An Ecosystem Approach to Economic Stabilization

Rodrick Wallace

• Éditeur: Routledge
• Année: 2015
• ISBN:
  9781317566687
• Édition: 1
• Sujet: Betriebswirtschaft
• Sous-sujet: Business allgemein

The creation of economic institutions that can function well under substantial uncertainties -- Black Swans -- is analogous to the dilemmas confronting our hunter-gatherer forefathers in the face of large-scale ecological unpredictability. The ultimate solution was not the development of a super hunter-gatherer technology that could ride out repeated catastrophe, but rather the invention, in neolithic times, of culturally-adapted 'farmed' ecosystems constructed to maximize food yield and minimize risks of famine.

Recent advances in evolutionary and ecosystem theory applied to economic structure and process may permit construction of both new economic theory and new tools for data analysis that can help in the design of more robust economic institutions. This may result in less frequent and less disruptive transitions, and enable the design of culturally-specific systems less affected by those that do occur.

This unique and innovative book applies cutting-edge methods from cognitive science and evolutionary theory to the problem of the necessary stabilization of economic processes. At the core of this book is the establishment of a statistics-like toolbox for the study of empirical data that is consistent with generalized evolutionary approaches. This toolbox enables the construction of both new economic theories and methods of data analysis that can help in the design of more robust economic institutions. This in turn will result in less frequent and less disruptive Black Swans, and enable as well the design of culturally-specific systems less affected by those that do occur.

1
The crisis in economic theory

1.1 Introduction

While this volume is not a history of economic thought and its current evolutionary branching – many such already exist (e.g., Beinhocker 2006; Nelson and Winter 1982; Boschma and Martin 2010; Diamond 1997, 2011; Hodgson and Knudsen 2010) – a powerful influence during the author’s conversion from a physical to a social scientist was a letter from the Nobel prizewinning economist Wassily Leontief that appeared in a 1982 issue of Science to the effect that

Page after page of professional economics journals are filled with mathematical formulas leading from sets of more or less plausible but entirely arbitrary assumptions to precisely stated but irrelevant theoretical conclusions. … Year after year economic theorists continue to produce scores of mathematical models and to explore in great detail their formal properties and the econometricians fit algebraic functions of all possible shapes to essentially the same sets of data without being able to advance, in any perceptible way, a systematic understanding of the structure and the operations of a real economic system.

Tony Lawson, extending Lawson (2009a, b), at the 2010 INET Conference in London, quotes Leontief and a long stream of recognizably similar complaints from well-regarded ‘mainstream’ economic and econometric theorists: Rubenstein (1995), Milton Friedman (1999), Ronald Coase (1999), Mark Blaug (1997), and so on. These are not criticisms made by marginalized ‘heterodox’ academics, but by central practitioners of the modern discipline.

Lawson’s (2006) earlier manifesto on the nature of heterodox economics explains some of the underlying problems. It focuses, first, on characterizing the essential features of the mainstream tradition as involving explicitly physics-like, deductive mathematical models of social phenomena that inherently require an atomistic perspective on individual, isolated ‘economic actors.’ Lawson (2006) explains the need for isolated atomism in mainstream theory as follows:

Deductivist theorizing of the sort pursued in modern economics ultimately has to be couched in terms of such ‘atoms’ just to ensure that under conditions x the same (predictable or deducible) outcome y always follows. The point then, however unoriginal, is that the ontological presuppositions of the insistence on mathematical modelling include the restriction that the social domain is everywhere constituted by sets of isolated atoms.

In Lawson’s (2006) view, post Keynsianism, (old) institutionalism, feminist, social, Marxian, Austrian and social economics, among others, are part of a generalized social science in which

The dominant emphases of the separate heterodox traditions are just manifestations of categories of social reality that conflict with the assumption that social life is everywhere composed of isolated atoms.

Lawson (2012) concludes that the only consistent ‘ideology’ identifiable in mainstream economic theory is the compulsive adherence to an atomistic mathematical model strategy.

Although there is criticism of Lawson’s perspective (e.g., Fullbrook 2009), many of his basic ideas seem to hold up well, but there is something deeper operating than simple constraints driven by formal mathematical limitations.

Since ecosystem theory was discovered by the physicists (e.g., May 1973), the field has been bedeviled by just the kind of mathematical modeling that Lawson decries. In reply to May and similar practitioners of physics-like modeling in biology and ecology, Pielou (1977, p. 106) writes:

[Mathematical] models are easy to devise; even though the assumptions of which they are constructed may be hard to justify, the magic phrase ‘let us assume that’ overrides objections temporarily. One is then confronted with a much harder task: How is such a model to be tested? The correspondence between a model’s predictions and observed events is sometimes gratifyingly close but this cannot be taken to imply the model’s simplifying assumptions are reasonable in the sense that neglected complications are indeed negligible in their effects …

In my opinion the usefulness of models is great [however] it consists not in answering questions but in raising them. Models can be used to inspire new field investigations and these are the only source of new knowledge as opposed to new speculation.

That is, mathematical modeling in biology, ecology, and social science is at best a junior partner in an ongoing dynamic relation with empirical or observational study. Under such circumstances, models can sometimes help. A little. Infrequently.

One is, however, usually inclined to prefer, as an alternative to yet another mathematical thicket, a clearly thought-out verbal model, illustrated by a few equally clear flow diagrams, followed by an appropriate number of elegant, clever, data-rich, observational or experimental case histories. Science then follows.

But there is even more going on here: recently, criticism has emerged of gene-based ‘replicator dynamics’ versions of evolutionary theory that suffer similar atomistic model constrictions (e.g., Lewontin 2000, 2010). Much of the debate in evolutionary theory has revolved around the ‘basic’ target of selection, with the Modern Evolutionary Synthesis heavily invested in the atomistic, gradualist theory of mathematical population genetics (e.g., Ewens 2004). Heterodox, non-atomistic, heavily contextual, evolutionary theories have emerged that materially challenge and extend that Synthesis, most often through focus on how selection pressures operate at scales and levels of organization beyond the individual organism (e.g., Gould 2002; Odling-Smee et al. 2003; Wallace 2010a).

These are, then, two similar case histories. Is atomism simply a ‘requirement’ of ‘physics-like’ mathematical modeling, or are deeper constraints at work, in contrast with Lawson’s conclusions?

1.2 The psychology of atomism

Economics and evolutionary theory are not the only biological/social sciences to come under the same gun. The cultural psychologist Steven J. Heine (2001) writes:

The extreme nature of American individualism suggests that a psychology based on late 20th century American research not only stands the risk of developing models that are particular to that culture, but of developing an understanding of the self that is peculiar in the context of the world’s cultures.

The explanation of ‘atomism’ goes deeper than ideology, into the very bones of Western culture: Nisbett et al. (2001), following in a long line of research (Markus and Kitayama 1991, and the summary by Heine 2001), review an extensive literature on empirical studies of basic cognitive differences between individuals raised in what they call ‘East Asian’ and ‘Western’ cultural heritages, which they characterize, respectively, as ‘holistic’ and ‘analytic.’ They argue:

• 1. Social organization directs attention to some aspects of the perceptual field at the expense of others.
• 2. What is attended to influences metaphysics.
• 3. Metaphysics guides tacit epistemology, that is, beliefs about the nature of the world and causality.
• 4. Epistemology dictates the development and application of some cognitive processes at the expense of others.
• 5. Social organization can directly affect the plausibility of metaphysical assumptions, such as whether causality should be regarded as residing in the field vs. in the object.
• 6. Social organization and social practice can directly influence the development and use of cognitive processes such as dialectical vs. logical ones.

Nisbett et al. (2001) conclude that tools of thought embody a culture’s intellectual history, that tools have theories built into them, and that users accept these theories, albeit unknowingly, when they use these tools.

In their famous paper ‘Culture and Change Blindness’ Masuda and Nisbett (2006) find:

Research on perception and cognition suggests that whereas East Asians view the world holistically, attending to the entire field and relations among objects, Westerners view the world analytically, focusing on the attributes of salient objects … Compared to Americans, East Asians were more sensitive to contextual changes than to focal object changes. These results suggest that there can be cultural variation in what may seem to be basic perceptual processes.

As Nisbett and Miyamoto (2005) put the matter:

There is recent evidence that perceptual processes are influenced by culture. Westerners tend to engage in context-independent and analytic perceptual processes by focusing on a salient object independently of its context, whereas Asians tend to engage in context-dependent and holistic perceptual processes by attending to the relationship between the object and the context in which the object is located. Recent research has explored mechanisms underlying such cultural differences, which indicate that participating in different social practices leads to both chronic as well as temporary shifts in perception. These findings establish a dynamic relationship between the cultural context and perceptual processes. We suggest that perception can no longer be regarded as consisting of processes that are universal across all people at all times.

Wallace (2007), who uses methods similar to those of this volume, writes:

A recent ‘necessary conditions’ mathematical treatment of Baars’s global workspace consciousness model, analogous to Dretske’s communication theory analysis of high level mental function, [can be] used to explore the effects of embedding cultural heritage on inattentional blindness [which is analogous to change blindness]. Culture should express itself quite distinctly in this basic psychophysical phenomenon across a great variety of sensory modalities because the limited syntactic and grammatical bandpass of the rate distortion manifold characterizing conscious attention must conform to topological constraints generated by cultural context.

As this book will show, a new class of statistical and analytic models likely to be useful as subordinate partners in the experimental and observational study of economic pattern and process can be developed that is not mathematically constrained to an underlying atomism.

Profound, culturally based, ‘ideological’ constraints abound across a plethora of Western scientific disciplines, including economics. Empires, however, do not always successfully construct their own realities, and models and policies based on those constraints can fail catastrophically. Several case histories will be given in later chapters.

1.3 The self-referential dynamic

A centrality of Lawson’s (2010) critique regarding the current use of mathematical models in economics is that

[T]here is a basic mismatch between the sorts of mathematical methods economists employ and the nature of the social, including economic, phenomena that economists seek to illuminate … Most fundamentally, [economists’] methods can be seen to be restricted to closed systems systems... [T]o date such closures have been found to occur only very rarely in the social realm... [and] we have good reason to suppose they will remain uncommon. Only for a closed system can one easily impose ‘entropy maximization’ or similar variational strategies in a search for equilibrium or long-time limit configurations. Open systems may be better addressed using Onsager-like formalisms abducted from nonequilibrium thermodynamics, at least as an empirical starting approximation.

One of the advantages of the (broadly) evolutionary perspective taken in this volume is that evolutionary, as opposed to mainstream economic, theorists have long understood the deeply self-referential form of complex, inherently open, natural phenomena. As Goldenfeld and Woese (2010) put the matter,

[T]he genome encodes the information which governs the response of an organism to its physical and biological environment. At the same time, this environment actually shapes genomes through gene transfer processes and phenotype selection. Thus, we encounter a situation where the dynamics must be self-referential: the update rules change during the time evolution of the system, and the way in which they change is a function of the state and thus the history of the system self-referential dynamics is an inherent and probably defining feature of evolutionary dynamics and thus biological systems.

Others have repeatedly observed the recursive, self-referential nature of evolutionary process, and postulated something approaching a ‘language of evolution’ (Langton 1992; Sereno 1991; Von Neumann 1966). Language dynamics – the product of an information source – are, of course, inherently open, and not subject to deductive mathematical stricture.

It can be argued that self-referential dynamics are equally a feature of most social – and hence economic – enterprise and interaction, raising, among other things, profound questions regarding the utility of ‘sufficient’ game-theoretic formulations beyond the simplest of toy representations of reality, as well as putting the cap on the large-scale utility of deductive mathematical theory for such phenomena.

Here, we explore self-referential dynamics from the perspectives of Wallace (2010a, 2011a), recognizing that the representation of fundamental socioeconomic processes in terms of information sources restrains, somewhat, the inherently nonequilibrium nature of open systems. Although information sources are both nonequilibrium and irreversible (continuously using resources and having few palindromes), the asymptotic limit theorems of information theory, and their extension to control theory via the Data Rate Theorem, permit the study of quasi-stable nonequilibrium steady states under broad necessary conditions constraints that permit construction of statistical models useful in data analysis.

2
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