non-Bank Deposit Taking Sector (NBDT). New standards for capital, liquidity and related
party exposures inevitably require more data to be collected from the industry and may
prompt a further upgrading of the sector's statistics in the future.
In 2010, we became the prudential regulator and supervisor of the Insurance sector, which
up until that time had been relatively loosely regulated in New Zealand. This meant that there
is currently little in the way of formal statistics on the insurance sector. Consequently we're
currently planning a data collection from the industry designed to meet our prudential and
broader statistical needs. This is a major job as there are around 100 newly licensed
insurers, and there are a wide range of potential risks to cover.
The third driver behind the expansion in our financial collections has been growing demand
from the general public, international agencies, media and financial analysts in the years
following the financial crisis. There's a growing appetite for more granularity and detail in
financial statistics and for coverage of new areas. For example, there's demand for more
detail on the financial products and services offered by banks, expanded data on financial
prices, and the ability to drill down into financial sub-sectors to a rather greater extent than
before. And there's much greater interest in understanding the capital markets - an area that
to date hasn't been well captured in statistics in New Zealand.
Meeting demand for statistics in a fast moving world
What statistics to produce and when poses important challenges for us as the main producer
of New Zealand's financial statistics. We need to respond to the increasing demands for data
and data transparency but we also need to manage the cost, size and complexity of our
statistical function and keep respondent burden to an acceptable level.
Decisions to proceed with new collections must be based on a clear business case. In many
respects the decision to begin a new financial data collection has the hallmarks of an
investment decision to purchase a long-lived asset. We engage extensively with users in
trying to identify clearly the benefits of the new data for financial analysis and policymaking in
the future. Some of the benefits associated with new statistics accrue several years down the
track once a good time series is developed. Choices made now about what (or) not to collect
and how to collect it can have implications for the quality of financial analysis (or
policymaking) for years into the future.
In assessing the costs of the new collection we also focus on the costs that our respondents
might incur in undertaking significant internal system changes and enhancements in order to
provide the information. We have an obligation to ensure that the costs that they incur are
"worth it".
Keeping up with structural change is always a challenge. The absence of financial statistics
on a particular part of the financial sector can sometimes mask structural changes
completely, because financial analysts have no way of seeing them. More often, we may be
aware of shifting patterns but lack the statistics that can properly capture them. This can
occur when new types of financial institution develop or when existing financial activities
migrate from one type of institution to another that isn't well represented by our statistics.
Structural changes can be very difficult to detect when they involve new financial products,
unregulated institutions or the provision of financial services from offshore.
Structural change can also arise due to shifts in trading patterns between New Zealand and
the rest of the world. Since the 1970s, the Bank has published weighted average measures
of the New Zealand dollar relative to the currencies of our major trading partners. We report
a variety of real and nominal measures of these trade weighted exchange rates (TWIs) on
our website. Our flagship TWI was developed 15 years ago following the introduction of the
euro and is based on five currencies (the US dollar, Australian dollar, yen, euro and British
pound). Since then, trading patterns have changed dramatically. In particular, China is now
the largest single destination for New Zealand's merchandise exports and its exchange rate
has become more flexible. Some years ago we developed a broader 14 currency trade
weighted index, which included the Chinese currency and this is published daily on our
website alongside the five currency index. However, we are currently undertaking a full
review of all the exchange rate measures that we publish, which we hope to complete before
the end of the year.
Even with good statistical practices, and extensive liaison with users, many statistical
collections ultimately become obsolete and need overhauling. Our standard statistical return
for the banking system has served us well over the past 15 years but we're now
redeveloping it. That reflects changes in the banking sector over the period and a better
understanding of what to monitor in the sector. For example, the existing return provides little
if any data on the banks' incomes and expenses and other performance metrics. Our hope is
that a new collection methodology will serve us well for the next 15 years.
During the rapid changes associated with the GFC, it became clear that the traditional time
lags in the availability of some of our financial sector data became too long for fully informed
analysis. Increasingly we drew on data from banks' internal management systems that could
be provided closer to real time.
We've used this experience to try and shorten the time lag in the availability of some of our
financial data. We've done this in areas such as bank credit, liquidity, solvency and debt
issuance. Timeliness is essential for good policy making but timing also needs to be weighed
alongside other parameters such as data quality, respondent burden and the costs of
processing the data more quickly.
Financial systems are complex, and users - especially uninformed users- often have
difficulty interpreting the data. Our challenge is to provide the external users of our statistics
with metadata and guidance around the use of our statistics without overloading them with
too much information. As we seek to re-develop many of our statistics over the next few
years and develop new ones, we will need to give equal attention to the support we provide
to the users of the new statistics.
Let me conclude briefly by saying
There is no magic to good policy making. Good decisions depend on good quality statistics
and information. Official statistics play a crucial role in informing the decisions that we take.
They also provide accountability for those decisions. As a user of official statistics we would
like to see a number of improvements to the suite of data we consume. We want faster,
higher frequency, more comprehensive and higher quality statistics.
New Zealand's financial sector statistics, most of which are collected by the Reserve Bank,
are in the midst of substantial change. The insights and changes prompted by the global
financial crisis have provided us with a unique opportunity to assess the quality and fitness of
purpose of our financial statistics and given some urgency to introduce some new data
collections, redevelop existing collections, and explore new avenues for data supply. Whilst
we're the biggest user of our own statistics, we are taking into account the needs of a broad
range of stakeholders in meeting this challenge.
I wish you a fruitful two days.
Thank you.