Are Technology Shocks Responsible for Business Cycles? In a Word, No.
In their writings, Finn Kydland and Edward C. Prescott (K-P), the 2004 Nobel laureates in economics, had hypothesized that a major cause behind boom-bust cycles is technology shocks. In order to assess the importance of this claim, which they labeled the theory of real business cycles, K-P employed the Solow growth model (after 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–a)*Na,
where Y is real output, A is a technology factor, K is the capital stock, and N is the number of workers employed. The a is a parameter. Mainstream economists hypothesize that in the real world there are relationships between various economic variables. These relations could be depicted via constants labeled parameters.
For instance, the relation between personal consumption expenditure and income after tax can be hypothesized as:
Personal consumption = α*income after tax, with α being a parameter.
Thus, if α is 0.8, this would imply that for an income after tax of $100, personal consumption is $80.
The parameter α, is ascertained with the help of a statistical method called regression analysis. The statistical method also provides the verification 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 α, K-P introduced a method which they labeled calibration. What is this all about? The K-P framework utilizes various studies, expert opinion and data analysis to form a view on the numerical magnitude of a parameter. For instance, using the historical data of wages and income K-P have established that the parameter a in the Cobb-Douglas production function is around 0.64.
By incorporating the information on a with the information on real gross domestic product, the stock of capital and the number of workers employed one, can now extract the numerical values for the technology factor A. Once the technology factor A is extracted, it can be employed to assess the effect it has on fluctuations of various key economic data, so it is held. In their research K-P have demonstrated that a technology-induced shock can explain 70 percent of fluctuations in the postwar US data.
The introduction of calibration supposedly provides an answer to the Robert Lucas (1995 Nobel laureate) critique that questioned the e
Article from Mises Wire