Vienna Woods Law & Economics

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“Is Economics a Science?” by Theodore A. Gebhard — May 15, 2015

“Is Economics a Science?” by Theodore A. Gebhard

The great 20th Century philosopher of science, Karl Popper, famously defined a scientific question as one that can be framed as a falsifiable hypothesis.  Economics cannot satisfy that criterion.  No matter the mathematical rigor and internal logic of any theoretical proposition in economics, empirically testing it by means of econometrics necessarily requires that the regression equations contain stochastic elements to account for the complexity that characterizes the real world economy.  Specifically, the stochastic component accounts for all of the innumerable unknown and unmeasurable factors that cannot be precisely identified but nonetheless influence the economic variable being studied or forecasted.

What this means is that economists need never concede that a theory is wrong when their predictions fail to materialize.  There is always the ready excuse that the erroneous predictions were the fault of “noise” in the data, i.e., the stochastic component, not the theory itself.  It is hardly surprising then that economic theories almost never die and, even if they lie dormant for a while, find new life whenever proponents see opportunities to resurrect their pet views.  Since the 2008 financial crisis, even Nobel Prize winners can be seen dueling over macroeconomic policy while drawing on theories long thought to be buried.

A further consequence of the inability to falsify an economic theory is that economics orthodoxy is likely to survive indefinitely irrespective of its inability to generate reliable predictions on a consistent basis.  As Thomas Kuhn, another notable 20th Century philosopher of science, observed, scientific orthodoxy periodically undergoes revolutionary change whenever a critical mass of real world phenomena can no longer be explained by that orthodoxy.  The old orthodoxy must give way, and a new orthodoxy emerges.  Physics, for example, has undergone several such periodic revolutions.

It is clear, however, that, because economists never have to admit error in their pet theories, economics is not subject to a Kuhnian revolution.  Although there is much reason to believe that such a revolution is well overdue in economics, graduate student training in core neoclassical theory persists and is likely to persist for the foreseeable future, notwithstanding its failure to predict the events of 2008.  There are simply too few internal pressures to change the established paradigm.

All of this is of little consequence if mainstream economists simply talk to one another or publish their econometric estimates in academic journals merely as a means to obtain promotion and tenure.  The problem, however, is that the cachet of a Nobel Prize in Economic Science and the illusion of scientific method permit practitioners to market their pet ideological values as the product of science and to insert themselves into policy-making as expert advisors.  Significantly in this regard, econometric modeling is no longer chiefly confined to generating macroeconomic forecasts.  Increasingly, econometric forecasts are used as inputs into microeconomic policy-making affecting specific markets or groups and even are introduced as evidence in courtrooms where specific individual litigants have much at stake.  However, most policy-makers — let alone judges, lawyers, and other lay consumers of those forecasts — are not well-equipped to evaluate their reliability or to assign appropriate weight to them.  This situation creates the risk that value-laden theories and unreliable econometric predictions play a larger role in microeconomic policy-making, just as in macroeconomic policy-making, than can be justified by purported “scientific” foundation.

To be sure, economic theories can be immensely valuable in focusing one’s thinking about the economic world.  As Friedrich Hayek taught us, however, although good economics can say a lot about tendencies among economic variables (an important achievement), economics cannot do much more.  As such, the naive pursuit of precision by means of econometric modeling —  especially as applied to public policy — is fraught with danger and can only deepen well-deserved public skepticism about economists and economics.

Theodore A. Gebhard is a law & economics consultant.  He advises attorneys on the effective use and rebuttal of economic and econometric evidence in advocacy proceedings.  He is a former Justice Department economist, Federal Trade Commission attorney, private practitioner, and economics professor.  He holds an economics Ph.D. as well as a J.D.  Nothing in this article is purported to be legal advice.  You can contact the author via email at theodore.gebhard@aol.com.

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