Modern Economics is Voodoo: Questioning the Value of Value-Free Thinking

Lydia Alpural-Sullivan

The mathematization of economics, and the resultant rise of neoclassical dominance, is not a benign movement toward objectivization as it pretends to be. Neoclassical theory as the dominant praxis in modern economics offers a clear ideological and practical advantage to capitalists because of its epistemological and historical context. Enabled by an incorrect trend towards characterizing economics as a value-free, fully empirical science comparable to physics or astronomy, the tendency to conceptualize economics as observed rather than created has become practically axiomatic, despite obvious problems. Economics is in fact – being fundamentally the study of human behavior -- no more value-free than psychology or philosophy. Because outcomes of mathematizing economics in the context of a developing global capitalist economy endows certain social classes with benefits in the form of information asymmetry, the push toward mathematization should instead be considered an historically and socially derived teleological progression.

1862 was the tail end of the era now considered the scientific revolution, a period characterized by the formalization and institutionalization of human knowledge beginning at the close of the renaissance. That year, William S. Jevons published A General Mathematical Theory of Political Economy, in which he criticized the study of Economics as being lamentably poor in its utilization of empirical methods that had been a core development in other sciences, such as physics and chemistry. According to Jevons: “Economy, indeed, being concerned with quantities, has always of necessity been mathematical in its subject… the easy comprehension of its quantitative laws has been prevented by a neglect of those powerful methods of expression which have been applied to most other sciences with so much success”. (536) Jevons’ work, along with that of his contemporaries Léon Walras and Karl Menger, are now considered seminal to the marginal revolution. In their wake, economics would become increasingly quantitative, redefining the conception of the individual and their relation to the market in the process.

The fashioning of economics into neoclassical theory relies on several base assumptions. These form the parts of a theoretical “machine”, through which sums of human preferences and behavior can be processed to produce tidy outcomes. Epistemologically, neoclassical theory takes after a structuralist approach in mathematics, which supposes axiomatic structures or functions, into which otherwise meaningless variables can be placed to form a meaningful whole (Shapiro, 536). These structures are not thought to be cultivated, but rather discovered through empirical observation. In other words, this theory supposes economics to have a definition, rather than be actively defined. Though this is the dominant approach in both modern math and economics, is by no means the only conclusion that meta-analyses of

mathematical theory have reached; other approaches recognize that no body of knowledge can escape the limitations of the human mind. Some mathematical philosophies such as social constructivism posit that essentially, there is no way to conceptualize mathematical truth outside the framework of human experience – constructivists believe that math is not so much discovered as curated, as the result of collective human knowledge.

The fundamental problem with abstracting economic phenomenon into ever-more complex mathematical systems is that the very phenomena being described are originated by people, who are then alienated from the processes in question. Ironically, as our quest for “objectivity” pushes the science of economics to be increasingly esoteric and less accessible to the average person, the objectivity of it must necessarily be impaired. The progression works like this: the more specialized knowledge about economics becomes, the fewer people will be able to become experts. Only those with a high degree of expertise will be considered qualified to advise those with less expertise. Acquiring this expertise is closely associated with one’s socio-economic status. Therefore, the vast majority are not offered facts, but rather interpretations by a particular class which are presented as facts.

Constructivists might argue that the limitation of empirical, or observed, science is that the mere act of observation is inherently subjective. For example, devoting effort to empirically observing one thing but not another, regardless of how flawlessly objective the research produced is, is still influenced by human interests. The net outcome of neglecting whatever is not studied must have an effect on the sum of the body of knowledge.

The Marginal revolution took place contemporaneously with another revolution of the 19th century –the industrial revolution. This is not a case of coincidence, but rather of mutual co-development. The mode of production and distribution in industrial capitalism enabled and inspired the conceptions of value, exchange and preference-ordering that characterizes the work of the marginalists. Likewise, marginalism as considered under the greater philosophical category of utilitarianism encouraged and justified the economic behavior surrounding profit acquisition and resultant class relations as the natural, axiomatic outcome of universal mathematical truths. Marginalism as a refinement of utilitarian theory is an intrinsically individualistic approach to interpreting behavior. Utilitarian Jeremy Bentham explicitly states in his Principles of Morals and Legislation: “The community is a fictitious body, composed of the individual persons who are considered as constituting, as it were, its members”. The interest of the community is, he goes on to say, “the sum of the interests of the several members who compose it”. (2)

The advantageousness of the coupling of neoclassical economic theory and capitalist implementation lies in their shared objective of homogenizing to achieve a neat outcome. The capitalist class does this practically by imposing militant intolerance of imprecision, and by using their political dominance for orienting social demands to conform towards their own personal gain (for example, presenting reluctance to work for them, or work harder, as a moral failing). In this way, they strive to ever-greater productivity and higher profits.

In neoclassical theory, the same homogenization manifests via the following assumptions: that all economic agents are not only “lightning calculators of pleasure and pain” (as Veblen put it), but they live in a world of unimpeded, perfect competition. The eagerness of capitalism’s proponents to accept a conception of the economic “science” as a formulaic reduction -- from complex social and economic relations to a number of faceless exchangers, swapping utility to the mutual benefit of all -- speaks to the interdependency of the prevailing economic system and theory, as the intellectual and moral defense of capitalism.

What effects then can we observe in the real world from the theorization of economics as a set of homogenous inputs and outputs, separate from the social realm? As this paper has argued, this tendency is not harmless or accidental, but is in fact a class-specific tool. This has become especially clear in the past century with more economic activity being financialized, and huge portions of GDPs being tied to dynamic capital systems like the stock market. This sector of the global economy is convoluted; thought to be the realm of experts in math and physics (referred to as “quants”). The game played by capital giants in many ways transcends the widely understood qualities of a classically productive firm, and instead relies on “sophisticated” investment strategies and accounting practices. So sophisticated, in fact, that even regulatory bodies like the SEC have difficulty keeping up, leaving the industry vulnerable to destructive fraud.

A modern capital exchange culture has thus developed which utilizes complex quantitative methods that few enough people understand for it to be dangerous. It hardly matters whether the originators even truly understand the quantitative methods they are using. This is because the movement of capital markets is, ultimately, tied to the attitudes of investors and therefore is inherently volatile and largely unpredictable. Executives know this, and they can (and do) easily bypass the quantitative integrity of their proposed strategies to harness the power of speculation. Those of high position in the financial realm can be likened to shamans, chanting prayers of profit and releasing a heady cloud of quantitative voodoo which obscures their colleagues and investors’ judgement. This is only a slight exaggeration, as account from fallen energy giant Enron shed light on the socially “constructed” versus simply “observed” nature of economic behavior. Starting in 1998 and until the firm’s collapse in 2001,

Enron staged a bizarre spectacle of financial frenzy on the sixth floor of it’s headquarters. An account describing it says:

“Enron’s theatre was expensive, $500 to set up each desk, more for phones in this stage-crafted spectacle, and more for the 36-inch flat panel screens and teleconference rooms. … The entire

set was wired by computer technicians who fed fake statistics to the big screens. On the big day, several hundred employees, including secretaries, played their rehearsed character roles,

pretending to be “energy services” traders doing megadeals. Jeffrey Skilling and Kenneth Lay played their starring role in the Enron dramatis personae to a target audience of invited Wall

Street analysts, who cannot tell real from fake”. (Boje, 468)

Certainly, the impulse not to contradict authority, whether didactic or hierarchical (or both) is a key part of what enables the misuse of math in such a way. Enron’s spectacular crash in 2001, and the fall of other large financial firms such as Lehman brothers in 2008, are excellent examples of the very real destruction that can ensue when mathematized economics transcends itself to become a tool for profiteering. About the Enron scandal, Boje acknowledges this, saying that “At Enron, Management was the gatekeeper of the information, and thus had perfect information… the numbers disclosed were in fact manufactured by Enron management, and could have been called into question by analysts. Enron was in the risk management business and methods of statistical calculations for risk management were highly developed in the financial industry but unused by Enron”. (463)

The danger in mathematizing an essentially social science is that rather than math being one tool in the greater set of tools, it begins to metastasize the science; transforming the very practices, standards, and frame into a highly specialized, abstract thing. This then obscures the direction of information flow. At best, the result is that the fundamental sociality of economics is neglected at best, or worse -- it becomes a tool for exploitation. This is not to say that empirical methods are useless to economics. It is obviously very worthwhile to employ quantitative methods to add greater clarity to the bigger picture – but instead of thinking of these methods as tools for observing and understanding some “economic animal” in the wild, they are better used to consciously and thoughtfully construct economic systems and policies. G.L.S. Shackle, in contrast to Jevons’ lamentations about the lack of empiricism in economics, believed economics to be “its own invention… essentially subjective, epistemic and teleological in nature”. Shackle concludes in kind, remarking that “In natural science, what is thought it built upon what is seen; but in economics, what is seen is built upon what is thought”. (66)

References

Bentham, Jeremy. “Principles of Morals and Legislation”. Ch1, P. IV: On the Principle of Utility. T. Payne & Son. 1789. London. P. 1-5

Boje, David M. et al. “(Mis)using numbers in the Enron Story”. Organizational Research Methods. Vol. 9, Issue 4. 2006. Sage Publications. New Mexico. P. 463-70.

Jevons, Stanley. “Brief Account of a General Mathematical Theory of Political Economy”. The Journal of the Royal Statistical Society. 1866. London. P. 282-87.

Shackle, George L. S. “Epistemics and Economics”. 1972. Cambridge University Press. Cambridge, UK. P. 66-7.

Shapiro, Stewart. “Oxford Handbook of Philosophy of Math and Logic”. 2005. Oxford University Press. NC, USA. P. 536-40.