Rigorous Economics Is a Deductive Science

Modern mainstream economics, led by the neoclassical school, actively embraces econometrics. Econometrics is an inductive, a posteriori branch of economics that seeks to approach economic truth through the process of quantifying and analyzing historical data. It begins from the methodological view that “economics should imitate the methodology of the natural sciences” (methodological monism). Econometrics has become accepted as a highly general method of economic research. In fact, university students spend years learning complex mathematical models and econometric methodologies that are far removed from the real economy. Meanwhile, in-depth “conceptual discussion” of economic issues has long been pushed to the sidelines.

The very idea of trying to arrive at some economic-scientific truth or norm through econometrics is, from the outset, a fatal error. Economics is not, in essence, an inductive discipline. Past data are nothing more than historical records produced by the actions of particular people living at particular times. By themselves, they cannot yield any economic-scientific truth. The Austrian economist Ludwig von Mises harshly criticized econometrics, saying that “as a methodology of economic analysis, econometrics merely expresses past trends in mathematical form and therefore contributes nothing whatsoever to clarifying the essence of economic problems.” 1)

Economics is fundamentally the study of human action. Human action 2) is purposeful action arising from value judgments and a sense of purpose. Human beings act consciously to improve whatever situation they are given in a direction better than the present. Purposefulness is a uniquely human characteristic. To apply the methodology of the natural sciences to economics is to reject this purposefulness. Only by gradually deducing the system of economics from the ultimate axiom that “human beings act purposefully” can one derive rigorous economic-scientific truths. Important questions such as what inequality is, what relationship exists between inflation and interest rates, and whether a fair price truly exists can be answered only in this way. This is precisely what conceptual discussion is.

Econometric analysis not preceded by high-quality conceptual discussion is no more than meaningless number play. Consider, for example, the IMF report published in 2015, Causes and Consequences of Income Inequality: A Global Perspective. The authors claim that “when the income share of the top 20% rises by 1%, real GDP growth falls by 0.08%, and when the income share of the bottom 20% rises by 1%, real GDP growth increases by 0.38%.” They then hastily conclude that “benefits do not trickle down.” This starkly shows how deceptively econometrics can be misused.

First, it is nonsense that the argument rejecting the trickle-down effect uses only two explanatory variables—“income shares by quintile” and “real GDP growth.” Although the trickle-down effect is not even treated as a formal theory in economics, it is still, in its own way, a complex and profound proposition. It is generally defined as “the effect whereby an increase in the income of high-income groups leads to expanded consumption and investment, ultimately increasing the income of low-income groups as well.” Therefore, in order to reject the trickle-down effect econometrically, the analysis should at the very least have considered all the variables explicitly stated in the definition, including consumption and investment. Even if all were considered, only a very fragmentary piece of the truth would be visible. Moreover, contrary to the authors’ claim, the possibility that a slowdown in economic growth led to worsening income inequality—reverse causality—was also excluded. Even the IMF, supposedly a gathering place for some of economics’ leading scholars, produces this kind of shoddy research. In this study, the numbers merely served to prop up the researchers’ unverified beliefs.

Although Mises and Frank Shostak denounced econometrics as “childish play,” econometrics itself is not entirely useless. In reality, policymakers and state-run researchers would probably be unable to do much of anything without the immediate help of econometrics. And through the concept of probabilistic causality, the inductive inference of econometrics can provide a broader factual picture than deductive inference. Variables that would seem to have absolutely no relationship in deductive reasoning may show a close relationship in inductive econometric analysis. However, inferring direct causation from the “probabilistic causality” revealed by econometric analysis is entirely the task of deductive science. Quantitative methodology should clearly remain an auxiliary tool.

1) Mises, Ludwig von. (1962). The Ultimate Foundation of Economic Science: An Essay on Method. Mises Institute, 63.

2) Philosophically, action and behavior are distinguished. Behavior is bodily movement not accompanied by human purposiveness, such as sneezing. Therefore, human behavior is treated not by praxeology but by natural sciences such as physiology.

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Original title: 엄밀한 경제학은 연역과학이다

Author: Beom-su Cho

Date: 2019-11-26

Source: https://www.cfe.org/bbs/bbsDetail.php?cid=free_opinion&pn=17&idx=22087