Home > Uncategorized > Differences in theoretical methodology: equilibrium vs. complexity vision

Differences in theoretical methodology: equilibrium vs. complexity vision

from David Colander and RWER no. 91

The two visions draw lessons from theory differently, and are associated with quite different research programs, especially as they relate to policy. The equilibrium vision sees formal theory as providing a necessary blueprint for policy. Franklin Fisher (2011) nicely captures this view. He writes,

“It is not an overstatement to say that they (the general equilibrium welfare theorems) are the underpinnings of Western capitalism… So elegant and powerful are these results (G.E.’s exploration and proofs of existence, uniqueness, and optimality) that most economists base their conclusions upon them and work in an equilibrium framework.”

In the equilibrium vision, without formal theory, policy has no scientific foundation. It takes the position: Better to have an inadequate formal theory than no formal theory at all.

The complexity vision sees developing a useful tractable formal general theory as currently far beyond our capabilities and instead focuses on gaining partial insights into the complex dynamics of the economy in whatever way it can – agent based models, simulations and general exploration of non-linear dynamic models. Since formal dynamics is analytically so difficult, the complexity vision is content with informal theory especially when talking about the aggregate economy. It takes the position: When guiding policy it is better to recognize that we have no directly useful formal theory than to confine policy analysis to an inadequate formal theory. Within the complexity vision ultimately, because the formal specification of the economy is so beyond our current analytic capabilities, even the best economic policy is based on heuristics, not scientific theory, and thus, in a formal scientific sense, is ungrounded. Policy advice should not be presented to policy makers as otherwise.

The complexity approach to policy holds that, because of the complexity of economic theory’s relationship to the real world, policy discussions are best separated from scientific discussions. Policy discussions should be based not directly on formal scientific theory, but, instead, on educated common sense – a wide ranging knowledge of economic scholarship that includes a good understanding of where researchers are in advancing formal theory, a good understanding of the history and institutions of the economy, a detailed familiarity with empirical data about the economy, and a philosophical understanding of the role that ethical views play in arriving at policy advice. Good policy is based on far more than just economic science.

The complexity approach divides economic analysis into two separable fields: science, whose goal is to discover the truth, and applied policy, whose goal is to solve real-world problems. The two fields are separated by a firewall to reduce the possibility of policy views influencing scientific judgments.[1] The goal is to allow specialization and gains from trade. The same economist could do both science and policy, but the two activities would use different methodologies, and would require different skill sets.

While the complexity methodology downplays the importance of formal theory in directly guiding policy, it is not against formal deductive theory, abstract mathematics, or sophisticated empirical research. But the goal of that theoretical research is a scientific goal – to better understand the economy; the goal is not to guide policy (although some policy guidance might follow as an unintended consequence). Thus, the complexity vision’s scientific research agenda is consistent with a vigorous and highly abstract theoretical and empirical research agenda that, if anything, because its focus on complex dynamics, is even more mathematically and statistically complex than the current research agenda associated with the equilibrium vision. In that sense the complexity methodology is quite different from the critical realist methodology espoused by heterodox critics of economics such as Tony Lawson.

Critical realists criticize equilibrium methodology for its emphasis on abstract mathematics; complexity theory embraces mathematics. Complexity economists criticize the equilibrium methodology for the way it uses theory in thinking about policy, not for its use of mathematics. Whereas the equilibrium methodology treats formal theoretical results as central to its applied policy research, the complexity methodology uses formal theory more as a fable or heuristic, which may or may not be relevant for policy. Within the complexity vision, formal theory is best thought of as a thought experiment that can be useful both for thinking creatively about policy problems and for preventing logical mistakes in reasoning. But, because the theory is only tenuously related to the real world economy the theory is meant to capture, the results of formal theory are not to be thought of as a blueprint for policy.

The distinction among the equilibrium, complexity and critical realist/heterodox views of the equilibrium methodology can be seen in reference to the well-known “searching for the keys under the lamppost joke.” The standard interpretation of the joke embodies the critical realist view. It is that economic theorists are out there in La-la-land, doing highly abstract economic research unrelated to the real world.

“Isn’t it stupid – searching where you haven’t lost the keys just because that’s where the light is?”

“Isn’t it stupid – working on models that you know are so far from reality that they can’t possibly describe reality: representative agent super rational choice models, when it’s obvious that the action is in interactive effects; Isn’t it stupid to work with strict rationality models, when it’s obvious that people are at best boundedly rational?”

From a complexity standpoint, a research strategy of “searching where the light is” is far from stupid. Where else but where the light is can one do formal theory? Where the complexity vision has a problem with the current equilibrium methodology is with its attempt to apply the abstract theory, developed where the light is, directly to policy. That’s the equivalent to searching for the keys where you did not lose them, and deserves the critical realists’ scorn. The complexity vision sees the goal of theorists searching in the light to be discovering potential patterns that help them understand the economy. While the goal is not to guide policy the discovered patterns might be helpful to applied policy researchers exploring in the dark. Theorists are developing an abstract knowledge of economic topographies, exploring abstract topographies where there are the equivalent of rocky cliffs, where there are smooth deltas, rolling hills, and where sudden storms changed the topography quickly, as a small creek becomes a raging river. This leads to a second role for theorists—to develop creative abstract policy solutions to deal with different topographies. These abstract solutions may or may not be transferrable to the real world. But the exploration can suggest other solutions that might work. The goal of this part of policy theorizing is creative design of policy.  read more

  1. ghholtham
    March 23, 2020 at 10:35 pm

    I think this is a good summary of the current situation, though rather too kind to equilibrium theorists who by inventing representative agents and turning macroeconomics into a bastard branch of microeconomics have set the subject back forty years. The sad fact is that the old Klein-style structural models used by Finance Ministries and central banks were better for forecasting and – pace Lucas – for policy analysis, despite their manifold shortcomings, than the DSGE models that have replaced them. A form of methodological extremism, which insists on awarding axiomatic status to something that should be a matter of empirical research and then ignores all real world problems of aggregation of heterogenous agents, should not be let off so lightly. The accomplishments of economic theory as useful fables can be conceded in many contexts but the colonisation of macroeconomics has been a disaster, leaving the subject in a similar state to the old Belgian Congo.

    • March 23, 2020 at 11:45 pm

      “[R]ather too kind to equilibrium theorists”? That is still to miss the point that equilibrium in economics is an aim we have to achieve, not something that happens automatically.

  2. March 24, 2020 at 1:12 am

    Equilibrium models are not just ‘inadequate’. They are wildly misleading. The real economy, and a complex system, has radically different behaviour. As I keep saying, as different as wild horses from a rocking horse.

    And there’s a simple route into understanding how different they are: economies of scale, which are pervasive, which generate exponential growth, which is a signature of instability.

  3. March 24, 2020 at 8:58 am

    In my view, the discussion so far only scratches the surface of the profoundly different theoretical opportunities, which ‘complexity economics’ offers today. It is not just the old debate between theory and application – in a new dress. My proposal on the deeper issues is too long for a blog contribution, but those who are interested can read my contribution to the special issue on ‘Complexity Economics’ of the Review of Evolutionary Political Economy (to appear later this year, here is the working paper): https://www.econ.tuwien.ac.at/hanappi/Papers/MPRA_paper_98129-Complexity.pdf
    Hardy Hanappi

    • March 26, 2020 at 11:26 am

      Gerhard, I found your paper very interesting. I have been arguing on somewhat similar lines (particularly about complex numbers and the overlooked significance of Chomsky on human brain structure and computing technology) for at least 35 years. Good to find like minds? My presentation at age 83 is nothing like as good as yours, but anyway, I’m emailing you my current working paper to see what you can make of it.

  4. Frank Salter
    March 24, 2020 at 1:19 pm

    Why is the conversation being restricted to equilibrium, a nonsensical concept ans the vague “convexity” when my analysis of abstract production theory describes the structures in the economy completely?

  5. ghholtham
    March 25, 2020 at 6:27 pm

    “[R]ather too kind to equilibrium theorists”? That is still to miss the point that equilibrium in economics is an aim we have to achieve, not something that happens automatically.”

    It doesn’t happen automatically because it doesn’t happen at all. Furthermore it isn’t a sensible objective of policy except in a metaphorical sense. We should want the economy to be broadly dynamically stable and to respect environmental limits. It won’t ever be in a statistical equilibrium, never mind the sort depicted in economic theory.

    Gerhard Hanappi, I enjoyed your paper. This blog is quite rich in people telling economists how to theorise and quite a lot of it is good advice. But one thing is noticeable – few take their own advice and produce a useful theory. I am sure a complex evolving system is the right way to view society, including its economic face. Yet systems theory has not produced concrete suggestions for how to conduct any economic policy, so far as I am aware.

    • March 26, 2020 at 8:51 am

      Gerard, with respect, I’m taking “equilibrium” in a mathematical sense, not a metaphorical one: i.e. as a concept with many applications, not as an application illustrative of the concept. See Kant’s explanation in my comment on Asad’s paper in RWER91.

      You are of course right, economics will never be in statistical equilibrium, as the concept is illustrated by a liquid finding its own level in a U-tube. When, as in modern cybernetic logic the equilibrium is a dynamic one – the course being pursued by a ship or the policy being pursued by a “ship of state” – the motion stays on course only because the steersman corrects errors as they arise and (through his instruments) become recognisable. If you look back you will find I myself have been advocating this theory of PID servos as a “useful theory” (more useful anyway than Adam Smith’s “invisible hand”). That is “complex” in the mathematical, not literal sense; the chaos of the Santa Fe complexity theorists is explained by acting on D feedback (avoiding problems) faster than resultant deviations are corrected with I feedback. I have been able to show empirically how evolution follows and algorithmically continues to follow the same pattern (P feedback before I before D), as life starts from no feedback through linear plant forms to circulating blood forms and circulating thought forms. This permits our language and invention and art, but sadly also new forms of error like viruses.

      While individually we are being plagued by a coronavirus, the economy is again succumbing to the plague of usury, and needs “vaccinating” with “honest money” if it is going to survive it. So yes, we agree, a complex evolving system is the right way to view society, but that means we need to understand both the dynamic logic of navigation – or more realistically, introduce institutions functioning like satnavs – and aim to provision rather than exterminate each other. The institution I particularly have in mind is the setting of local population targets, with locally significant feedback not only on births and deaths but on the scheduling of pregnancies.

      • March 26, 2020 at 10:53 am

        PS. I see what I called “dynamic equilibrium” is included in Newton’s first law of motion:

        “Every body perserveres in its state of rest, or of uniform motion in a straight line, unless it is compelled to change that state by forces impressed thereon”.

        Hence the corollary (Newton’s first), as in Wheatstone’s Bridge:

        “A body by two forces conjoined will describe the diagonal of a parallelogram [e.g. a diamond or a square], in the same time that it would describe the sides, by those forces apart”.

  6. March 26, 2020 at 10:45 am

    Hi!

    My F-Secure does not allow to load the full article, as it claims the site has been notified as being harmful. Is this another ploy by mainstream economists or is there a real problem?
    Best,
    Paul Jonker-Hoffrén

  7. March 27, 2020 at 11:24 am

    I enjoy reading this post which is organized with clear and reasonable logics. Mainstream economics could be seen as a result of those work that prefer easy researches while leaving aside other matters i.e. “searching for the keys under the lamppost” while neglecting the surrounding darkness, but where the keys may or may not stay. The metaphor reveals some new meanings of “formal theory”. In fact, as I know, mainstream economists have never perceived that what their writings are understood are very different from what they try to say, and most of them never conceived to subvert common sense or experiences. Correct interpretation of mainstream is the prelude for a correct new economics.

    The above perspective leads to a unified economics synthesizing both sides. Where? How? Is it possible? The author seems pessimistic, however, I’d like to report again that it has been done 15 years ago, the solution has, with 3 published books, become more mature to date. Welcome to visit my site to read the new introductory papers and translations. Thanks!

    I’d like to add that, the social realities are a mixture of consistencies and discords, equilibria and disequilibria, convergences and divergences, etc., and all of the above are really the respective results of the Algorithmic logic, so the Algorithmic unification complies with general scientific principles and simultaneously holding inside pluralities and conflicts (ridiculous logic? Not at all!) Complexities are not so difficult as conjectured by the author, because we can extract from them many new laws or regularities, some of them can be called “higher-order”. For example, profitable opportunities exist in very complicated and uncertain ways, an economist cannot precisely identify them, but, the proposition that “profitable opportunities exist somewhere” is very useful and encouraging to practitioners, whereas the mainstream denies them definitely. For another example, the economy is hard by a government to manage precisely, but, if we reveal that knowledge development, from the perspective of Combinatorial Explosions, will generally and roughly keep going on, the government will be relieved and laissez-faire would reasonably be one of the primary polices.

    Complexities can be dealt with at least in the following ways: 1. A wholesome, condensed but vague group of principles, expressed verbally with traditional genres; 2. Applied various models, not only mathematical, and extracted from empirical observation of the real world as the “theoretical prototype”, depicting multiple regularities; 3. Computerized and evolutionary simulation with huge systems and even global cooperation, as the new embracive “formal research”. Please notice that “AlphaGo” can exercise millions of times to study the strategies during the nights of game days, this is why it defeated human players!

  8. March 28, 2020 at 1:00 pm

    Says David Collander: “Thus, the complexity vision’s scientific research agenda is consistent with a vigorous and highly abstract theoretical and empirical research agenda that, if anything, because its focus on complex dynamics, is even more mathematically and statistically complex than the current research agenda associated with the equilibrium vision. In that sense the complexity methodology is quite different from the critical realist methodology espoused by heterodox critics of economics such as Tony Lawson.”

    Yes, but. Why is it different? I disagree with the complexity researcher’s vision not for its insightful mathematics but because it is trying to classify economic phenomena in terms of mathematical ones. I broadly agree with Tony Lawson’s position because he, like me, is arguing that the type of mathematics needed should be chosen from the available types (seen in examples of them) to reflect the observable economic phenomena.

    Tony initially, however (in “Economics and Reality”), focussed on the inconsistency between mathematical models devoid of economic reality, and econometrics devoid of understanding of numerical complexity. His later focus on comparison (“Reorienting Economics”) has moved him towards Nature’s way of realising equilibrium by “equalising”. We largely agree that the root problem is Hume’s unwise “philosophy” of science, though as a practical scientist I’ve gone beyond Bhaskar’s “Realist Theory” to his “Dialectic”, with its useful mnemonics DREIC and RRREIC distinguishing fundamental from applied science. Cooperation between us has sadly not developed because I’ve not been able to explain satisfactorily to him the significance of the types of mathematics I and not he are familiar with due his not having worked with electronics, computers and information systems. Put bluntly, mathematics includes multi-dimensional geometry as well as log/linear quantitative arithmetic, and topology (which deals with the order – as in causality – and number of circuits/circulation rather than the magnitude of numbers). What is known as Complexity Theory is using arithmetical language to express the dimensional geometry of repetitive algorithms. In Tony Lawson’s economic reality it can best be seen and understood visually rather than symbolically: as topological circuits within which power and information feedbacks can both circulate in reality and be imagined circulating. He and Geoff Harcourt gave me an opportunity to explain that to them 18 years ago, but sadly I didn’t do so very well. Public speaking is not my forte!

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