In Defense of Quantitative Reasoning

The following is a direct quote from Friedrich von Hayek’s 1968 essay “Competition as A Discovery Procedure”:

“I should like to add a few words about the consequences of the disappointment in microeconomic theory caused by fallacious methodological criteria of scientism. The notion that we must formulate our theories so that they can be immediately applied to observable statistical or other measurable quantities seems to me to be a methodological error. It is a false epistemiological principle to adapt the theory to the available information, so that the observed variables appear directly in the theory.” (Hayek, 11-12).

It is indeed tempting to subscribe to Hayek’s opinion that to deserve a title of scientific theory, it must be formed independently and regardless of the facts and empirical data. Hayek makes a valid argument that at times data are tailored to fit the initial hypothesis and questionable, at best quasi-scientific results emerge.
To demand the opposite is admirable yet highly impractical. The entire reason why a hypothesis is formed in the first place is due to suspicion of a certain relationship existing between the observable variables. Such is the nature of analytics as a science itself: human minds perceive patterns and seek verification of their initial assumptions. It calls for a formulation of clear and unambiguous hypotheses. Once the null and the research hypotheses are defined, a scientist designs an experiment. At this stage of research, arguably the most important one, a number of independent variables is considered. An experiment can be designed to simply test the strength of a relationship between a single dependent and a single independent variable. If that is the case, a researcher might not be careful enough and might falsely conclude that the two variables will always act in a manner consistent with the outcomes of the experiment. “We might be able to notice certain regularities in the observed behavior of these variables. Often these regularities apply, but sometimes they do not. Yet using the means of macrotheory, we can never formulate the conditions under which they apply,” writes Hayek (12). I am afraid I disagree that we can literally never formulate those conditions. For if it were so, the field of macroeconomics would cease to exist. The few relationships that are firmly anchored in the minds of macroeconomists exist due to the strong empirical evidence that support those relationships in the first place. Every single one is supported by a verifiable model.
That brings me to another point. When observing a change of a dependent variable that is a function of an independent variable, a coefficient of determination between the two is of utmost importance. For if the “R squared” explains a minor portion of the dependant variable’s variation (like 20 percent), it surely calls for a more complete model. So, a model gets rebuilt and the research continues. As long as a model of a dependant variable captures a significant and sizable proportion of this variable’s variation, it does not deserve to be labeled methodologically flawed. Modern computing grants us power to split atoms with a precision of our forecasting and other econometric models. That was clearly not the case when Hayek wrote his original essay in 1968.
Hayek lived during the time when the Might and speed of modern computers would be a scientist’s wild dream. He lived in a scientific community severely constrained by the lack of any automated computational capabilities. Unable to perform any rigorous quantitative analyses, he chose to abandon all efforts to do so all together, labeling the attempts of all other economists to describe the world numerically as “fallacious methodological criteria of scientism.” Instead, he chose to practice economics in the form of political philosophy, a form that was prevalent for centuries, a form lacking quantitative rigor and precision but abundant with ideological implications.
Hayek claimed that the attempt to quantify the world around us is “a methodological error.” Such claim is severely biased and can be easily contested by one of the Forefathers of all Science, Isaac Newton himself. In his work “Rules for the Study of Natural Philosophy” Newton establishes clear provisions of the Scientific Method. To be termed scientific, a method of inquiry must be based on gathering observable, empirical and measurable evidence subject to specific principles of reasoning. A scientific method must further include the collection of data through observation and experimentation, and the formulation and testing of hypotheses. That is the scholarly method a respectable scientific community follows, not rhetorical demagoguery regarding the political philosophy and the mere rhetoric of the government’s coercive powers.
Last but not least, this post is written by an author practicing a Science of Economics. This is the science concerned with an endless myriad of choices, tradeoffs, and opportunity costs. This is the science describing people’s behavior and their interactions with other individuals. This is the science aiming to accurately and precisely describe people’s welfare and fluctuations thereof. This is a Science and it deserves its quantitative rigor, and we, the growing generation of tomorrow’s scientists, will fight to preserve it.