Simpson (2014) on Methodological Objections to the Real Business Cycle Theory (Post 1 of 2)

Real business cycle (RBC) theories are nonmonetary explanations of the business cycle. Supporters of RBC theory claim that business cycles arise due to changes in real factors, instead of monetary factors, in the economy. The focus is on alleged causes of the business cycle that emanate from places other than changes in the supply of money and spending. Further, such cycle theory assumes markets are always in equilibrium (i.e., they always clear, even during recessions and depressions).

Probably the most popular version of RBC theory claims that changes in the level of technology affect the economy such that it causes fluctuations in output and employment (i.e., a business cycle). The claim is that a new invention will increase productivity and bring on an expansion in the economy as the use of this invention becomes widespread. Likewise, technological regression will cause a decrease in overall production in the economy, thus creating a contraction. . . .

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Let me start with a criticism pertaining not to the content of RBC theory but to the methodology of RBC theorists. RBC theorists often simply attempt to mimic the movement of variables during business cycles, such as unemployment and output, using mathematical equations.  They believe that this somehow makes their “theory” valid. However, simply being able to mimic a phenomenon does not provide an explanation for why that phenomenon occurs. To explain a phenomenon one must be able to show logically what factors are causing that phenomenon to occur.

One may be able to mimic changes in output, unemployment, interest rates, the money supply, and so on and one may even be able to obtain the correct relative changes in these variables; however, unless one can show why these variables are changing or why a change in one variable causes a change in another, one does not have an explanation for the movements. In fact, one does not have a theory at all for why the phenomenon occurs. One merely has an intellectually empty imitation of variables. . . . 

In addition, curve fitting data, or what contemporary, mainstream economists might call “calibrating” a “model,” does not provide an explanation of why the variables in the “model” change. It does not identify the causal factors involved. One needs a logical explanation grounded in the nature of the phenomenon and entities being studied to understand why variables move as they do.

—Brian P. Simpson, Remedies and Alternative Theories, vol. 2 of Money, Banking, and the Business Cycle (New York: Palgrave Macmillan, 2014), 79, 81.