Download Business Cycles : Real Business Cycle Approach

Copyright Protected © Dr Cillian Ryan 2001
Copyright Protected © Dr Cillian Ryan
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Draft: Chapter for
'Encyclopaedia of Economics' Snowden, B. & H. Vane Editors Elgar 2002
Business Cycles : Real Business Cycle Approach
For many years economists have struggled to understand economic fluctuations in the
hope that this would enable them to eliminate the unpalatable effects of recessions and
booms such as unemployment or house price inflation. Under this view of the macroeconomy there existed a desirable level of full- (or natural-level-) employment output
which could be attained save for the vagaries of demand fluctuations. These fluctuations,
according to Keynes, depended on the ‘animal spirits’ of consumers and investors.
Alternatively, according to monetarist, they depended on expectation errors or rigidities
caused by monetary fluctuations. Thus, it was believed that governments, by undertaking
economic research and judicious use of fiscal or monetary policy, could control the worst
excesses of the business cycle.
One of the difficulties with the models used by policy makers to understand the
effect of their policy actions was that the parameters (such as the marginal propensity to
consume) employed in traditional models might change as government economic policy
changed. If this were the case then the policy predictions based on these models would be
useless. This was the so-called Lucas Critique. Lucas instead suggested that models ought
to be based on primary elements of microeconomic behaviour such as utility and
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production functions. In attempting to formulate such a model Kydland and Prescott
(1984) founded what we now call Real Business Cycle Theory.
Essentially the model they built led them to the conclusion, surprising at the time,
that most fluctuations were caused not by demand variations due to changing
expectations or ‘animal spirits’ but rather by agents reactions to shocks to the production
function or in other words ‘real’ shocks, hence the title Real Business Cycle Theory.
Their ‘discovery’ came about due to the methods they used to build and test their
model. Since the model was not based on reduced form equations (such as the IS or LM
curves we usually estimate) it could not be tested econometrically and instead they used a
technique known as computer simulation. Computer Simulation is sometimes
derogatorily referred to as doing econometrics with one observation! In practice, the
original research took data from a particular base year and using parameters from
previous econometric studies for the consumption, production and other functions fitted
(or calibrated) the model to the base year data. The inter-temporal utility and production
functions were simple Cobb-Douglas type functions, with production being subject to
shocks. These shocks were derived by first calculating the level of economic growth that
could be attributed to changes in labour and capital in any period. The difference
between the predicted change and the actual change (Solow residuals) was attributed to
random economic shocks. The model, which has been calibrated to the base year, is then
run through the computer with a different shock for each year and the resulting choices of
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consumption, employment, production and investment are noted and compared with the
actual data for the economy.
Kydland & Prescott found that when the computer simulation of their model was
compared with actual US data that the fluctuations in the model economy looked very
like those in the real data. Thus, they concluded, the new model, where fluctuations in
economic variables only arise as a result of shocks to the production function, provided a
good fit of the ‘Stylised Facts’ (see chapter???). This was seen as a dramatic result at that
time, since, as was noted above, it was believed up to that point that production (or
supply-side) shocks only accounted for a very small percentage of the real fluctuations,
and that either demand or monetary shocks were the more important determinants. This
new theory called the traditional view into question.
The policy implications of this were enormous. Instead of the business cycle and
the associated fluctuations in employment, consumption and investment being caused by
some demand-side market failure which the government needed to eliminate, this
research suggested that the fluctuations we observe are optimal responses on the part of
individual consumers, producers and investors to real economic shocks (such as weather,
natural events, strikes, political upheaval and new inventions etc.). It follows that any
attempt on the part of government to smooth out these variations must cause consumer to
deviate from their freely-chosen, optimal actions and hence make them worse off.
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To put it another way, the Keynesian ideal of striving to attain some target level
of full-employment equilibrium is misplaced. What is actually happening is that
equilibrium output is constantly moving about over time, in response to ‘real’ shocks.
Furthermore, proponents of the Real Business Cycle prefer to think of these shocks not as
some predetermined cyclical process, but as random shocks along the long-run growth
path of the economy
The result also had another profound implication, and along with other research
questioning the efficacy of short-run interventionist policy, has had a significant
influence on many modern western governments. The theory suggested that the object of
fiscal policy was not short-term counter-cyclical intervention, but rather to design tax and
expenditure policies particularly as regards the provision of public goods and education
which maximize the growth rate of the economy. Furthermore, monetary policy has no
role in this framework as its distortionary effects on prices and expectations can only
interfere with optimal consumer choices. Sometimes this policy prescription is referred to
as supply-side economics as it is concerned with devising policies that maximize the
supply of output in the long run. In summary, Real Business Cycle theory suggests that
governments ought to be concerned with achieving the best long-run trend of GNP rather
than being concerned with the fluctuations around it. Needless to say, this view provoked
considerable controversy on a variety of fronts, both because its interpretation of the
process generating the stylised facts we observe was so radically different from our
previous understanding, and because it was seen to diminish the role of government and
was thus seen as a right –wing agenda setting theory (though defenders would argue that
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the emphasis on designing optimal fiscal policies rather than on discretionary monetary
policy is strongly in the Keynesian tradition). The theory was thus attacked on a number
of levels.
Economists first tackled the claim that the model fitted the data well. It was
suggested that the Cobb-Douglas forms of the utility and production functions employed
by researchers were too convenient, that their choice of parameters for these functions
based on past empirical work was arbitrary, and unlike econometric studies, the claim
that the results of the simulated model were ‘close’ to the real data was purely subjective
and unverifiable.
Subsequent refinements of the simulation technique (which had been employed in
international trade and tax policy studies for decades) helped to address some of these
problems. An advanced econometric technique, known as the Generalized Method of
Moments, allows the data to tell the researcher what the appropriate functional form and
parameters of the functions should be and removes some of the subjective choices a
researcher must make when setting up the model. Similarly, sensitivity tests can be
conducted to see just how much the results of the model vary as the parameters of the
functions vary. Finally, it was noted that the stylised facts we are measuring the model
against are not rigid observations but rather they are derived by sampling real economic
data, and we can measure the sampling variability. Thus it is possible to ask if a given set
of simulated observations is likely to have come from the underlying population given
the real data at our disposal. Despite these refinements to the simulation method, there are
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many economists who remain sceptical about this type of approach, advocating instead
the refinement and improvement of econometrics-based macroeconomic modelling.
The second key development was to marry some of the improvements in the
methodology, as outlined above, with refinements to the model to tackle areas where the
simulation results did not perform well in matching the real data. The key deficiency was
the performance of the model with respect to the labour market. Firstly the original
simulated model could only generate about half the fluctuations actually observed in the
employment market, and secondly the model failed the famous ‘Dunlop-Tarshis’ test.
This is the stylised fact, established as long ago as the 1930s, that there was a near zero
correlation between hours worked and real wages over the cycle.
One line of research tried to improve the models ability to match labour market
variations by allowing for, amongst others, such phenomenon as the effect for a
minimum 40 hour week on the employment/unemployment /over-time/rest decision and
the effect of house-hold opportunities (doing your own housework/maintenance/decorating versus working and paying someone else). These sorts of
refinements all succeeded in substantially improving the performance of the model.
The second line of research tackled the ‘Dunlop-Tarshis’ problem that there
should not be any relationship between wages and hours. The real business cycle model
implies a positive correlation because the demand curve for labour moves up and down
the labour-supply curve as shocks hit the production function. By contrast the older
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Keynesian/Monetarist approach saw the labour supply curve as moving up and down the
labour demand curve (for example, due to employees mis-perceptions of the real wage or
sticky wage contracts) and thus predicts a negative correlation. Thus what was necessary
was a model that would generate movements in both the labour demand and supply
curves. This was addressed by, for example, allowing for the influence of cyclical
government spending on labour supply decisions and by extending the model to
incorporate Keynesian-type labour market failures.
More recently, research in this field has concentrated in trying to extend the
model to explain nominal and monetary stylised facts rather than the real issues. In these
models either money or a banking sector is incorporated into the model and then the
influence of either real production or nominal money supply side shocks are considered.
To date these models have enjoyed mixed success in explaining the monetary stylised
facts and much work remains in this area.
Bibliography
Christiano, L. J. and M. Eichenbaum (1992), ‘Currency, Real-Business Cycle Theories
and Aggregate Labor Market Fluctuations’, American Economic Review, 82,
June .
Danthine, J.P. and J.B. Donaldson (1990), Efficiency Wages and Business Cycle Puzzle’,
European Economic Review, 34, November.
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Kydland, F. E. and E. C. Prescott (1982), ‘Time to build and Aggregate Fluctuations’,
Econometrica, 50, November.
Long, J. B, Jr, and C. I. Plosser (1983) ‘Real Business Cycles’, Journal of Political
Economy, 91, February.
Ryan, C and A.W. Mullineux (1997), ‘The Ups and Downs of Modern Business Cycle
Theory, in Reflections on the Development of Modern Macroeconomics in B.
Snowden B and H.Vane (eds), Aldershot : Edward Elgar,