FORECASTING THE
MACROECONOMY
Forecasting economic time series involves constructing a model,
assuming values that any exogenous variables will take in the
future, and then running through the model to see what happens to
the endogenous variables. There are several types of model:
1. Structural models
These take a theoretical model of the economy (such as the AS/AD
model) and estimate the parameters (ie the constants) statistically.
This involves choosing the parameter values that fit the data most
closely (cf a line through a scatter plot), using a variant of
regression analysis. Some structural models impose the assumption
of rational expectations; others do not.
Advantage/disadvantage: rooted in economic theory.
2. VAR models
Vector AutoRegressions examine how each variable in an
economy depends on lagged values of every other variable and of
itself – again using regression analysis. Simple VARs have no
exogenous variables; more sophisticated ones do.
An advantage/disadvantage is that VAR models are atheoretical. A
disadvantage is that they can suffer from overparameterisation.
Structural models and VAR models assume linear dynamics (ie the
gap between actual and equilibrium values of a variable is closed
at a constant rate over time).
3. Neural networks
Based on the structure of, and learning processes in the brain.
Often used in pattern recognition (eg how computers read
handwriting), now also used in forecasting. Information enters
each neurode (black dot in diagram) from inputs or from other
neurodes. A weighted average of this information is taken (weights
estimated statistically), and then ‘squashed’ (ie adjusted in a
nonlinear way). The output is therefore an aggregate of many
highly nonlinear processes.
INPUT
HIDDEN
OUTPUT
LAYER
LAYER
LAYER
Figure 2: A single hidden layer feedforward neural network
Squasher may be y = 1/(1+e-x).
Advantage: neural networks can approximate arbitrarily closely
any nonlinear process, even chaos.
Disadvantages: need a lot of data; danger of overparameterisation;
no basis in theory.
The future: a mix of approaches.
You can get an online interactive version of the Treasury model,
and much other information about macroeconomic forecasting,
from http://www.bized.ac.uk/virtual/economy/
You can get a compendium of current forecasts for the UK from
http://www.hm-treasury.gov.uk/pub/html/forc/comp/main.html
Latest Treasury model forecasts are:
GDP growth (per cent)
RPIX inflation (per cent, Q4)
1997
3½
42¾
1998 1999
2¾
1 to 1½
2½
2½
Forecast
2000
2¼ to 2¾
2½
2001
2¾ to 3¼
2½
An important use of forecasting is to predict the effects of
alternative policy measures – the above forecasts made a particular
set of assumptions, but what happens if those assumptions are
changed?
Following results are from the Treasury model. ‘Before’ refers to
base forecasts, ‘after’ refers to forecasts following a reform
(reducing the basic rate of income tax to 20% from 1999 on):
Economic forecasts may be subject to the Lucas critique – if a
discrete policy change alters the parameters of the model (eg via
expectations), the model cannot forecast well. eg the outcome of
the early 1980s Thatcher experiment (where the government
sought directly to reduce expectations of inflation by adopting an
aggressive counter-inflation policy) could not be forecast.
Information needed:
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national income
consumer expenditure
investment
government spending and tax income
prices
unemployment
trade
Economic forecasting is difficult, imprecise, and subjective; it is
potentially useful to business and policymakers, and it is fun.