T T Mboweni: Renewed challenges for model builders and forecasters in
times of extreme uncertainty
Keynote address by Mr T T Mboweni, Governor of the South African Reserve Bank, at the
SAKE24 Economist of the Year Award's Dinner, Johannesburg, 20 May 2009.
* * *
Distinguished guests, ladies and gentlemen
1. Introduction
Thank you for the invitation to address you on this important occasion. Since this is a
function to recognise the efforts of economic analysts to predict the future, it is fitting to share
a few thoughts on the challenges and serious issues that confront both model-builders and
forecasters in these most difficult and turbulent times.
The current financial crisis has forced us all to make a major re-assessment of the way in
which we have generally perceived the economy to work. Previous fundamental relationships
and economic correlations we took for granted have come under question and this has
caused intense debate in almost all areas of economic discourse.
The South Africa Reserve Bank and almost all of us here at this venue make use of various
tools in the form of structural models that help us analyse and forecast the future of the
economy. The fact that forecasts keep changing in such a dramatic way does not necessarily
mean that we are bad modellers or forecasters. But we must be aware of the limitations of
models, and the major challenges that face forecasters in this ever-changing economic
environment.
2. The use and challenge for models
At the heart of any economic model is a perception of how the economy works. This leads to
the representation of the structural economic relationships in the economy. This can either
be a "guesstimate" or gut feel, based on the modeller's knowledge of how the economy
functions or, alternatively, a well-articulated mathematical representation of the
interrelationships in the economy in the form of an econometric model.
There are significant differences between models, depending on the different views on how
the economy is seen to function, and also the use to which the model is being put. Although
the various types of models are structured to capture and replicate the economy by providing
for the key channels of the transmission mechanism, the emphasis tends to shift between
models. For example, the National Treasury will be interested in a model that is geared to
accurately assess the overall economic and financial market impact of the spending patterns
of government, while the central bank would be more concerned with having a model
specifically aimed at achieving its mandated inflation target and monitoring the economic
consequences of its monetary policy actions.
There is no unique model or best approach to the forecasting processes and procedures in
central banks. This is one reason why the South African Reserve Bank has adopted the
socalled suite of models approach. Central banks try to pursue full-information strategies. So,
instead of relying on just one model to produce the Monetary Policy Committee (MPC)
forecast, we employ a large variety of different models. Also, since the structures of the
various models are diverse, each one is capable of telling a different story. The
suite-ofmodels approach has the added advantage of taking some degree of model uncertainty into
account by taking all relevant and potentially-important information into consideration.
There are essentially two different types of models. The first is the structural macroeconomic
type of model which includes the traditional multi-equation model, and the second is a
shortterm time series forecast model. Each has its own set of benefits and disadvantages. For
example, we have the higher frequency autoregressive integrated moving average (ARIMA)
models which are useful for short-term forecasts but are incapable of predicting a turning
point since they are essentially based on their own historic trends. The structural
multiequation models such as the South African Reserve Bank's core econometric model is more
suited for policy analysis and forecasting since it incorporates behavioural relationships
between the key variables of the model.
Other structural models such as the dynamic stochastic general equilibrium models (DSGE)
and quarterly projection models (QPM) are more reliable over the medium to longer term but
are extremely sensitive to the initial conditions or data starting points of the forecast. This is
also a reason why many central banks that have adopted the DSGE approach spend a lot of
time and resources on determining exactly where the economy finds itself currently and how
far it is from the steady state.
Because of the lags in the response of inflation to changes in the monetary policy stance,
any forward-looking monetary policy framework requires a forecast of inflation. However,
forecasts should be used with the required degree of caution. Forecasts are, by definition,
surrounded by uncertainty, and knowledge about the degree of forecast uncertainty is
essential for decision-makers. Basically, we can identify five sources of forecast uncertainty:
uncertainty about future shocks to endogenous variables (e.g shocks to consumption and
productivity); uncertainty about assumptions concerning exogenous variables (e.g
assumptions about oil prices); uncertainty about model parameters (e.g marginal propensity
to consume); uncertainty about data (e.g revisions of GDP); and uncertainty about the model
structure and specification.
Because of these uncertainties, it becomes extremely difficult to assess the balance of the
various influences on the central forecast. Mervyn King, Governor of the Bank of England,
has therefore argued that we should not focus too much on the central forecast: "The
Monetary Policy Committee has always stressed that a projection is a probability distribution
for possible outcomes and not a single path for either growth or inflation".(Mervn King, Bank
of England, 2009)
Since their impact depends on the variable in question and the forecast horizon under
scrutiny, to actually prioritise or rank the source of forecast uncertainty is a difficult task,.
However, in any given model, the degree of uncertainty related to future shocks and the
assumed trend in the exogenous variables generally pose the greatest threat to aggregated
forecast uncertainty, rather than the uncertainty related to the estimated parameters and
data. But challenges also relate to the structural specification of the models used by central
banks as it is difficult to incorporate everything that really matters in a simplified econometric
framework of the real world.
For example, the traditional models were not able to capture the current crisis. David
Blanchflower of the Bank of England recently commented on the use of misspecified models
or models that fail to take crucial financial issues into consideration: "The economic models
that provided the rationale for the inflation targeting approach do not describe well the
features of the global economy that led to the current crisis; the build up of global
imbalances, perceptions of risk in the economy and stresses within the financial sector."
(David Blanchflower, Bank of England, 2009) As these factors are extremely difficult to
incorporate into our models, building models that capture these issues will be a challenge to
model builders.
Apart from specification problems, there is the issue of exogenous assumptions that get fed
in to the model. A forecast generated by even the most perfect model will only be as good as
the assumptions that are used. Very often these exogenous assumptions are notoriously
difficult to predict. For example, in 2007 and 2008 when the international oil prices were
increasing, we were continuously surprised on the upside by oil price developments. We
were also caught by surprise by the degree to which oil prices declined in the second half of
2008. In the forecasting process our modelling team spends a lot of time analysing the
relevant data and forecasts of other institutions to come up with well-informed assumptions.
But there is no guarantee that these assumptions will be correct or that they will remain
unchanged by the time of the next meeting.
By way of illustration, at the April MPC meeting, the assumptions incorporated into the model
included an average contractual oil price of US$50 per barrel in 2009 and US$55 in 2010.
(The contractual prices are lower than the spot prices). However in August 2008, the oil price
assumptions for the same two years were US$115 per barrel and US$107 per barrel
respectively. Other assumptions in the previous meeting included: International commodity
prices are expected to decline on average by 15 per cent this year and to remain unchanged
next year; international wholesale prices are expected to decline by 31⁄4 per cent this year
before increasing by 2 per cent in 2010; while growth in South Africa's trading partners is
expected to contract by 2 per cent in 2009 and expand by 11⁄2 per cent next year. The real
effective exchange is expected to depreciate by 41⁄4 per cent in 2009 and to remain
unchanged in 2010. Domestic assumptions include a 4 per cent increase in final
consumption expenditure by general government in the next 2 years; administered price
inflation of 2 per cent in 2009 and 93⁄4 per cent in 2010; and an increase in import crude oil
volumes of 5 per cent in 2009 and unchanged in 2010.
3. The monetary policy transmission mechanism
All central bank models strive to replicate the most important channels of the monetary policy
transmission mechanism. In particular this includes the interest rate channel and the
exchange rate channel in particular. The exchange rate is possibly one the most difficult
variables to estimate in the model and usually includes some sort of interest rate parity
measure which allows for the domestic exchange rate to appreciate if the interest rate
differential moves in its favour. However, does this relationship necessarily hold at times of
global financial market uncertainty? We have seen in these circumstances investors and
international banks feel the need to limit their risk exposure by repatriating their funds to
"safe-haven" instruments such as USA bonds in particular. Our models are unable to predict
reliably the exchange rate during such periods where we have extremely volatile and
unpredictable capital movements.
The other critical transmission channel is the interest rate channel. Most models generally
assume that there is no obstruction to the interest rate pass-through to the rest of the
economy. However, at the peak of the financial market crisis towards the latter part of last
year, commercial banks started to raise their credit lending standards and criteria. The
quarterly Senior Loan Officer survey of the Federal Reserve Board bears testimony to the
fact that elevated loan spreads and increased deposit requirements have been self-imposed
by the banks to reduce their asset risk in an effort to protect their balance sheets. Although
this is probably perfectly rational behaviour by prudent banks struggling to value the extent of
their loan exposure, it has the unfortunate effect of reducing the effectiveness of monetary
policy initiatives taken by central banks to stimulate the economy. In fact, in most advanced
economies, central bank interest rate levels are currently at their lowest levels in decades,
but this does not necessarily imply that this intended benefit is passed on directly through to
the investor and consumer.
The behaviour of commercial banks is quite understandable, given the nature and origins of
the current economic situation. However, it also underlines the procyclical nature of their
actions: banks are more keen to offer credit when times are good, but become somewhat
reluctant to advance credit facilities during times of uncertainty and economic slowdown. This
behaviour of commercial banks is not unique to the USA. The BER/ Ernst & Young Financial
Services Index has also found evidence that domestic banks also have raised their lending
standards and criteria. It also appears that domestic banks are charging higher spreads
relative to prime than was previously the case.
The above illustrates that we should not rely too heavily on the results of a model to
guarantee our policy success, particularly during times of heightened uncertainty. No model
can be expected to replicate all these factors in a consistent time-invariant framework,
especially since the behavioural patterns of economic agents tend to change so radically
from time to time.
4. Conclusion
Despite all the problems with the use of models and the challenges related to forecasting in
an uncertain environment, models, irrespective of how they are structured, remain integral to
the policy decision taken and we will therefore continue to use them. The models themselves
have become increasingly sophisticated. But this does not guarantee the success of
monetary policy formulation and implementation especially, in an uncertain future. The
challenges we are faced with have certainly escalated in recent times. However, with the
new challenges we also have new opportunities to get a greater understanding of the
dynamic and ever-changing economy we need to deal with.
Thank you very much.
References
Blanchflower, D. 2009. "Macroeconomic policy responses in the UK?", open lecture by David
Blanchflower an external member of the Bank of England Monetary Policy Committee at the
University of Nottingham, published by the globalisation and economic policy centre,
University of Nottingham, Thursday 29th January, 2009. www.dartmouth.edu/~blnchflr.
Ernst & Young, 2009. "The Financial Services Index : 1st Quarter 2009", the financial
services report for the first quarter of 2009, compiled by George Kershoff (BER) and Graham
Thompson (E&Y), the survey was conducted between 11 February and 17 March and the
results processed on 18 March 2009. The number of responses processed was: retail banks
(21), investment banks (17), investment managers (63) and life insurers (17), April 2009.
Federal Reserve Board, 2008. "Senior Loan Officer Opinion Survey on Bank Lending
Practices", survey on the state of the USA banking sector provided by the Federal Reserve
Board, published January 2009.
http://www.federalreserve.gov/boarddocs/snloansurvey/200902/
King, M. 2009. Opening Remarks by the Governor, Inflation Report Press Conference, Bank
of England, Wednesday 13 May 2009.