Why Economics is Still Not a Science of Adaptive Systems
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By Greg Daneke
Gregory A. Daneke is Professor Emeritus at Arizona State University. He held other faculty posts, including: Michigan and Stanford as well as working with research institutes in Europe and Canada. He has also advised government agencies, including: Energy, State, GAO, and White House. He is the author of over 120 scholarly publications and at least 1 diatribe.
Over a hundred and twenty years ago Thorstein Veblen (1898) confronted his fellow economists with their intellectual short-comings. While rejecting biological (as well as Marxian) determinism, Veblen advocated the adoption of an evolutionary perspective involving the interaction of individuals and their institutions. Veblen’s vision has been dramatically enhanced in relatively recent years by developments in computational approaches under the rubric of complex adaptive systems theory (see, Daneke, 1999). Nevertheless, mainstream or neoclassical economics remains mired in myth and magic, as well as captive to a pernicious ideological agenda.
Veblen also asserted that economics was more a normative philosophical enterprise than a science, and it has become increasingly less scientific since his time. However, mainstream claims to natural scientific status are still quite ferocious. Veblen began his observations with the bold declaration the French theorist (De LaPouge, 1897) that “anthropology is destined to revolutionize the political and social sciences as radically as bacteriology has revolutionized the science of medicine (p.54)”. Today, however, most observations from the other social sciences (especially regarding cultural evolution) remain an anathema to many economists. As Margaret Thatcher proudly claimed “there is no such thing as society”.
Following the mainstream’s failure to predict let alone explain the recent global banking crisis it came under widespread attack by pundits, heterodox economists (note, Colander, 2011), and even a couple of Nobel laureates. Nonetheless, the mainstream remains pretty much unscathed and largely unrepentant (Skidelsky, 2018). Some of the old guard has been particularly petulant, but then humility has always been in very short supply among many mainstream economists. Others merely waited for the tempest to pass, and by and large it did. Unorthodox approaches caught a bit of the short-lived tail wind, but gradually fell back into their status as tangential at best.
One particular tangent, known as complex adaptive systems (or simply “complexity”, note: Arthur, 2014; Daneke, 1999; Haldane & May, 2011; Heilbing & Kirman, 2013; Keen, 2017; Elsner et. al. 2015), gained some notoriety, and several of its adherents maintained that it could ameliorate some of the more pressing issues persisting from the near collapse. Essentially complexity economics uses a variety of computational tools (nonlinear math, neural nets, cellular automata, adaptive algorithms, etc.) to simulate the co-evolutionary interaction of heterogeneous agents (exhibiting cooperative, reciprocal, and even altruistic behaviours) and their institutions. It includes elements such as path dependency (historical relevance) and comprehends feedback loops that amplify variance. Plus, it explores semi-spontaneous dynamics and the creation of novel EMERGENT PROPERTIES (where “the whole is greater sum of its parts”). The essential policy focus of complexity is the design of institutions that enhance the overall resilience of a given system. Among other things resilience emphasizes SAFE FAIL, rather than striving for the fool proof, for as Murphy’s Laws maintain “fools are so ingenious”. Furthermore, it includes nonlinearity which aids in the identification of cascading effects across the vast webs of commerce that present unappreciated systemic risks.
So why do so many mainstream economists continue to ignore it? While the unwritten Marquis of Queensberry rules of intellectual fisticuffs outlaw questioning the motives of those inside the status quo ante (those outside are fair game), it is impossible to ignore their ideological agenda. Moreover, the most parsimonious explanation is that mainstream economics is mostly a cult disguised as a science. And as any good study of the political economy of economics would reveal, it is so thoroughly embedded in leading universities, foundations, think tanks, the halls of power (legislative, legal, and financial), and the culture generally that prying it loose, even at the edges, is a monumental task.
Most of models and methods of the mainstream only create a thin veneer of science, and they rarely corresponds to the scientific method we learned back in grade school. Its theories are rarely inductively derived. More like a religion its canon is deductively derived from dogma. It relies upon ill-founded assumptions including, but not limited to, universal omniscient rationality, unalterable preferences, and general equilibrium (see, Madrick, 2014). It is also primarily ahistorical (path independent). Furthermore, to the extent that it is statistical, it is mostly comparative statics as well as mostly limited to the linear (e.g. regression).
The jaundiced eye turned toward recent advances in complexity economics is not the result of scientific considerations. Plus, this is not the mainstream’s first bite at the apple. Following WWII, neoclassicists consciously decided to forego much of the blending of engineering, diverse social sciences, and computational methods (known loosely as operations research), that significantly helped win the war (see, MacKenzie, 2002). They and their wealthy patrons conspired to concoct a toxic brew of anti-systems thinking. Anti-New Deal/anti-Keynesian politics, “red scare” mongering and hyper-militarism were combined with inordinate amounts of fake scientism and applied to illogically discredit most alternative methods and concepts. By the time nonlinear dynamical and computational approaches re-emerged in the guise of chaos and complexity theories in the early 80s, a small cult of neoliberal ideologues had completely captured economics as well as the lion’s share of business school curricula (e.g. “shareholder primacy” see, Daneke & Sager, 2015). More critically they also over-ran the halls of power (government as well as banking). The mainstream selectively and reluctantly adopted certain conceptual devices (e.g. game theory), but only those that could be distorted so as not to challenge their ideological predilections.
The conscientious cloaking of ideology with faux science has been substantially fortified via the efforts of a small yet tenacious cadre that originated with the Mont Pelerin Society (or Pelerins for short, see, Mirowski & Plehwe, 2009). Several of its members and their fellow travelers would receive their self-anointed fake Nobel in Economics (actually the Swedish State Bank Prize). Soon after Ronald Reagan and Margaret Thatcher were exclaiming “TINA” (there is no alternative), “Neoliberalism” (or what I call neofeudalism, see Daneke, 2019) really did become the only game in town as well as across the planet. Its religious elements were carved in stone (including: market fundamentalism, dramatically decreased social spending, and privatization, etc.). Plus, despite their lip service to competitive forces, the Pelerins undermined the enforcement of ant-trust laws, as well as deregulating banking and sanctioning all manner political and corporate corruption. As a result they helped enshrine a new feudal system of massive inequality, radically reduced mobility, and only slightly more subtle levels of kleptocracy than those of backward banana republics.
Following its glaring intellectual debacle, many suggested that neofeudal economics would dramatically decline; Au contraire Mon Amie. It has boldly and openly extended its once subliminal support for a rentier society. Furthermore, they have even effectively diverted populist backlashes into ultra-conservatism and racism (see, Patenaude, 2019) as well as amplifying “managed democracy” and “introverted totalitarianism” (Wolin. 2008). The supreme hypocrisy of extolling anarcho-capitalism (itself an oxymoron), while promoting oligarchy and monopoly, are perplexing enough without the virtual immolation of entire societal systems.
The election of Donald Trump may well be the harbinger of the next stage of devolution (alluded to by Veblen and others), a return to old fashioned totalitarianism. Beyond the arrival of a demonic demagogue, Hanna Arendt (1951) describes how these more virulent systems begin with subtle, yet vast, popular atomization, alienation, and undermining of the public sphere. All existing parties, leaders and policies are ridiculed. And, members of the free press are vilified. The masses that have never had much involvement with politics become agitated and mobilized. Ancient ethnic or cultural differences are amplified and scapegoats invented and harassed. Does this sound familiar? The final elements that distinguish full frontal fascism from the run of the mill version (we already have) involves accelerated surveillance and “the systematic use of terror”.
Thus far neofeudal economics has merely presided over the conversion of broadly inclusive economies into withering rentier states. The immense siege engine of neofeudalism is a perpetual motion debt machine producing vast mountains of counterfeit wealth. As Schumpeter (1934) observed, economic expansions are usually followed by an over-reliance upon financialization and a decline in actual innovation. The US economy, for example, is completely addicted to mega-financialization. Meanwhile it sustains monstrous militarization amid its abject failure to address the “limits to growth” (à la Meadows, et.al. 1972) imposed by resource and climate constraints on a finite planet. Mainstream economists, of course, continue to deny any limits, holding that a fairy land of free markets and open price discovery will merely pluck technological substitutes out of the ether and scale them up without the real economy skipping a beat, or troubling with any negative externalities for that matter. But, the real reason for this mythology is more mundane. In a global system where money is literally “created out of thin air” via the explosion of credit and speculation on processes of repayment/rollover, growth (especially in the debt system itself) is essential. Without exponential growth, debts cannot be repaid with interest, fees, and rents, let alone payouts on piles of super-leveraged side bets.
The US economy, as Bernie Madoff tried to tell us, is one stupendous PONZI SCHEME, where more debt must be continuously created to just service the interest on existing debts, curtail fire sales or devaluations of hyper-inflated assets and/or avoid triggering cascading bankruptcies amid unpayable default swap obligations (to the tune of hundreds of trillions of dollars). This metastization of derivatives adds a whole new level of lunacy to global financial systems that drank the quantitatively juiced neoclassical cool aid (note, Williams, 2011), while partaking of other Pelerin party favours.
When rentiers rule the world, providing a thick smoke screen for maximization of unearned and unproductive wealth becomes the sine qua non for economists who know on what side their bread is buttered. It is no accident that money and banking are conspicuously absent from most macroeconomic models, especially since the melding of micro and macro theory during the early reign of the Pelerins. Likewise most macroeconomists ignore the accumulation of power, and how existing institutions accelerate the maldistribution of the resources and opportunities.
Even if economists were to step up their adoption of complex systems tools and concepts, they are unlikely to break thought their self-imposed firewall regarding the actual ecology of institutions. Too many sacred cows and kleptocrats would be revealed (and reviled). Initially many who dabbled in things such as “agent-based models” assumed that they could have their cake and eat it to. That is that they could merely graft these interactive simulations (with heterogeneous agents and their evolving strategies) onto the tree of neoclassical economics, while ignoring all the existing and evolving institutions. Their little gingerbread economic person (homo economicus) that allows them to toss away all the inconvenient dough, could be more readily spread with unearned icing. Meanwhile, the relatively few who have come to realize that complex systems research would yield wildly different assumptions about how and for whom our economies actually work could be easily held at bay.
If economics was ever to seek to improve the human condition, let alone become an evolutionary science, it needs to follow Veblen further and embrace an institutional ecology approach (see, Daneke, 1999). Recall Veblen’s A Theory of the Leisure Class (1899) provided a powerful critique of a previous “Gilded Age”, much like our own. In his various books Veblen plumbed the societal processes that impede or enhance the functioning of the economy and highlighted those that buttressed predatory impulses. Veblen further maintained that many of the institutions of business and finance are actually a throwback to our more “barbaric” past, and often overwhelm and degrade the positive attributes of industry (1904).
When it comes to reintroducing the misplaced cultural features of political economy, the ersatz neutrality of mainstream economics invokes either a cynical technocratic (and anti-democratic) approach or a naïve (and inauthentic) anarchic utopianism. By assuming for so long that political processes were irrelevant, economists tend to take overly simplistic views toward institutional testing and redesign. I once chided my political science colleagues who were so enamoured with neoclassical applications (e.g. rational choice theory) that they were giving up their perfectly adequate inquiries to become mediocre economists. Now the case is reversed for earnest, yet ill-equipped, economists. If political economy is going to be restored via the use complexity tools and the evolutionary concepts, the various ingredients (psychology, anthropology, ethics, etc.) need to be on an equal footing.
Complexity economics without political and cultural sensitivity could merely replace homo economicus with machina economica. Even armies of widely diverse agents could produce relatively minor patterns of adaptation or exaptations after multiple exposures to the forced optimization of advanced A.I. (artificial intelligence). This would be a prime case of the curse of “getting what we wished for” when colleagues and I back at the University of Michigan touted an “artificial reality check for economists”. A.I. might cast out the baby of “perpetual novelty” (note, Holland, 2014) for the sake a bigger BIG DATA bathtub. Furthermore, as the piles of “semi-unsupervised” algorithms spewing forth from “deep learning” (neural net) machines continue to displace human judgements we could find ourselves at the mercy of models more impenetrable than those currently used as an apology for widespread economic inequities and incongruities. Biases embedded in big data and amplified by tiny coding errors (plus coder biases) as well as Bayesians inferences, could give us many a distorted policy picture. With the collection and manipulation of data becoming its own asset class, who knows what mischief its owners might get up to within those proprietary “black boxes”? Reconsider the widespread wreckage owing to the role of “quants” and their arcane obfuscation of risk and reason within banking and finance.
The promise of A.I., while over-hyped for over half a century, may be finally coming to fruition. Certainly the advances in medicine and other information intensive industries could be immense. Yet, even when it is earnestly and honestly done (e.g. NOT merely applied as a tool for increased surveillance and societal atomization), A.I. and its brute efficiency aims exacerbate the classic conundrum of sustaining reasonable levels of production and consumption. To update a modern adage, “a robot can build a car [and even drive a car], but a robot will never buy a car”. We have yet remotely begun to address the societal impacts of the impending advanced algorithmic avalanche.
This second and more transformative stage of the I.T. (information technology) revolution, with machines that think for themselves (but not necessarily like humans), is NOT merely another skirmish in the war on labour launched decades ago by the Pelerins and their various baby Borks from the “Law and Economics Movement” (some of which now sit on the US Supreme Court). Hard won institutions of labour justice are now being washed away in the burgeoning “Gig Economy”. The ranks of the “Precariat” (precariously employed proletariat, see Standing, 2014) will soon swell with AI induced redundancies, as well as legions of climate and conflict refugees. These displaced and disenfranchised individuals are easy pickings for any demagogue (either right or left) who promises to restore past glories or forge utopian futures.
Employment impacts may be the least of our worries, however. While weak on treatments, I.T. pundit and Harvard Business School Professor, Shoshana Zuboff (2019) has diagnosed several of the pressing societal ailments associated the so-called “internet of things” and A.I. advances in her sweeping 700 hundred page tome, The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. After years of being a cheerleader for the information epoch, she sheds light on its darker-side. She details how the development of what she calls the “behavioural surplus” (which began with Google) is ushering in an entirely new era of monopolized and mismanaged capitalism. She even implies that this new business model is an extension of Pelerin predominance. Hoody-wearing wankers in Silicon Valley actually call this “data exhaust”, and it is being reinjected to turbocharge the ancient systemic processes of expropriation and dispossession. More sinister perhaps, some of the providers of our various new tech devices not only seek to extract our very essences and commodify them, they want to radically reprogram us and sort us into A.I. invented cohorts. This can amount to “red lining” one’s life before they even have a chance to live it. Worse yet, they delude themselves that their self-learning machines will somehow discover the algorithmic amalgams of large scale social control, and that the outcomes will be benign.
This resurrection of B. F. Skinner (1971) fails to recognize his backward science. In science generally, control is an exceedingly rare pinnacle of constantly revalidated predictive theorizing. As such it is far rarer, if not completely impossible (and perhaps repugnant), in the social sciences. Much like mainstream economists, Skinner began at the wrong end with strategies of behavioural modification and merely assumed he had explained away human “freedom and dignity”. Nowhere perhaps is an investigation of the complex ecology (including machine behaviour) more needed than in this realm (look for, Daneke, forthcoming).
Well actually, a more dire need for a thoroughgoing ecological approach to economics has been with us for some time. It will be absolutely vital to subduing the banking, oil, and weapons axis. However, even if mainstream economists can somehow be turned to the task, I am not sure whether there is time left to rescue democratic capitalism, let alone ameliorate many of our on-going crises. Even in the so-called “hard sciences” progress is made, as Max Plank observed, “one funeral at a time”. Besides, we are dealing mostly with a culturally fortified ideological edifice rather than a social science. Furthermore, elites are unlikely to sacrifice their long-term investments in such a successfully disguised feudal restoration. Plus, in our present “alternative facts” political environment with its internet driven cynicism and nihilism, it is not clear whether proven science matters much anymore. Yet, propaganda, misinformation, political skullduggery, and economists pandering to parasites and pirates have always been vital ingredients within the evolution (and/or devolution) of economic systems. So we had better get busy immediately.
Arendt, H. (1951). The Origins of Totalitarianism. Cleveland: Meridian.
Arthur, B. (2014). Complexity and the Economy. Oxford: Oxford University Press.
Colander, D. (2011). Is the Fundamental science of macroeconomics sound? Review of Radical Political Economics 43(3): 302-309.
Daneke, G.A. (1999). Systemic Choices: Nonlinear Dynamics and Practical Management. Ann Arbor: University of Michigan Press.
Daneke, G.A. and A. Sager (2015). Ghoshal’s Ghost: Financialization and the End of Management Theory. Philosophy of Management, 14(1): 29-45.
___________ (2019). Serfs Up; Finance, Feudalism, & Fascism: Ruminations of the Political Economy of Our Time while there is Still Time. Seattle: Amazon Paperback, 2019.
_________ (forthcoming). Automacene Rising: The Political Economy of the Artificial Intelligence Revolution.
De LaPouge, M. (1897).The fundamental laws of anthropo-sociology, Journal of Political Economy, 6(1): 54-92.
Elsner, W., T. Heinrich, and H. Schwardt (2015). The Microeconomics of Complexity. New York: Elsevier.
Haldane A. and R. May (2010). Systemic risk in the banking ecosystem, Nature, 469 (Jan.): 351-355.
Helbing, D. and, A. Kirman (2013). Rethinking economics using complexity theory, Real-world Economics Review, 64: 23-52.
Holland, J. H. (2014). Complexity: A Very Short Introduction. Oxford: Oxford University Press.
Keen, S. (2017). Can We Avoid Another Financial Crisis? Cambridge: Polity Press.
MacKenzie, D. (2002). The imagined market, London Review of Books, 24(21): 22-24.
Madrick, J. (2014). Seven Bad Ideas: How Mainstream Economists Damaged America and the World. New York: Vintage.
Meadows, D., D. Meadows, J. Randers, and W. Behrens. (1972). the Limits to Growth. New York: Universe Books.
Mirowski, P. & D. Plehwe Eds. (2009). The Road from Mont Pelerin: The Making of the Neoliberal Thought Collective. Cambridge: Harvard University Press.
Patenaude, W. (2019). Modern American populism: Analyzing the economics behind the “silent majority”, the tea party, and Trumpism. American Journal of Economics and Sociology, (78)3: 787-834.
Schumpeter, J. (1934). The Theory of Economic Development. Cambridge: Harvard University Press.
Skidelsky, R. (2018). Money and Government: Unsettled Issues in Macroeconomics. New Haven: Yale University Press.
Skinner, B. F. (1971). Beyond Freedom and Dignity. Cambridge, MA: Hackett Publishing. Standing. G. (2011).
The Precariat: The New Dangerous Class. London Bloomsbury Academic.
Veblen, T. (1898). Why economics is not an evolutionary science. Quarterly Journal of Economics. 12(4): 373-397.
______ (1899). The Theory of the Leisure Class. New York: MacMillan.
______ (1904). The Theory of Business Enterprise. New York: Charles
Williams, E. (2010). In the land of blind, the one-eyed man is king: How financial economics contributed to the collapse of 2008-2009. Journal of Post-Keynesian Economics 34 (1): 3-23.
Wolin, S. (2007). Democracy Incorporated: Managed Democracy and the Specter of Inverted Totalitarianism. Princeton: The Princeton University Press.
Zuboff, S. (2019). The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. New York: Public Affairs.
From: pp.6-10 of WEA Commentaries 9(2), June 2019
In common with so many other commentators of the economics scene, this article has many assumptions implied in it. The worst one that I can see, is the feeling that the complexity of our social system presents us with a challenge that can only be solved by the computers and their burgeoning programmers, so we have little hope of making real progress in what might be thought to be an ever darkening pseudo-scientific world.
In my view this could not be further from the truth, and by asking the right question our once dismal science can be transformed into a real bright shining and true one, without even a single doubtful pseudo adjective needing to be appended. The question to be answered is: “How many different KINDS of business deals are needed as a minimum, to cover the whole of our social system.”
The answer is 19, and how one arrives at this relatively small number may be found in my working paper SSRN 2865571 “Einstein’s Criterion Applied to logical Macroeconomics Modeling”.
Having appreciated what this implies, the associated axioms, assumptions, and definitions needed for approaching our subject allows for a presentation that is both seamless and fully comprehensive. My 310 page e-book (write to me for a free copy) which is included in the references of this paper, allows the would-be open-minded student to approach this whole past-badly expressed subject from a completely new perspective and I think he will find that the results are little short of being sensational. At last, after Adam Smith began the process, can we better understand how the whole shebang actually works!
This commentary is deeply appreciated. There are so few, even among critics of the mainstream, who understand the meaning of “an evolutionary perspective involving the interaction of individuals and their institutions”. The fact that the Financial Stability Board, which leads the global reform of financial regulation, does not appreciate the need to focus on “the design of institutions that enhance overall resilience”, with an emphasis on “Safe fail”, leaves us with international banks that are no less prone to catastrophic failure that they were in 2007/8. I have had the opportunity to raise these concerns with the Governor of the Bank of England and leading think tanks in Washington DC, albeit less cogently than Prof Daneke does, and it is clear that they simply do not appreciate the nature of the problem. There is much work to be done.
One of the advocates of an evolutionary systems approach to economics not referenced in this excellent article is Kenneth Boulding. He was cofounder of general systems theory and even president of the American Economic Association in 1968. His 1978 book, Ecodynamics: A New Theory of Societal Evolution, should, in my view, have lead to a Nobel prize and remains one of the most important works in economics.
For example Boulding wrote:
“Equilibrium has become a kind of holy sacrament in economics and has seriously diverted attention from the real world of Heraclitean flux . . . The economic system is a structure in space-time. Consequently, it is evolutionary, subject to constant and irreversible change.”
“Our own society cannot be understood by equilibrium concepts alone. The universe is a disequilibrium system and has been from the very beginning. Equilibrium, therefore, is a figment of the human imagination. It is a product of our limited perception.”
“The classical economic taxonomy of factors of production into land, labour and capital is too heterogeneous to be useful; know-how, energy and materials are a much more useful taxonomy in understanding productive processes.
” Another taxonomic and conceptual problem that has plagued economics from the time of Adam Smith is the confusion between stocks and flows . . . The capital stock is a population of items, production is births into that population, consumption is deaths . . . Furthermore, the idea that production is consumption is only partly true. What we get satisfaction from for the most part is use, not consumption . . . This has led to an extraordinary neglect of information collection about the capital structure . . . and the absurd view that it is income which is the only measure of riches.”