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6.11 Calibrating the Model

It was Kydland and Prescott (1982) who first demonstrated that a general

equilibrium real business cycle model, driven by exogenous technological

shocks, was capable of generating time series data that possessed the statistical

properties of US business cycles over the period 1950–79. However,

real business cycle theorists have not generally attempted to provide models

capable of conventional econometric testing but have instead tended to

focus on providing numerical examples of a more general theory of

fluctuations. In order to examine the quantitative implications of their modThe

els, real business cycle theorists have developed a method known as ‘calibration’

or ‘computational experiments’. Cooley (1997) defines calibration

as ‘a strategy for finding numerical values for the parameters of artificial

economies’ and involves a ‘symbiotic relationship between theory and measurement’.

The calibration strategy consists of the following steps (see

Kydland and Prescott, 1982, 1991, 1996; Plosser, 1989; Backhouse, 1997b;

Abel and Bernanke, 2001):

1. Pose a question relating to a specific issue of concern, for example an

important policy issue such as ‘What is the quantitative nature of

fluctuations caused by technology shocks?’

2. Use a ‘well-tested’ theory, where ‘theory’ is interpreted as a specific set

of instructions about how to build the imitation economy.

3. Construct a model economy and select functional forms. Kydland and

Prescott (1982) utilize the basic stochastic neoclassical growth model as

the cornerstone of their model.

4. Provide specific algebraic forms of the functions used to represent production

and consumption decisions. For example, a specific Cobb–Douglas

production function is used by Plosser (1989).

5. Calibrate the model economy using data from pre-existing microeconomic

studies and knowledge of the ‘stylized facts’. Where no information

exists select values for parameters so that the model is capable of mimicking

the real-world behaviour of variables.

6. The calibration exercise then involves simulating the effect of subjecting

the model to a series of random technology shocks using a computer.

7. The impact that these shocks have on the key macroeconomic variables

is then traced out so that the results can be compared with the actual

behaviour of the main macroeconomic time series.

8. Run the experiment and compare the equilibrium path of the model

economy with the behaviour of the actual economy. Use these types of

simulations to answer questions relating to the important issues initially

identified under (1).

In their seminal 1982 paper Kydland and Prescott use the neoclassical growth

model and follow the calibration/simulation procedure to see if the model can

explain aggregate fluctuations when the model economy is subject to technology

shocks. As Prescott (1986) recalls, ‘the finding that when uncertainty in

the rate of technological change is incorporated into the growth model it

displays business cycle phenomena was both dramatic and unanticipated’.

The simulations carried out by Kydland, Prescott and Plosser produced some

impressive results in that their models are able to mimic an actual economy

with respect to some important time series data. These simulations indicate

that a competitive economy hit by repeated technology shocks can exhibit the

kind of fluctuations that are actually observed.

On the negative side, one of the problems with calibration is that it currently

does not provide a method that allows one to judge between the

performance of real and other (for example Keynesian) business cycle models.

As Hoover (1995b) notes, ‘the calibration methodology, to date, lacks

any discipline as stern as that imposed by econometric methods … Above all,

it is not clear on what standards competing, but contradictory, models are to

be compared and adjudicated.’ Nevertheless calibration has provided an important

new contribution to the methodology of empirical macroeconomic

research. While initially the calibration methodology was focused on business

cycle research, more recently calibrated models have been used to

investigate issues in public finance, economic growth, industry, firm and

plant dynamics and questions related to the choice of economic policy (Cooley,

1997). For more detailed discussions and critiques of the calibration methodology

see Kydland and Prescott (1991, 1996); Summers (1991a); Quah (1995);

Hoover (1995b); Wickens (1995); Hansen and Heckman (1996); Sims (1996);

Cooley (1997); Hartley et al. (1998).