Charles Bean: Measuring recession and recovery - an economic
perspective
Speech by Mr Charles Bean, Deputy Governor for Monetary Policy at the Bank of England,
at the Royal Statistical Society (RSS) Statistics User Forum Conference, London,
27 October 2010.
* * *
Good morning! It is a great pleasure to open this conference dedicated to exploring the way
statistics are used in the study and control of the business cycle and, in particular, the issues
thrown up by the Great Contraction of 2008-9. Before I turn to that topic, however, it might
be useful if I start by saying a few words about the sort of information that the Bank of
England's Monetary Policy Committee (MPC) relies on when it sets the level of Bank Rate
(or the amount of asset purchases) each month.
First, and most obviously, there is the wealth of official statistics on the economy generated
by the Office for National Statistics (ONS) and other national statistical agencies, covering
such variables as output, employment, pay and prices. That is the absolute bedrock on which
our analysis and policy rests, and without it we would struggle to do our job.
But the picture they provide is rarely perfect. Series often do not quite correspond to the
appropriate economic concept, either because they are conceptually difficult to measure or
else because only imperfect proxies are available. As an example, take output. In the old
days, when the economy was dominated by manufacturing, it might have been relatively
easy to measure the volume of output and value added of different industries. But our
economy today is dominated by services. Conceptually even defining the value added in,
say, the financial sector, let alone measuring it, is not straightforward. Moreover, the meaning
of a series often changes subtly over time as the economy evolves. Manufacturing today is a
very different animal from manufacturing 30 years ago: for instance, the value added of
Rolls-Royce aero engines today comes as much from the after-sales and maintenance as
from the engine assembly itself.
Finally, and most saliently for real-time policy analysis, the official data invariably appear with
a delay of some months and can be substantially revised as more information accrues and
the ONS improve their methodology. For that reason, the Monetary Policy Committee
supplements the official data with two other sources of information that are more timely, even
if they lack precision compared with the official data. The first are the regular business
surveys from the likes of the Confederation of British Industry and the British Chambers of
Commerce. As many of these have been going for quite a while, we have in many cases
been able to establish their usefulness as predictors of the not-yet-available official data.
Second, we also rely on the information provided by our network of regional Agents who
have about 8000 business contacts across the country. They can often help the MPC
understand what lies behind puzzling movements in the official data or in the business
surveys. And, though the evidence they provide is more qualitative rather than quantitative,
they can give us early warning of major cyclical developments. The outstanding example
here is in the aftermath of the collapse of Lehman Brothers and the subsequent near-seizure
of the global financial system in early October 2008, when our Agents reported many of their
contacts saying that "orders had fallen off a cliff" - the first real indication of the severity of
the contraction that was to follow over the next nine months.
The sharpness of that contraction, as well as its unexpected nature, can be seen in Chart 1,
which plots the path of four-quarter real GDP growth on top of the fan chart associated with
the MPC's projection for growth, conditioned on prevailing market interest rates, made in
August 2008. Given that each shade of green corresponds to 10% of the possible outcomes
and the whole fan covers 90% of the possible outcomes, it can be seen that the MPC had
collectively assessed the probability of contraction over the four quarters to 2009 Q2 as
about a half, but the probability of growth being less than -11⁄2% as just 1 in 20. Now the
MPC does not attempt to calibrate the probabilities associated with tail events precisely. But
it is a fair bet that, if we had, then we would have put the chances of a contraction as large as
the ONS's current estimate of 6% as being virtually negligible.
It is worth stressing that we were not alone in thinking a very severe contraction in activity
was unlikely. Almost all forecasters were in the same boat. For instance, when we prepare
our projections each quarter, we also canvass the views of outside forecasting bodies. Their
assessment of the probabilities of various ranges of possible outcomes was very similar to
ours.1 Chart 2 illustrates the same point, but puts it into a broader context. The blue line
shows the actual path of four-quarter GDP growth over the period since the creation of the
MPC, while the pink line shows the Committee's central (mean) projection from a year
earlier. The green bars show the range of end-year forecasts for the following year produced
by about 25 other organisations, together with their corresponding average (the green
diamonds). The striking feature is the close proximity of the MPC's projections and the
average of the outside forecasts throughout the sample. For most of the period - one in
which, it should be said, growth was unusually stable - those forecasts are close to the
subsequent outturns. The two exceptions are the Great Contraction of 2008-9 and the
"phantom" slowdown after the 1997-8 Asia/LTCM crisis, when early vintages of the official
data for output as well as business surveys pointed to a slowing in growth that was not
subsequently borne out in mature vintages of the official data. And for both these episodes,
no forecaster came close to predicting the outcome.2
The generic point here - which holds true in fuller analyses over longer time periods - is that
the big divergences, when they occur, are not between the central forecasts made by
different bodies, but rather between those forecasts and the corresponding outturns. And that
is as it should be: deviations of outturns from central (mean) forecasts should be
unpredictable if those forecasters are using the information that is available to them
efficiently.
Why then, as the Queen famously asked at the London School of Economics in November
2008, did no-one see the Great Contraction coming? Some economic downturns are broadly
predictable in nature. In particular, that is the case when they are deliberately policy-induced
in order to squeeze inflation down, though even then it may still be difficult to get the
magnitude and timing right, and there will always be other unexpected events that perturb
the path of the economy. But downturns associated with financial or banking crises are rather
different animals. Rapid growth in credit and asset prices can act as a warning sign of
building vulnerabilities, but frequently appear to be validated by developments in underlying
economic fundamentals. In the case of the present crisis, those developments included: low
long-term real interest rates associated with high savings rates in emerging market
economies; an unusually stable macroeconomic environment, with an associated apparent
reduction in risk; and financial innovation which purported to distribute risk more widely rather
than leaving it concentrated in the banking system.
With hindsight, we now know that much of that financial innovation in fact left risk
concentrated in the banking sector; it was in effect simply shifting maturity transformation off
balance sheet, where it was not subject to the same regulatory requirements. To that must
be added: the underestimation of risk, coupled with inadequate risk management; distorted
incentives facing the originators of US sub-prime mortgages and the ratings agencies
responsible for assessing complex structured finance assets. Finally, the complexity of those
products and the high degree of interconnectedness between financial institutions meant that
the financial system, instead of becoming more stable, had in fact become more vulnerable
to failure.
The lesson I want to draw from this is not that the problems in financial markets which began
in August 2007 and culminated in the near-meltdown of the global financial system a little
over a year later were an inherently unpredictable Act of God. Rather it is that one would
need to be endowed with perfect foresight to have been able to predict how the financial
crisis would unfold, spilling over from one institution to another, and from one market to
another. And who knows what would have happened if, for instance, Lehman Brothers had
successfully found a buyer that weekend in September 2008?
Moreover, the impact on the real sector, which is what concerns us here, was also extremely
difficult to judge. While it was predictable that the availability of credit would tighten as risk
aversion rose and financial institutions rushed to de-leverage their balance sheets, it was far
harder to know by how much. And much of the contraction in household and business
spending appears to have been down to a sharp rise in precautionary saving and the
postponement of investment projects and the running down of inventories as uncertainty
rose. Again, while such a reduction in spending was plausible, it was nevertheless extremely
difficult to judge its likely magnitude.
The moral from this is that one should not expect to be able to predict the timing and scale of
these sorts of events with any precision. But financial institutions and policymakers could
- and should - have been more alert to the vulnerabilities that were building during the years
leading up to the crisis and therefore to the possibility of a major shock to the financial sector
and to the economy more generally. It is somewhat analogous to seismologists trying to
predict earthquakes along a fault line. It is impossible to predict the day and magnitude of a
shock with any precision, but it may be possible to say something about the likelihood of an
earthquake occurring within a given period from seismic measurements and indicators of
latent stress.
Now it might seem natural to measure the severity of a recession by the magnitude of the fall
in output. Indeed, a recession is sometimes characterised in the media as being two or more
consecutive quarters of falling output, with the end of the recession being marked by a return
to expansion. But that is not a very useful definition, as the mere resumption of growth will
still leave some plants idle and some workers unemployed. From an economic perspective, it
should be the margin of unused resources in the economy - the difference between actual
and potential output - that we care about. And it is also the margin of unused resources that
determines how much the economy can grow during the recovery before it puts significant
upward pressure on inflation3, the control of which is the MPC's primary objective.
The problem is that the level of potential output is inherently difficult to measure. For an
individual firm, the notion of capacity is slippery. A car manufacturer might be able to say
how many units can be produced if all production lines are operating 24/7, but he knows that
to do so would prevent essential maintenance and impair the firm's ability to produce output
later. And in the service sector, the notion of capacity is even more complex. What is the
capacity of a law firm, for instance? One might be able to say how many hours the existing
partners could work, but that is not the same as how much output they could produce.
Moreover, it is impossible to match unemployed workers to unfilled vacancies
instantaneously, so it is not appropriate to ask what level of output could be achieved if all
those who wanted a job were actually in one. The frictions and the institutional characteristics
of labour and product markets need to be taken into account too.
Economists studying business cycles have used a variety of approaches to construct proxies
for potential output. One is to assume that potential output evolves smoothly over time and
that actual output fluctuates around this; potential output can then be proxied by a smooth
trend line fitted through the more jagged path of actual output. A more structural approach
takes measures of capital and the available labour force (after allowing for any labour market
frictions) and then assumes something about the nature of the technology with which they
are combined to produce output. A third approach eschews direct measurement of potential
output altogether and instead uses survey-based measures of the margin of unused
resources to draw inferences about the evolution of potential output.
While judging the margin of spare capacity is always a problem for policy makers, it is
particularly difficult at the current juncture because a banking crisis accompanied by a deep
recession is likely to lead to some impairment of the economy's supply capacity. Moreover,
different approaches presently suggest very different degrees of supply impairment. Suppose
we use the first of the approaches above, assuming both that the economy was operating
around potential in the years leading up to the crisis and that potential output had continued
to rise at broadly the same rate throughout the recession, reflecting continued growth in
human knowledge. That approach would point to output being a little under 10% below
potential at the current juncture, an enormous margin of unused resources.
But we get a very different picture if we look at direct measures of the margin of unused
resources. Chart 3 shows a swathe of alternative indicators of capacity utilisation drawn from
business surveys. They suggest that the margin of spare capacity within firms is now
relatively modest. As far as the labour market goes, the rise in unemployment has been only
a little over two percentage points, notably less than in earlier UK recessions even though
the fall in output has been greater; see Chart 4. Together, these observations suggest a far
more modest margin of unused resources and, by implication, a substantial depression of
potential output resulting from the Great Contraction.
There is, however, an important qualification. The counterpart to the modest rise in
unemployment is a much smaller fall in employment than would have been expected on the
basis of past experience, in part reflecting a high degree of wage moderation in the private
sector. This can be seen in Chart 5, which contrasts the evolution of employment and output
with the experience during the recession of the early 90s, when output fell less but
employment more. The corollary is that productivity growth has been extremely weak during
this downturn. That is in stark contrast to the United States, where productivity growth has
remained strong and there has been a large shake-out of labour. Now this could be indicative
of a fall in potential output. But it could also indicate a considerable degree of labour
hoarding, which would be consistent with a rather greater margin of underutilised resources
than suggested by Charts 3 and 4.
A number of recent cross-country studies4 have documented the substantial and long-lasting
effect on output of past recessions caused by banking crises. That is illustrated in Chart 6.
The dark blue line shows the mean fall in output relative to a continuation of the pre-crisis
trend (calculated omitting the three years preceding the crisis) across 88 previous systemic
banking crises in advanced and emerging market economies. The average decline in output,
relative to a continuation of the pre-crisis trend, is around 10% and remarkably persistent,
suggesting that ultimately aggregate supply follows aggregate demand down, even if it does
not fall immediately. The UK experience (red line) has so far been fairly similar to that
average past experience, although the most recent quarterly outturns have been somewhat
stronger than one might have expected. Chart 6 also reveals, however, a very marked
heterogeneity across episodes, with the blue swathe covering the central 50% of the
distribution of outcomes and the grey swathe 90% of the distribution; a substantial
permanent loss in output is by no means pre-ordained.
There are a variety of ways that a banking crisis might impair an economy's supply capacity.
Reduced availability of credit and lower activity are both likely to depress investment, which
has indeed fallen sharply. They are also likely to result in more business bankruptcies and
fewer new firms being formed, though here the evidence is rather more positive, with
liquidations rising much less during the recession than one would expect (Chart 7). Finally,
as we saw in the eighties, high levels of unemployment can become entrenched if the
longterm unemployed are allowed to become disconnected from the labour market. But, as
Chart 4 shows, the rise in longterm unemployment has so far been modest, while the exit
rate from long-term unemployment into jobs has been broadly flat.
So, at the current juncture, some indicators seem to suggest a rather large margin of spare
capacity, while others point to a much smaller margin. Now it may be possible partly to
reconcile these apparently conflicting observations once one allows for the fact that in some
businesses, especially in manufacturing, it may be possible to shut down some capacity
temporarily, reactivating it at relatively low cost once conditions improve. To the extent that
the survey responses relate to the immediately operable capacity, rather than potential
capacity, it would be possible to have simultaneously a modest margin of spare capacity in
the short run, but rather more in the long run. Even so, the generic point remains that we
presently have only an imprecise idea of the margin of unused resources in the economy.
But this is a key determinant of how much the economy can grow before igniting inflationary
pressure, as well of the size of the structural fiscal deficit that needs to be closed.
Would better or different statistics have helped us in anticipating the recession, in monitoring
its evolution and in setting policy? Aside from the important, but unfortunately rather
challenging, matter of measuring the margin of unused resources in the economy, I do not
believe that the recession has highlighted any obvious lacunae in our conventional
macroeconomic indicators, though it has certainly presented us with plenty of puzzles. (It has
highlighted shortcomings in economic models, but that is a different story.) Rather the key
information gaps have been inside the financial sector. Some of these we have been able to
fill. For instance, in 2007, following the example of the Federal Reserve and the European
Central Bank, we had happily just decided to launch a regular survey of the banks in order to
provide more information on credit conditions. That has proved invaluable during the
recession as a guide to how the availability of credit was evolving. If we hadn't already
decided to launch such a survey, we would certainly have needed to introduce one.
We were already quite well served with information of key monetary and credit aggregates,
which have naturally taken a more prominent role in our analysis during the crisis. We did,
however, find that following the collapse of Lehman's, we needed a richer and timelier picture
of banking sector developments. We therefore instituted an additional regular survey of just
the major lenders; some of the resulting data appears in our publication Trends in Lending,
together with a commentary on credit developments informed by the associated discussions
with the lenders. We would, however, have liked access to more information on the evolution
of credit by industry and firm size so as to get a better handle on where credit constraints
were biting hardest. Gaining access to micro-prudential supervisory data relating to individual
institutions collected by the FSA has proved invaluable in assessing the resilience of the
banking system and thus its ability to supply the credit to support the recovery.
One area where more information would be useful is on the activities of the shadow banking
sector. Almost inevitably, one has less knowledge of these institutions than of regulated
entities. But we have seen that serious problems can arise in such hidden corners of the
financial sector. High-quality flow of funds data, similar to that available in the United States,
would also be valuable. That would facilitate a better understanding of the factors influencing
changes in agents' balance sheets, and thus be valuable in the pursuit of both monetary and
financial stability. Cross-sectional information on balance sheets within the household and
business sectors could also be useful in evaluating the seriousness of financial strains.
Finally, I think it is worth noting that if so-called macro-prudential policies are to be used
successfully to improve the resilience of the financial system and to moderate the credit
cycle, financial data collection will need to be more flexible in future. Almost certainly the
seeds of the next financial crisis will sprout in a different corner of the financial system from
this one. Collecting data dedicated to helping fight the last war will not serve, if those
emerging risks are to be identified early and dealt with appropriately.
Thank you.