A) As evolutionary-NeoSchumpeterians (or complexity-oriented) economists, we conceive the economy as a dynamic system in which scattered heterogeneous and boundedly-rational agents interact. Local and global interactions involving feedbacks and domain-specific connections involve producing, investing, consuming, distributing incomes, trading in general, learning, innovating, entry/exit, etc. And the ongoing development of the specifc dynamics we propose to explore a problem generate "EMERGENT PROPERTIES".
B) The methodologies we use range from verbal logical arguments (which of course can be genuinely complex) to complex ABMs, passing through non-linear highly stylized models, replicator dynamics and evolving complex networks with the afore-mentioned components.
C)The specific methodology used is not innocous. Thus, whereas verbal arguments involving real complexity are often almost inestricable, ABMs are a bit more enlightening (the less so the higher the scale), and, in my opinion, the subset of low-scale ABMs, enriched-replicator dynamics, networks and non-linear styled complex models are the best. They often even allow for closed-form quasi-exhaustive analysis.
D) The problem is how should we pass from the results we obtain in our theory, to the posing of policy recommendations to be implemented within a reality which we perceive as emerging from a complex system?
Notice that there are two sources of complexity (2 complex realms involved):
1)The inherent complexity of the real system under scrutiny.
2)The often black-boxed complexity of the theory we propose.
We know that even small differences between two evolving complex systems can make a huge difference in their outcomes. If we assume (as we should) that we can never access the "real complex mechanism underlying reality" (just we should aspire to approach it, at least in social sciences), we should be very prudent in our policy prescriptions.
E) The solution prescribed by those using simple models (mainstream economic models or simple statistical models) is not valid, since they begin by assuming that reality is SIMPLE (instead of complex), and they falsely avoid the problem. Why should social reality be simple in its functioning? The historical record of crisis and social distorsions, and the analogies with natural systems point out to a clear failure of the standard approach. Thus, if we accept complexity:
How do you address the issue of double complextity 1) and 2)?
I agree with Francisco. I feel vertigo when, after correctly arguing about the inherent complexity if real economic systems, some advisors come up with a COMPLEX (often black-boxed) large scale computer ABM, just try to "calibrate it" through often just preliminary behavioral experiments or a few statistical partial fits, and then (after "testing" the plausibility of the giant ABM according to the -somehow observable COMPLEX- reality) they move to recomend very precise policy actions. I also think that we still have to ponder much deeper regarding the nature and role of complex economic science within a truly essentially complex world (complexity in the sense of e.g. The Santa FE Institute, USA).
Beating complexity (1) with more complexity (2) is the dominant way of battling and combining complex economic practice with scientific economic theories. My economic point of view is that complex problems (1) can find simple solutions (2), e.g. identifying the single working elements of systemic comlexity as dynamic economic 'Gestalt' (4th order cybernetics). I do think that we can only communicate with economic complexity in a scientific manner and that any 'control or command' thought (approach) leads to 'paper tigers' (advanced and perfected scientific artifacts).
In this sense, I try to see the complexity of human economic action in the scientific framework of sociophysics (social science economics), i.e. economic science as a 'list' of true statements about complex reality.
I cannot under stand what Francisco Fatas-Villafranca means by two realms of complexity. Would you explain in more detail (2) the second realm of complexity?
---Yes: underlying neo-classical / neo-keynesian mechanistic approaches from economic theory to economic reality (i.e. linear or locally linearizable deterministic models which are assumed to be useful tools to understand reality, or essentially stationary stochastic processes often linear or linearizable, or even more general models but with a simple topological structure -Arrow Debreu) we find the PRECONCEPTION that reality works on the basis of relatively SIMPLE (although unknown) mechanisms. Decartes, Newton, Laplace..Walras, Marshall, Hicks, Samuelson..Lucas, Sargent, ..
---From the complexity/evolutionary field we claim and build up models which are Complex adaptive systems because we believe that reality is ontologically or essentially COMPLEX.
---Then, if we assume the complexity approach and we come up with complex MODELS to study a complex REALITY, we must be conscious that both our models, and reality itself, may be highly highly sensitive to introducing new mechanisms, policy interferences, etc. Since our complex models never EVER can be a isomorphism of the complex reality they try to understand, we have a specially problematic situation, since not only what we have in our hands or computers as models, but also the real mechanisms at work are COMPLEX, always different and highly sensitive to discrepancies.
--When I Have had the need to advise or trying to monitor or guide policy in real complex situations, with a theoretical system which is also complex and never isomorphic ti reality, i have been always very concerned with the best way to propose and apply policies and interventions.
---My point is that, whereas mainstream advisors just ignore this situation and carry out interventions very often with catatrophic consequences (guided by simple models to approach a reality which is essentially complex),, we are conscious of the need of complex models for a complex reality, BUT still we face the terrible challenge of the discrepancy between our complex schemes, and a complex and highly complex reality.
---I feel the need to intervene on reality because otherwise it is essentially unstable. But I am not sure regarding the best use we can do of our complex models to guide policy actions. I think that many economists (even complexity ones) are just recommending actions too happily!! A but unconsciously!!, because they rule out (or prefer to ignore) this problem of no isomorphism between 2 realms of complexity (our conplex models or mental maps, and the complexity of the external world that we try to control). In fact, I have felt in my experience that the inmense advance we have reached with the COMPLEXITY approach to science and reality, has eroded or even destroyed the Popper's approach to theory discrimination/falsationism.
---The complexity approach should lead us to rethink the science-reality relation. Popper, Khun, Lakatos etc are just relevant if our preconception is that reality is essentially simple, structurally stable..What do you think?
I agree with Francisco. I feel vertigo when, after correctly arguing about the inherent complexity if real economic systems, some advisors come up with a COMPLEX (often black-boxed) large scale computer ABM, just try to "calibrate it" through often just preliminary behavioral experiments or a few statistical partial fits, and then (after "testing" the plausibility of the giant ABM according to the -somehow observable COMPLEX- reality) they move to recomend very precise policy actions. I also think that we still have to ponder much deeper regarding the nature and role of complex economic science within a truly essentially complex world (complexity in the sense of e.g. The Santa FE Institute, USA).
Exactly! I was thinking precisely on the advisory role of complexity economists coming from Santa Fe. I wonder whether they take into consideration the no-isomorphism between complex models and complex reality, and the prudency plus that this fact demands..
Surely this is an extremely interesting and important theme, but I have no enough time today to discuss the points in detail. The following are just my impressions I felt when reading Francisco Fatas-Villafranca and Isabel Almudi 's commnets:
(1) It may not very wise to consider at the same time policy advisers' misconducts and epistemological questions of complex systems and complexity. I understand that you have actual problems on this points, but I feels that epistemology must precede good policy recommendation question.
(2) Fransisco thinks of two realms. I wonder if this is a good framework when we examine complex systems and behaviors in a complex system. I have been thinking that we should better distinguish three "realms" (?) of complexity:
(a) complexity of an objective system (e.g. national or world economy)
(b) behavior of humans in a complex situation (.e.g. how we behave in a complex world.What does the complexity means for us, human beings? )
(c) theory or models of complex systems (e.g. economics and economic of complexity in particular)
(3) Simple rules or behaviors may engender complex processes.
See for example Ronald A. Heiner (1983) The Origin of Predictable Behavior. The American Economic Review 73(4): 560-595.
(4) My general impression vis-à-vis Santa Fe Institute is that they lack a good theory of human or animal behaviors. Fransisco and Isabel may be right when they claim that they are considering too simply the correspondence between real economy and their models. ABM or ABS must be used mainly to understand the working of complex systems, but we should refrain at least at the actual stage of our discipline from using them as means of predictions. Direct application of their simulations is extremely misleading when we do not understand the real process and characteristics of the real system. ABS is a necessary and hopeful mean of economics research but we should also keep in mind that it is still in a embryonic prematured stage.
See my paper: A Guided Tour of the Backside of Agent-Based Simulation.
Sensible policy making should not be carried out without a theoretical system supporting government action. The same can be said regarding action in general. This is one of my strong disagreements with behavioral economics (which is not Simonesque-bounded rationality!!!) and cyborg-computational super-ABMs coming from statistical physics (which often end up in black-boxed computational/statistical exeercises).
Still, I believe that detecting blockages and catalyzers in real phenomena (analyzed from a complexity perspective), and carrying out prudent domain-specific policy actions to be monitored as time goes by, is a strong point of the evolutionary economic approach to policy (see e.g. paper attached on catalyzers, blockages, and how to deal with them in a potentially fruitfull manner).
I would go even a bit further: relative pro-active policies targeting key mechanisms of the analytical evolutionary process under scrutiny (calculating elasticities on sets of runs arising from simple -instead of giant- evolutionary models, and performing local and global sensitivity analysis) is possible. An example of the evolutionary approach to the theory of economic development is attached to this comment.
I don't care how many kinds of complexity are involved, there is a simple way to get rid of them, which is often used by engineers and physicists. It is simply consider the aggregate or average properties of the fewer number of structural situations being examined. In the case of our social system of macroeconomics, the ease for doing this is by asking the necessary question of about how many different kinds of business transaction or exchange are being involved in the Big Picture.
The emphasis is on the word "kinds" because there are many participants and their separate interrelationships are complex, but which can all have a small number of common kinds of business deals. (In every case money is being returned for whatever types of goods, services, valuable documents, access rights, tax demands, etc.) My (attached) analysis in SSRN 2865571 "Einstein's Criterion Applied to Logical Macroeconomics Modeling" shows that a total of only 19 different kinds of these exchanges are required for the whole of our national economy, and that they pass between only 6 different types of entities or agencies. I find that rather than having to meet the complexities head on, one can get around them, if one looks at the situation in a more general way.
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