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Some elements for a definition of an evolutionary efficiency criterion


Together with the concepts of equilibrium, scarcity, choosing, etc., efficiency is at the core of economics. However, in an evolutionary context, efficiency raises several issues concerning to rationality, the complex evolving nature of the economy, economic change as the fundamental economic problem, and the role of expectations —that link purposeful action to actual action. The main goal of this paper is to provide some necessary elements to accommodate an efficiency criterion within an evolutionary theory of the production of action. In a nutshell, an evolving complex system could be considered as being (or “becoming”) efficient if the agents’ intentions could “materialize” in actions that would give rise to real states of affairs which, essentially, were compatible (even similar; never identical of course) with what it was expected (ex-ante) when the action “plans” were elaborated and selected. We set out this criterion as a micro-criterion and then we explore an extension of it at a systemic level using the theory of meso-level connections.

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Fig. 1


  1. 1.

    Important formal developments are Arrow (1951), Arrow and Debreu (1954) and Debreu (1959). An interesting extension is Allais’ principle of efficacité maximal (Allais 1989, §114). This principle refers also to the minimization of waste (perte)—as in van Staveren (2012: 119)—however, obviously, with reference to the agents’ preference indexes, and not to the mere use of resources. Moreover, Allais (1989, §424) also points out that the Pareto criterion incurs at least in a couple of mistakes.

  2. 2.

    As shown below, in our approach, we analytically separate the allocative operation from the constitution of action plans for the sake of simplicity. This separation is important because the allocative operation itself is not likely to accommodate an explanation of the formation of plans since both means and ends should be analytically given (see Loasby 2003) when the selection of plans takes place.

  3. 3.

    This may include “preference learning” (Schubert 2013: 246) and “learning to consume” (Witt 2001).

  4. 4.

    Although authors such as Lane et al. (1996) have recognized the importance of action beyond mere choice to understand economic processes in the evolutionary context, developments in evolutionary economics usually do not go beyond such statements.

  5. 5.

    See, for example, Ascombe (1957), Searle (1983), Bratman (1987 [1999]), Malle et al. (2001), and, from the point of view of neuroscience, Fuster (2008).

  6. 6.

    For a discussion, see Vanberg (2014).

  7. 7.

    For an action to be rational, it must be intentional (Muñoz et al. 2011), i.e.: pursue ends (Nelson 2017).

  8. 8.

    Within the Austrian paradigm, a related but more limited concept that is linked to the logic of the entrepreneurial function is dynamic efficiency (Huerta de Soto 2012).

  9. 9.

    For simplicity, we assume here that agents select only one plan at each instant of time. Obviously, this is only true in the case of alternative and exclusive plans: I cannot be in Paris and Melbourne at the same time. However, in general, it is possible to deploy two or more plans at the same time: I can run and listen to music if I have an iPod.

  10. 10.

    The “design” or formation of each personal action plan depends on the personal characteristics of the person: his internal structure of beliefs, attitudes, values and its representations of reality that constitute a set of elements that define what a person perceives as existing, based on what he knows, feels and wants. Rubio de Urquía (2005) has referred to this structure as the personal ensemble. The personal ensemble is a fundamental element for the formation of the bundle of action plans, although it does not fully determine it. The personal ensemble is caused by the dynamics of deployment of the person (his “biography”), especially his ethical and cognitive (both personal) dynamics and the cultural dynamics in which the person develops his existence. Similar notions are mental models (Denzau and North 1994), space of representations (Loasby 1999), theories (Schütz 1951), etc.

  11. 11.

    Schütz (1951: 166-169) speaks of practicability. In what follows, it is important to point out that projecting — and selecting — a course of action is different from mere fancying. “Projecting of performances (…) is a motivated phantasying, motivated namely by the anticipated supervening intention to carry out the project.” (Ibid. p. 165).

  12. 12.

    Consistency is a necessary condition for the feasibility of the plans because consistency enables effective feasibility ex post. For a formal proof, see Encinar (2002).

  13. 13.

    It could be the case that compensating errors may lead to plan completion even though it is based on false assumptions. However, completion of everyone’s plans is not evidence of Pareto efficiency. For example Rizzo (1990) explains how, for Hayek, agents could be in individual equilibria because they do not discover any evidence that would cause them to change their plans, even though those plans are not optimal. They can be in equilibria even though there are unexploited gains from trade that are ignored. Kirzner (1973: 215-218) proposes an example in which buyers in one part of the market are ignorant of sellers in another part of the market who would sell at lower prices. The buyers buy at high prices (their expectations are met) but they would clearly regret those transactions if they knew about the other sellers who sell at lower prices. There might be nothing in the course of events that would cause them to discover what they are ignorant of and their projected goals of action are realized even though the system is not “efficient” in a Pareto sense. That is, Kirzner equates full coordination with Pareto efficiency; however, Hayek allows for agents and the system to settle into an equilibrium that is not Pareto optimal. Additionally, for Hayek, to talk about equilibrium requires the passage of time and human action — it is not static and atemporal.

  14. 14.

    Unlike the neoclassical version, our approach does not take action as an isolated unit: each agent knows that his fellow social actors are guided by anonymous typifications of other actors –a knowledge that gives each agent an incentive to fit his own actions into the stereotyped patterns expected by others — and other agents must understand the agent if his/her actions are to succeed or have, at least, an objective probability of success (Koppl 2002, p.113). Additionally, our approach allows conflict to play a role. Conflicts of goals and/or actions are a source of unfeasibility with which agents have to deal. This is a very important issue that we cannot elaborate here due to lack of space.

  15. 15.

    Defined in a negative sense as a decrease in the degree of the unfeasibility of agents’ action plans. Hayek (1978) stressed the importance of coordination in his discussion on the empirical tendencies toward equilibrium: he characterized it “by a maximum compatibility of plans and dissemination of knowledge, subject to the adaptation to constant change in system’s external data” (Rizzo 1990: 16).

  16. 16.

    Soros (2013) proposes a concept of reflexivity-related uncertainty principle. His concept is linked, on the one hand, to what he meant by cognitive function (understanding the world in which the agent lives) and, on the other, to what is called the manipulative function (which concerns the action of the agent with reality and therefore is linked to intent, according to the author). The two functions connect the subjective reality perceived (or designed) with the real state of things or objective reality. Both functions are fallible (in the sense that the calculations/perceptions of the agent who makes them can fail). According to Soros, the set of roles indicated along with fallibility and intentionality form a reflective system. An extension is Beinhocker (2013).

  17. 17.

    Koppl (2002: 107) points out that ignorance of the future discourages agents’ action aimed at the future. Thus, agents plan only where the inner zones of relevancy — that is, the field of action or part of the world the agents think they can control at least in some degree, and the milieu of action or other fields of action not open to agents’ immediate domination but mediately connected with the field of action (Schütz, 1946: 124–125) — give them enough subjective predictability to expect the desired result with the required degree of confidence. On the other hand, agents plan for the foreseeable future, and the very concept of expectations contains within it the notion of the predictability of the future. This notion of predictability is a pragmatic and subjective one (not a philosophical one) and pragmatic judgment may be mistaken. Koppl (2002) has also noted a similarity between Keynes (1936) and Schütz’s (1951) discussions of conventions. Davis (2017b), also on Keynes’ philosophical thinking, connects reflexivity, complexity and uncertainty. On the role of expectations in a radical uncertainty environment, see Shackle (1955), esp. Part I, and Shackle (1972).

  18. 18.

    “[O]ur expectations about events we do control (…) is our knowledge of the field of action. This knowledge exists in the form of plans we might carry out. The field of action is filled, therefore, with hypothetical propositions. ‘If I do this, that follows.’ The point of our plans is precisely to change events, to move them from the path they would otherwise take.” (Koppl 2002: 107)

  19. 19.

    The emergence of novelties produce disequilibrium. As we have shown elsewhere, novelty depends on the intentionality of agents. The very fact that an unexpected event arises from the interaction of intentional dynamics does not eliminate the fact that its origin is intentional (Muñoz and Encinar 2014a: 332).

  20. 20.

    Divergence between the expected and that that is actually obtained, on the other hand, is the result that is expected more frequently in genuine dynamic processes. See Antonelli (2011) on “out-of-equilibrium dynamics”.

  21. 21.

    Expectations are conjectures about the future. An action plan is, in fact, an expectation, a genuine conjecture (an experiment) in a Popperian sense.

  22. 22.

    How effective is not real in the sense of the external, something that is there, if that is not what the agent perceives as real as a result of its plan of action in interaction.

  23. 23.

    As if it were a search process in the sense of Kirzner (1992).

  24. 24.

    For this expectation to generate action, it must not be a mere mental state (a pure expression of desire) but should articulate and make sense of the projective space of action.

  25. 25.

    Expectations affect the constitution of spaces of action of the agents.

  26. 26.

    We are assuming that, to some extent, agents can interpret and find out why their plans failed. However, we are aware that the Duhem-Quine thesis would suggest that it can be very hard to know why a plan failed within a complex system − because of the initial conditions versus the general hypothesis vs the implementation of the plan or market test or even measurement errors.

  27. 27.

    New connections or new combinations that are at the basis of entrepreneurship (Earl 2003).

  28. 28.

    An interesting example is Sarewitz and Nelson (2008), who propose the so-called “Sarewitz-Nelson rules”, a certain dynamic negative efficiency criterion applied to the selection of technological trajectories (in particular, three rules to rule out, a priori, the lack of promising technological paths). Almudi et al. (2016) criticize, formalize and extend these types of rules.

  29. 29.

    The formal proposal in Almudi et al. (2016) makes it possible to detect blockages and barriers that may stop (or at least slow-down to the limit) the learning co-evolutionary processes taking place between “practice” and “understanding”. This blockage of co-evolution may eliminate domain-specific possibilities for learning, which might erode (e.g.) technological advance. Accordingly, this would be the case if the “enlightening testability rule” were not verified at a sufficiently high level in certain cases; or even if the “standardized technical core rule” were not verified in certain domains.

  30. 30.

    See Dopfer (2012) for a discussion of the concept of meso.

  31. 31.

    An organization, company, industry, economic sector and, ultimately, the entire economy.

  32. 32.

    At this point we make abstraction of the institutional setting. Of course, different social arrangements have consequences in terms of coordination −to the extent that a social arrangement can be judged economically better than another if it generates faster mutual discovery processes and more extensive meshing of plans (Harper 2013: 63). In particular, revisiting Kirzner’s work, Harper (2013) stresses the role of the system of property rights of a society to have a better understanding of the logic of economic coordination.

  33. 33.

    A limit case, however in a static or atemporal context!, is the Walrasian GE, where all plans (of consumption and production) are mutually compatible a priori. However, in true dynamic processes, the common situation is the presence of goal conflicts. Muñoz and Encinar (2014b) and Kallerud (2011) provide some examples.

  34. 34.

    Two examples of this are the Keynesian entrepreneur of the General Theory (Keynes 1936) and the economics of rationing (Malinvaud 1977; Benassy 1986).


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We would like to thank two anonymous referees, the editor of the JEEC, and attendants at the Colloquium on Market Institutions and Economic Processes at NYU (especially, prof. Israel M. Kirzner, Mario Rizzo and David Harper) for their very helpful comments and suggestions. The usual disclaimer applies.

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Muñoz, FF., Encinar, MI. Some elements for a definition of an evolutionary efficiency criterion. J Evol Econ 29, 919–937 (2019).

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  • Evolutionary efficiency
  • Action plans
  • Reflexivity
  • Expectations


  • B40
  • B52
  • D69
  • D84