By Dr Frank Shostak
Some economists such as Finn Kydland and Edward C. Prescott (KP), the 2004 Nobel Laureates in economics, are of the view that a major cause behind economic boom-bust cycles is technology shocks. In order to validate this view, KP employed the Solow growth model (Robert Solow the 1987 Nobel Laureate) which in turn is based on the Cobb-Douglas production function of the following type,
Y=A*K(1-α)*Nα
Where Y is real output, A is a technology factor, K is the capital stock and N the number of workers employed. The α is a parameter.
By popular thinking, relationships between various economic variables could be depicted via constants labelled as parameters. For instance, the relation between personal consumption expenditure and income after tax could be described as,
Personal consumption = alpha* Income after tax
With alpha being a parameter. Thus, if alpha is 0.8 then for the income after tax of $100 this would imply that personal consumption is $80.
The parameter alpha is ascertained by means of a statistical method. The statistical method also provides the verification as to whether the obtained number is a valid estimate of the true parameter in the real world.
Instead of employing conventional statistical methods for the estimation of the parameter alpha, KP introduced a method which they labelled calibration. What is this all about?
The KP framework utilises various studies, expert opinion and data analysis to form a view on the parameters. For instance, using historical data of wages and income, KP have established that the parameter α in the Cobb-Douglas production function is around 0.64. By incorporating the information on α with the information on real GDP, the stock of capital and the number of workers employed, one could extract the technology factor A. Once the technology factor A is extracted, it could be employed to assess the effect it has on the fluctuations of the real output Y.
In their research KP have concluded that a technology-induced shock can explain 70 percent of fluctuations in the post-war US output.
The introduction of calibration supposedly addresses Robert Lucas’s (1995 Nobel Laureate) critique that questioned the reliance on fixed parameters models to assess the implications of government policies on the economy.
According to Lucas a change in the government policy is going to alter the parameters in the real world. Hence, a model, which employs unchanged parameters, is going to produce misleading results. (A change in government policy alters the behaviour of participants in the economy. The fixed parameters model ignores that this is so). On this, Robert Lucas is in agreement with Ludwig von Mises. According to Mises, “There are, in the field of economics, no constant relations.”
KP boom-bust model
What is the mechanism in the KP framework that converts the technology shock into the boom-bust cycles? A positive technology shock according to KP implies that with a given supply of capital and labor, the economy could generate more output.
Higher productivity leads to higher wages. This in turn raises workers willingness to work more and reduce their leisure. The higher return on capital gives rise to more capital investment. All this leads to an economic boom and prosperity.
A recession is caused by a negative technology shock, which lowers the return on labour and capital. This in turn causes workers to work fewer hours and to the decline in capital investment. Consequently, this leads to a fall in output i.e. to an economic bust. (A negative technology shock refers to an event that reduces the overall productive capacity of an economy).
Note again, that notwithstanding the calibration method, KP still employ a fixed parameters model to establish the importance of the technology shock in setting the boom-bust economic cycles. Again, the calibration method is about establishing parameters not by means of conventional statistical methods but by examining the historical data and expert opinion.
Now, to suggest that a technological shock is not going to alter the parameter α in the Cobb Douglas production function is to hold that we are dealing with machines and not human beings.
This in turn implies that the KP conclusion that a technology-induced shock could explain 70 percent of fluctuations in the post-war US data is questionable. (Conceptually even if one were to accept that the parameter α , which is obtained by means of the calibration, is stable over time this does not address the Lucas’s critique that a change in government policies and other shocks such as the technology shocks, are going to affect the human conduct and hence the parameter α).
Economic boom is not about economic prosperity
Contrary to KP, an economic boom is not about economic prosperity and wealth generation, but about the diversion of resources from the wealth generating activities towards activities that consume and do not produce wealth i.e. undermine the wealth generating process. Or we could say that an economic boom gives rise to activities that are engaged in consumption, which is unbacked by the previous production of wealth i.e. non-productive consumption.
If for some reason the diversion of resources is arrested, various non-productive activities that sprang up as a result of this diversion come under pressure i.e. an economic bust emerges.
Therefore, what is required in order to establish how boom-bust cycles are formed is to identify the mechanism that gives rise to the persistent diversion of resources from wealth generators to non-wealth generators.
Central Bank policies the key factor behind boom-bust cycles
In a free, unhampered market, we could envisage that the economy would be subject to various shocks but it is difficult to envisage a phenomenon of recurrent boom-bust cycles.
According to Rothbard,
Before the Industrial Revolution in approximately the late 18th century, there were no regularly recurring booms and depressions. There would be a sudden economic crisis whenever some king made war or confiscated the property of his subjects; but there was no sign of the peculiarly modern phenomena of general and fairly regular swings in business fortunes, of expansions and contractions.
The boom-bust cycle phenomenon is somehow linked to the modern world. However, what is the link? Careful examination would reveal that the link is in fact the modern banking system, which is coordinated by the central bank. The source of the boom-bust cycles turns out to be the alleged “protector” of the economy — the central bank itself.
Whenever the central bank eases its monetary stance, it sets the diversion of wealth from wealth producers to the holders of the newly generated money out of “thin air”. The emergence of activities on the back of the central bank’s easy monetary stance gives rise to an economic boom.
The easy monetary stance results in economic impoverishment of wealth producers. Once the central bank tightens its monetary stance, the diversion of resources towards activities that emerged on the back of the central bank’s previous loose monetary stance is stopped. This in turn leads to their demise, or what is called to an economic bust.
The heart therefore of what business cycles are is the process of the diversion of resources from wealth generating activities towards non-wealth generating activities. This process is set by the monetary policies of the central bank.
Change in technology has nothing to do with boom-bust cycles
Change in technology can be important to the process of wealth generation. Better technology could strengthen the process of wealth generation. Conversely, a negative technology shock is going to undermine the process of wealth generation. All this however has nothing to do with the boom-bust cycles. Again, the heart of business cycles is the process of the diversion of resources from wealth generators to non-wealth generators. This process is set in motion by the monetary policies of the central bank.
What KP have established is not a novel way for understanding the phenomenon of the business cycle but a different method of curve fitting. By means of calibration, various imaginary models could now be introduced. What we have here is an emphasis on developing a method of curve fitting rather than trying to identify the essence of what gives rise to the boom-bust cycles.
Conclusion
Changes in technology could be important to the process of wealth generation. This however, has nothing to do with the phenomenon of the boom-bust cycles. Various mathematical models that have supposedly established that changes in technology are the key driving factor of the boom-bust cycles do not address the causes of boom-bust cycles but rather describe fluctuations of the data.
