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Meso comes to markets: Comment on ‘Markets come to bits’
Journal of Economic Behavior & Organization Vol. 63 (2007) 307–312
Discussion
Meso comes to markets: Comment on ‘Markets come to bits’ Jason Potts ∗ , Kate Morrison 1 School of Economics, University of Queensland, Queensland Q4072, Australia Available online 17 January 2007
Mirowski’s research programme of markomata formally sets out to model ‘the diversity of market forms by making use of the mathematical theory of automata, and then to taxonomize and organize these entities by means of a theory of evolution’ (Mirowski, this issue). This suggests a new sort of economics in which it is markets that evolve not people, systems that evolve not agents, prosthesis that evolve not preferences, and rules that evolve not information. Economies evolve; people do not. This proposition is both obvious and true, making it an excellent foundation for an evolutionary social science. So, if we are to take Mirowski’s program seriously as a general framework for economic analysis, which we think we certainly should, then it is important to recognize that although Mirowski’s unified rubric of markomata elides agency and is instead based upon John von Neumann’s theory of automata as a model for the study of social institutions, the separate lines of research into markets as computational entities are all still very much but a microeconomics. Markomata is a theory of the core microeconomic building blocks of an economic system as well as a theory of their evolutionary principles (i.e. a microeconomics) but it is not yet a theory of the whole economy. Yet, it is our view that Mirowski’s markomata program can indeed be the basis for such a general theory when analytically expounded in terms of the new evolutionary economic framework of micro meso macro (Dopfer et al., 2004; Dopfer, 2005) in which market automata (Mirowski and Somefun, 1998; Potts, 2001) are abstracted as a special, central instance of generic meso rules (Dopfer and Potts, 2004). Which is to suggest that the Mirowski framework of markomata can be yet further developed. As in Machine Dreams (2002), Mirowski is at pains here to present carefully the ‘figure/ground reversal’ in which ‘it is markets that evolve in an ecology of human beings, rather than the other way around’ (Mirowski, this issue). But in making the shift from man to machine, from the ∗ 1
Corresponding author. Tel.: +61 7 3365 6562; fax: +61 7 3365 7299. E-mail addresses: [email protected] (J. Potts), [email protected] (K. Morrison). Tel.: +61 7 3848 2624; fax: +61 7 3365 7299.
0167-2681/$ – see front matter © 2007 Published by Elsevier B.V. doi:10.1016/j.jebo.2005.12.014
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agent as the locus of theory to the rule or automata, Mirowski is less clear about how this new microfoundation relates to a broader macro analysis of the whole economic system, nor indeed whether such ambition for a computational theory of long-run economic growth or development is even reasonable for an evolutionary computational economics. How far can we legitimately analytically extend the computational theory of markets under the cover of evolution? This is the Hayek question writ large, namely how does a market order emerge, which in the micro meso macro framework reduces to the question of how a macro order self-organizes from a meso trajectory of micro rules. Mirowski’s case that economics is becoming and should be a science of markets (i.e. rules) not of man (i.e. choice) is a persuasive analytic expression of the idea that economic evolution is a growth of knowledge process. It is, moreover, something that Smith (1776) and Marshall (1994) might well have recognized. So, let us suppose we can make that leap to an ontologically robust and empirically rich computational taxonomy of market forms that ultimately reduces to the diverse rules of markets rather than the preferences or rationality of agents, and that all of this can pass as a new evolutionary computational microeconomics. The question is then, what is next? Mirowski provides some clues about this, in particular suggesting how computational theory can furnish a number of lemmas or principles that constrain what is evolutionary possible at the macroeconomic level. For example, the impossibility of a Turing-equivalent market or of complete arbitrage means that the aggregation of markomata is not a ‘super-market’, but must be a complex, diverse and historically dependent ecology of connected markomata. The upshot is that although Mirowski’s computational conception of markets furnishes a powerful and expedient system of microfoundations for evolutionary economics, the transition to a macro view of an evolving market economy does not, and cannot, involve more of the same. The aggregation of automata is not a bigger automata, but rather the arrival of emergent complex self-organizing economic systems (see Potts, 2000; Foster, 1997, 2005; Foster and Potts, 2006). Mirowski is right that markets are the centre of economic analysis, that markets are computational in nature, and that markets evolving makes for an evolutionary computational microeconomics, but he is wrong to suppose that the story ends there. From micro computation we build meso structure, and from meso structure we build macro order, and this is how economic systems evolve. Mirowski criticizes Hayek for his seeming oblivion of the idea that markets differ in computational composition and, moreover, that these differences may then have systematic consequences for the operational array of prices and activities. That is certainly a fair comment, as is the critique of modern evolutionary economics as that in which everything evolves except markets (Mirowski, this issue). In a similar spirit, Loasby (1999, p. 112) has argued that ‘markets are much too important, and much too amenable to economic analysis, to be treated as primitives’. So Mirowski is right to point out that evolutionary economists have, by and large, failed to notice that markets exhibit emergent or spontaneous differences and so, as with anything with variation under selection, that markets too may evolve (although see Vanberg, 1994; Loasby, 2000; Potts, 2001; McMillan, 2002; Morrison, 2004). Yet Hayek’s (1976, p. 109) notion of a catallaxy as a special kind of spontaneous order ‘brought about by the mutual adjustment of many individual economies in a market’ [italics added] is intended to emphasize not the computational microstructure of how markets work, but rather the nature of the resultant emergent order. Hayek’s catallaxy is the macro order that Mirowski proposes can be described with the micro theory of markomata. But no such connection can be directly made, for Mirowski’s markomata is an order of rules that combines with other generic orders of rules to form the macro system. Market rules are abstractly necessary but not generally sufficient to describe the evolution of the economic system. The same is true of the Institutional and Schumpeterian evolutionary economists, who are mostly concerned with the
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macro patterns of change in economic activities (as one activity or technology displaces another, etc.) and less so with the detail of coordination along the way. We suggest, then, that we can use the micro meso macro (hereafter mmm) framework (Dopfer and Potts, 2007) to connect markomata to the macro order by viewing markets themselves as meso. Space does not permit a detailed introduction of mmm, but the core idea is relatively straight-forward. In mmm, an economic system is conceptualized as being made of generic rules that allow carriers to perform operations (Dopfer and Potts, 2004). A rule and its population of carriers is a meso unit, the macroeconomic system is a complex system of connected meso units, and economic evolution is the process of change in meso units, either through novel generic rules being introduced into the economic system or through a change in the population of each meso rule. Evolutionary macroeconomics is the study of how the entire systems of meso are coordinated and how they change. Evolutionary mesoeconomics is concerned with the structure and population of each generic rule, and evolutionary microeconomics is the study of the individual processes of adoption by a carrier (such as an agent) of the rule. This framework is intended to capture the idea of economic evolution as a process of endogenous transformation of the economic order through the origination, adoption and retention of new economic ideas, or generic rules, that may variously manifest as behaviours, organizing rules or technologies. It is entirely within the ambit of the mmm framework to treat market rules themselves as generic rules, and this is surely the apposite place to start. So let us leave technological change to the technology scholars and cognition and human decision theory to the psychologists, for Mirowksi’s proposition does indeed center a new empirically warranted microeconomics from which we may generalize, via the mmm framework, to allow a strong claim to be staked for a new economics, complete and proper. There are three aspects to this analytical integration. First, the meso domain adds precision to markomata theory by providing a clear distinction between heterogeneity of market forms and variation in their relative prevalence and stability. In evolutionary mesoeconomics, a generic rule is understood with respect to three prime dimensions: its analytical separability from other rules (a continuous double auction is undeniably different to a posted-price markomata), the size of its population (how ‘big’ a part of the economic system is this rule?), and its relative stability in terms of the three-phase meso trajectory (i.e. is the generic market rule still in the origination stages, is it undergoing rapid adoption and/or adaptation, or is it stable and completely embedded within the economic system?). This meso view, that each type of market rule possesses its own population and trajectory, brings immediate clarity to several of Mirowski’s less-central but nonetheless intriguing remarks. Two are worth noting. His almost casual observation (Mirowski, this issue) of the relative ubiquity of posted-price markomata compared to other more computationally complex market forms can now be understood both as a statement about relative population sizes and with respect to evolutionary dynamics; using mesoeconomics, the analyst can understand not only current relative frequencies but how they are likely to change as the respective meso trajectories unfold. While making no standard claims to predictive power, the addition of the meso trajectory concept to the markomata analytical toolbox is crucial to any hope that a new computational evolutionary economics may provide insight into the future shape and nature of market-based systems. Similarly, it is the meso trajectory, as the core dynamical unit of economic analysis, that lends power to Mirowski’s call for a ‘natural history of markets’ (Mirowski, this issue). A retrospective account of the market forms that have shaped economic evolution over historical time is made possible with the recognition that markomata, while central to economic analysis, are, like all meso, subject to the evolutionary dynamics of origination, adoption and retention (or early death). Markomata theory allows a fresh view of the economy as a market system, but it requires the dynamical context of the meso
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trajectory to allow the past and future of the market system to be properly analyzed and, perhaps, understood. The second way in which mmm may usefully generalize Mirowski’s proposition is via a fuller microspecification of markomata rules and where and how they are carried. As Mirowski himself notes, one of the dimensions along which markets differ is the degree to which they require knowledge or know-how on the part of individual users; for example, specialist training is a precondition for effective trading in the CDA-based exchanges, while a child can purchase a newspaper at the local store. Some markets, such as broker-mediated real-estate markets, rely on written and enforceable codes of conduct; others presume specific knowledge of time, place and unwritten but knowable rules for bidding (such as perishable-goods auctions, e.g. Weisbuch et al., 2000 on the Marseilles fish market); and in some markets a pre-requisite for participation is access to and ability to operate a web-connected computer (e.g. eBay). Clearly, any markomata is decomposable into a set of rules that are variously behavioural, social or technological; furthermore, the computational capacity of any market relies on rules carried by some convex combination of individual, group and machine as an allocation of complexity (Clark et al., 2004). It is here that the mmm framework can add further analytical precision to Mirowski’s conception of markets, via the rule taxonomy (Dopfer, 2005) that underpins the micro domain of micro meso macro. This schema allows a conceptual organization of rule types and the ways in which they are carried. The rule taxonomy parsimoniously distinguishes four types of rule (cognitive, behavioural, social/organizational and technological) and two classes of carrier: subject (i.e. the human individual) and object (i.e. physical artifacts). It establishes a partial correspondence between rule type and class of carrier, whereby organizational and technological rules are carried by objects, and cognitive and behavioural rules are carried by subjects. Hence, the rule taxonomy offers an alternative, and we suggest strongly complementary, method for the decomposition and thus classification of heterogeneous market forms. Along with analytic precision, this micro-taxonomic approach offers a particular advantage to markomata theory: it provides Mirowski’s proposition with a strong answer to those concerned with the question of robust microfoundations by allowing the vexed question of human agency to be treated in a purely positive, empirically determined way. The task of the microeconomist, in this view, is no more and no less than one of classification: of the complete set of rules that comprise a particular markomata; of the typology of such with respect to their behavioural, social/organizational or technological content; and of the class of carrier associated with the operational execution of each rule in the set. Though not required by the mmm analytical framework, it should be noted that this conceptual approach is perfectly amenable to object-oriented (OO) modeling techniques, in the sense that it seeks to define rules (in OO terminology, an object) in terms of their type (a property) and by the relevant class of carrier (a method). Furthermore, microdynamics are inherent: the mmm framework, being fundamentally scale-free, utilizes the trajectory concept to describe the process by which individual agents may originate, adopt, adapt, retain (and, of course, discard) economic rules. This again suggests a modeling domain of much potential as the mechanisms by which new rules are diffused within a population of autonomous individuals, and the outcomes of such processes are familiar conceptual territory for practitioners of endogenous network formation, agent-based modeling and evolutionary game theory. Modeling questions aside, however, it is clear that a more robust and complete microspecification for markomata theory can be achieved via its integration with the mmm framework: the rule taxonomy facilitates a more precise and honest unpacking of the rules that comprise any given markomata. The strength of the approach, and the reason it should be used to extend the microfoundations of Mirowski’s proposition, is that it also (and non-trivially) allows methodological individualism to be upheld without compromising the potential applica-
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tion of established modeling techniques. This is important if we seek to attain the basic properties required of a useful, realistic and feasible economics; these being, necessarily and sufficiently, empirical warrant, analytical rigour and methodological pragmatism. There is a yet stronger imperative to integrate mmm with markomata theory, and moreover one that furthers the case made so far that what Mirowski is doing is furnishing a whole new conception of economics, namely the implications this may have for macroeconomic analysis, an area even more fraught (and inseparably so) than the question of human agency. Mirowski never explicitly considers the relation of markomata to macroeconomics, so it is unclear whether this is because he regards the extension as imponderable, insidious or just non-computational. Instead of a macro perspective, Mirowski offers a theory of markomata networks, including the hypothesis that the topology of connected markomata is likely to exhibit small-world properties in the connections between markets (and we might also suggest that there are also likely to be hubs in the distribution, such that some markets are much more heavily connected than others, making it scale-free, and also that the distribution of markomata types along an axis of complexity is likely to be described by a power-law). Yet an ecology of markets is not yet a macroeconomic system, and this is where mmm can provide some guidance on how markomata might underpin a new ‘computational’ approach to evolutionary macro analysis. Mirowski’s program is certainly macroscopic in that it seeks to encompass the study of all markets as a single connected web, yet it is equally clearly not what is normally meant by macro as an aggregation of expenditure or supply functions (or the study of aggregate phenomena such as inflation, unemployment or output). The analytic sense of a large number of automata or institutions all fitting together in a complex way is perhaps more closely related to the erstwhile discipline of political economy, which sought to understand how the whole economy functions through the interaction of all institutions as based around the market. Mirowski’s macro is perhaps best then understood as computational political economy, and the mmm framework can provide some structure for this. The macro domain of mmm analysis is about how all of the meso fit together, both at the deep level of how generic rules themselves fit together and also at the surface level of how rule populations fit together. This process of fitting together is a self-organizing process of coordination of meso rules to each other through changes in connections and in populations. The implication, then, is that we may think of an economy as a complex system of markomata forming a perhaps global connected web (a macromata perhaps, although Hayek preferred the term catallaxy) that is embedded within and structures the relation between all other generic rules (or meso). Among other things, this would add significant force to the sources of variety in the evolution of markomata as the effect of other generic rules and their changes also impacted on the way that rules are bent or got around to infuse the evolution of markomata, and also vice versa, as markomata evolution itself engenders change in the rules of other automata. A loaded metaphor is to think of the macromata as a kind of operating system (e.g. Friedman, 2000) for an economic system, a system that evolves through successive increases in computational power and connectivity that manifests in real changes in the macro pattern of economic activities. So, it seems to us that it might also be useful to think of the macroeconomic order as a connected system of market rules and the behavioural, social/organizational and technological rules that attend them. mmm allows us to view this system from two perspectives; in terms of the efficacy of connections between the generic rules themselves and in terms of the relative frequencies of rule populations; it also allows the sources of rule variety to be specified and the consequent re-ordering of the macro system to be systematically traced through. This macromata perspective scales up the analytic power of Mirowski’s framework by connecting it to a sharper conception of Hayek’s catallaxy that honors still the emergent and self-ordering nature of an only
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partially designed order. Much of markomata theory elides agency by locating it firmly instead in the designer of constructed markets. But a macro analysis can never do that, as the enormity of the failure of the 20th century’s experiments with centralized planning attest. Perhaps mechanism design has always harbored this ambition, and it is germane to note that Hayek (1945) warned against this on the computational grounds of essentially distributed knowledge. His point was that knowledge grows better and faster in parallel (see Loasby, 1999). So maybe a massively parallel view of markets and the non-market rules on which they depend and with which they interact, each with adapted computational capacity, is an expedient conceptual basis for an evolutionary computational macroeconomics. No one likes it when historians do theory, and worse yet is when they are right. But Mirowski’s markomata framework is eminently workable as a general analytical framework for economics. It has ontological and analytic foundations in the theory of computation and evolution, a taxonomic basis that is both logical and historical, and moreover it makes coherent a significant body of modern microeconomic analysis. It is a powerfully extensible approach that shows real promise for the formalization of economic change as a growth of computational capacity in a market system through the evolution of generic rules. References Clark, J., Morrison, K., Potts, J., 2004. The allocation of complexity. Working Paper. School of Economics, University of Queensland. Dopfer, K., 2005. Evolutionary economics: a theoretical framework. In: Dopfer, K. (Ed.), The Evolutionary Foundations of Economics. Cambridge University Press, Cambridge, pp. 3–55. Dopfer, K., Foster, J., Potts, J., 2004. Micro meso macro. Journal of Evolutionary Economics 14, 263–279. Dopfer, K., Potts, J., 2004. Evolutionary realism. Journal of Economic Methodology 11, 195–212. Dopfer, K., Potts, J., 2007. General Theory of Economic Evolution. Routledge, London. Foster, J., Potts, J., 2006. Complexity, evolution, and the structure of demand. In: Holmen, M., McKelvey, M. (Eds.), Flexibility and Stability in the Innovating Economy. Oxford University Press, Oxford, pp. 99–120. Foster, J., 2005. From simplistic to complex systems in economics. Cambridge Journal of Economics 29, 873–892. Foster, J., 1997. The analytical foundations of evolutionary economics: from biological analogy to self-organization. Structural Change and Economic Dynamics 8, 427–451. Friedman, T., 2000. The Lexus and the Olive Tree. Anchor Books, New York. Hayek, F., 1976. Law, Legislation and Liberty, vol. II. Routledge & Kegan Paul, London. Hayek, F., 1945. The use of knowledge in society. American Economic Review 35, 519–530. Loasby, B., 2000. Market institutions and economic evolution. Journal of Evolutionary Economics 10, 297–309. Loasby, B., 1999. Knowledge, Institutions and Evolution in Economics. Routledge, London. Marshall, A., 1994. Ye Machine. Research in the History of Economic Thought and Methodology, Archival Supplement 4. JAI Press, Greenwich, CT, pp. 116–132. McMillan, J., 2002. Reinventing the Bazaar: The Natural History of Markets. Norton, New York. Mirowski, P., 2002. Machine Dreams: How Economics Became a Cyborg Science. Cambridge University Press, Cambridge. Mirowski, P., Somefun, K., 1998. Markets as evolving computational entities. Journal of Evolutionary Economics 8, 329–356. Morrison, K., 2004. Asset Price Dynamics Under Networked Expectations. Unpublished mimeo. Potts, J., 2001. Knowledge and markets. Journal of Evolutionary Economics 11, 413–431. Potts, J., 2000. The New Evolutionary Microeconomics: Choice, Complexity and Adaptive Behaviour. Edward Elgar, Cheltenham. Smith, A., 1776. The Wealth of Nations (Cannan edition 1994). The Modern Library, New York. Vanberg, V., 1994. Rules and Choice in Economics. Routledge, London. Weisbuch, G., Kirman, A., Herreiner, D., 2000. Market organisation and trading relationships. Economic Journal 110, 411–436.
Discussion
Meso comes to markets: Comment on ‘Markets come to bits’ Jason Potts ∗ , Kate Morrison 1 School of Economics, University of Queensland, Queensland Q4072, Australia Available online 17 January 2007
Mirowski’s research programme of markomata formally sets out to model ‘the diversity of market forms by making use of the mathematical theory of automata, and then to taxonomize and organize these entities by means of a theory of evolution’ (Mirowski, this issue). This suggests a new sort of economics in which it is markets that evolve not people, systems that evolve not agents, prosthesis that evolve not preferences, and rules that evolve not information. Economies evolve; people do not. This proposition is both obvious and true, making it an excellent foundation for an evolutionary social science. So, if we are to take Mirowski’s program seriously as a general framework for economic analysis, which we think we certainly should, then it is important to recognize that although Mirowski’s unified rubric of markomata elides agency and is instead based upon John von Neumann’s theory of automata as a model for the study of social institutions, the separate lines of research into markets as computational entities are all still very much but a microeconomics. Markomata is a theory of the core microeconomic building blocks of an economic system as well as a theory of their evolutionary principles (i.e. a microeconomics) but it is not yet a theory of the whole economy. Yet, it is our view that Mirowski’s markomata program can indeed be the basis for such a general theory when analytically expounded in terms of the new evolutionary economic framework of micro meso macro (Dopfer et al., 2004; Dopfer, 2005) in which market automata (Mirowski and Somefun, 1998; Potts, 2001) are abstracted as a special, central instance of generic meso rules (Dopfer and Potts, 2004). Which is to suggest that the Mirowski framework of markomata can be yet further developed. As in Machine Dreams (2002), Mirowski is at pains here to present carefully the ‘figure/ground reversal’ in which ‘it is markets that evolve in an ecology of human beings, rather than the other way around’ (Mirowski, this issue). But in making the shift from man to machine, from the ∗ 1
Corresponding author. Tel.: +61 7 3365 6562; fax: +61 7 3365 7299. E-mail addresses: [email protected] (J. Potts), [email protected] (K. Morrison). Tel.: +61 7 3848 2624; fax: +61 7 3365 7299.
0167-2681/$ – see front matter © 2007 Published by Elsevier B.V. doi:10.1016/j.jebo.2005.12.014
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agent as the locus of theory to the rule or automata, Mirowski is less clear about how this new microfoundation relates to a broader macro analysis of the whole economic system, nor indeed whether such ambition for a computational theory of long-run economic growth or development is even reasonable for an evolutionary computational economics. How far can we legitimately analytically extend the computational theory of markets under the cover of evolution? This is the Hayek question writ large, namely how does a market order emerge, which in the micro meso macro framework reduces to the question of how a macro order self-organizes from a meso trajectory of micro rules. Mirowski’s case that economics is becoming and should be a science of markets (i.e. rules) not of man (i.e. choice) is a persuasive analytic expression of the idea that economic evolution is a growth of knowledge process. It is, moreover, something that Smith (1776) and Marshall (1994) might well have recognized. So, let us suppose we can make that leap to an ontologically robust and empirically rich computational taxonomy of market forms that ultimately reduces to the diverse rules of markets rather than the preferences or rationality of agents, and that all of this can pass as a new evolutionary computational microeconomics. The question is then, what is next? Mirowski provides some clues about this, in particular suggesting how computational theory can furnish a number of lemmas or principles that constrain what is evolutionary possible at the macroeconomic level. For example, the impossibility of a Turing-equivalent market or of complete arbitrage means that the aggregation of markomata is not a ‘super-market’, but must be a complex, diverse and historically dependent ecology of connected markomata. The upshot is that although Mirowski’s computational conception of markets furnishes a powerful and expedient system of microfoundations for evolutionary economics, the transition to a macro view of an evolving market economy does not, and cannot, involve more of the same. The aggregation of automata is not a bigger automata, but rather the arrival of emergent complex self-organizing economic systems (see Potts, 2000; Foster, 1997, 2005; Foster and Potts, 2006). Mirowski is right that markets are the centre of economic analysis, that markets are computational in nature, and that markets evolving makes for an evolutionary computational microeconomics, but he is wrong to suppose that the story ends there. From micro computation we build meso structure, and from meso structure we build macro order, and this is how economic systems evolve. Mirowski criticizes Hayek for his seeming oblivion of the idea that markets differ in computational composition and, moreover, that these differences may then have systematic consequences for the operational array of prices and activities. That is certainly a fair comment, as is the critique of modern evolutionary economics as that in which everything evolves except markets (Mirowski, this issue). In a similar spirit, Loasby (1999, p. 112) has argued that ‘markets are much too important, and much too amenable to economic analysis, to be treated as primitives’. So Mirowski is right to point out that evolutionary economists have, by and large, failed to notice that markets exhibit emergent or spontaneous differences and so, as with anything with variation under selection, that markets too may evolve (although see Vanberg, 1994; Loasby, 2000; Potts, 2001; McMillan, 2002; Morrison, 2004). Yet Hayek’s (1976, p. 109) notion of a catallaxy as a special kind of spontaneous order ‘brought about by the mutual adjustment of many individual economies in a market’ [italics added] is intended to emphasize not the computational microstructure of how markets work, but rather the nature of the resultant emergent order. Hayek’s catallaxy is the macro order that Mirowski proposes can be described with the micro theory of markomata. But no such connection can be directly made, for Mirowski’s markomata is an order of rules that combines with other generic orders of rules to form the macro system. Market rules are abstractly necessary but not generally sufficient to describe the evolution of the economic system. The same is true of the Institutional and Schumpeterian evolutionary economists, who are mostly concerned with the
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macro patterns of change in economic activities (as one activity or technology displaces another, etc.) and less so with the detail of coordination along the way. We suggest, then, that we can use the micro meso macro (hereafter mmm) framework (Dopfer and Potts, 2007) to connect markomata to the macro order by viewing markets themselves as meso. Space does not permit a detailed introduction of mmm, but the core idea is relatively straight-forward. In mmm, an economic system is conceptualized as being made of generic rules that allow carriers to perform operations (Dopfer and Potts, 2004). A rule and its population of carriers is a meso unit, the macroeconomic system is a complex system of connected meso units, and economic evolution is the process of change in meso units, either through novel generic rules being introduced into the economic system or through a change in the population of each meso rule. Evolutionary macroeconomics is the study of how the entire systems of meso are coordinated and how they change. Evolutionary mesoeconomics is concerned with the structure and population of each generic rule, and evolutionary microeconomics is the study of the individual processes of adoption by a carrier (such as an agent) of the rule. This framework is intended to capture the idea of economic evolution as a process of endogenous transformation of the economic order through the origination, adoption and retention of new economic ideas, or generic rules, that may variously manifest as behaviours, organizing rules or technologies. It is entirely within the ambit of the mmm framework to treat market rules themselves as generic rules, and this is surely the apposite place to start. So let us leave technological change to the technology scholars and cognition and human decision theory to the psychologists, for Mirowksi’s proposition does indeed center a new empirically warranted microeconomics from which we may generalize, via the mmm framework, to allow a strong claim to be staked for a new economics, complete and proper. There are three aspects to this analytical integration. First, the meso domain adds precision to markomata theory by providing a clear distinction between heterogeneity of market forms and variation in their relative prevalence and stability. In evolutionary mesoeconomics, a generic rule is understood with respect to three prime dimensions: its analytical separability from other rules (a continuous double auction is undeniably different to a posted-price markomata), the size of its population (how ‘big’ a part of the economic system is this rule?), and its relative stability in terms of the three-phase meso trajectory (i.e. is the generic market rule still in the origination stages, is it undergoing rapid adoption and/or adaptation, or is it stable and completely embedded within the economic system?). This meso view, that each type of market rule possesses its own population and trajectory, brings immediate clarity to several of Mirowski’s less-central but nonetheless intriguing remarks. Two are worth noting. His almost casual observation (Mirowski, this issue) of the relative ubiquity of posted-price markomata compared to other more computationally complex market forms can now be understood both as a statement about relative population sizes and with respect to evolutionary dynamics; using mesoeconomics, the analyst can understand not only current relative frequencies but how they are likely to change as the respective meso trajectories unfold. While making no standard claims to predictive power, the addition of the meso trajectory concept to the markomata analytical toolbox is crucial to any hope that a new computational evolutionary economics may provide insight into the future shape and nature of market-based systems. Similarly, it is the meso trajectory, as the core dynamical unit of economic analysis, that lends power to Mirowski’s call for a ‘natural history of markets’ (Mirowski, this issue). A retrospective account of the market forms that have shaped economic evolution over historical time is made possible with the recognition that markomata, while central to economic analysis, are, like all meso, subject to the evolutionary dynamics of origination, adoption and retention (or early death). Markomata theory allows a fresh view of the economy as a market system, but it requires the dynamical context of the meso
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trajectory to allow the past and future of the market system to be properly analyzed and, perhaps, understood. The second way in which mmm may usefully generalize Mirowski’s proposition is via a fuller microspecification of markomata rules and where and how they are carried. As Mirowski himself notes, one of the dimensions along which markets differ is the degree to which they require knowledge or know-how on the part of individual users; for example, specialist training is a precondition for effective trading in the CDA-based exchanges, while a child can purchase a newspaper at the local store. Some markets, such as broker-mediated real-estate markets, rely on written and enforceable codes of conduct; others presume specific knowledge of time, place and unwritten but knowable rules for bidding (such as perishable-goods auctions, e.g. Weisbuch et al., 2000 on the Marseilles fish market); and in some markets a pre-requisite for participation is access to and ability to operate a web-connected computer (e.g. eBay). Clearly, any markomata is decomposable into a set of rules that are variously behavioural, social or technological; furthermore, the computational capacity of any market relies on rules carried by some convex combination of individual, group and machine as an allocation of complexity (Clark et al., 2004). It is here that the mmm framework can add further analytical precision to Mirowski’s conception of markets, via the rule taxonomy (Dopfer, 2005) that underpins the micro domain of micro meso macro. This schema allows a conceptual organization of rule types and the ways in which they are carried. The rule taxonomy parsimoniously distinguishes four types of rule (cognitive, behavioural, social/organizational and technological) and two classes of carrier: subject (i.e. the human individual) and object (i.e. physical artifacts). It establishes a partial correspondence between rule type and class of carrier, whereby organizational and technological rules are carried by objects, and cognitive and behavioural rules are carried by subjects. Hence, the rule taxonomy offers an alternative, and we suggest strongly complementary, method for the decomposition and thus classification of heterogeneous market forms. Along with analytic precision, this micro-taxonomic approach offers a particular advantage to markomata theory: it provides Mirowski’s proposition with a strong answer to those concerned with the question of robust microfoundations by allowing the vexed question of human agency to be treated in a purely positive, empirically determined way. The task of the microeconomist, in this view, is no more and no less than one of classification: of the complete set of rules that comprise a particular markomata; of the typology of such with respect to their behavioural, social/organizational or technological content; and of the class of carrier associated with the operational execution of each rule in the set. Though not required by the mmm analytical framework, it should be noted that this conceptual approach is perfectly amenable to object-oriented (OO) modeling techniques, in the sense that it seeks to define rules (in OO terminology, an object) in terms of their type (a property) and by the relevant class of carrier (a method). Furthermore, microdynamics are inherent: the mmm framework, being fundamentally scale-free, utilizes the trajectory concept to describe the process by which individual agents may originate, adopt, adapt, retain (and, of course, discard) economic rules. This again suggests a modeling domain of much potential as the mechanisms by which new rules are diffused within a population of autonomous individuals, and the outcomes of such processes are familiar conceptual territory for practitioners of endogenous network formation, agent-based modeling and evolutionary game theory. Modeling questions aside, however, it is clear that a more robust and complete microspecification for markomata theory can be achieved via its integration with the mmm framework: the rule taxonomy facilitates a more precise and honest unpacking of the rules that comprise any given markomata. The strength of the approach, and the reason it should be used to extend the microfoundations of Mirowski’s proposition, is that it also (and non-trivially) allows methodological individualism to be upheld without compromising the potential applica-
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tion of established modeling techniques. This is important if we seek to attain the basic properties required of a useful, realistic and feasible economics; these being, necessarily and sufficiently, empirical warrant, analytical rigour and methodological pragmatism. There is a yet stronger imperative to integrate mmm with markomata theory, and moreover one that furthers the case made so far that what Mirowski is doing is furnishing a whole new conception of economics, namely the implications this may have for macroeconomic analysis, an area even more fraught (and inseparably so) than the question of human agency. Mirowski never explicitly considers the relation of markomata to macroeconomics, so it is unclear whether this is because he regards the extension as imponderable, insidious or just non-computational. Instead of a macro perspective, Mirowski offers a theory of markomata networks, including the hypothesis that the topology of connected markomata is likely to exhibit small-world properties in the connections between markets (and we might also suggest that there are also likely to be hubs in the distribution, such that some markets are much more heavily connected than others, making it scale-free, and also that the distribution of markomata types along an axis of complexity is likely to be described by a power-law). Yet an ecology of markets is not yet a macroeconomic system, and this is where mmm can provide some guidance on how markomata might underpin a new ‘computational’ approach to evolutionary macro analysis. Mirowski’s program is certainly macroscopic in that it seeks to encompass the study of all markets as a single connected web, yet it is equally clearly not what is normally meant by macro as an aggregation of expenditure or supply functions (or the study of aggregate phenomena such as inflation, unemployment or output). The analytic sense of a large number of automata or institutions all fitting together in a complex way is perhaps more closely related to the erstwhile discipline of political economy, which sought to understand how the whole economy functions through the interaction of all institutions as based around the market. Mirowski’s macro is perhaps best then understood as computational political economy, and the mmm framework can provide some structure for this. The macro domain of mmm analysis is about how all of the meso fit together, both at the deep level of how generic rules themselves fit together and also at the surface level of how rule populations fit together. This process of fitting together is a self-organizing process of coordination of meso rules to each other through changes in connections and in populations. The implication, then, is that we may think of an economy as a complex system of markomata forming a perhaps global connected web (a macromata perhaps, although Hayek preferred the term catallaxy) that is embedded within and structures the relation between all other generic rules (or meso). Among other things, this would add significant force to the sources of variety in the evolution of markomata as the effect of other generic rules and their changes also impacted on the way that rules are bent or got around to infuse the evolution of markomata, and also vice versa, as markomata evolution itself engenders change in the rules of other automata. A loaded metaphor is to think of the macromata as a kind of operating system (e.g. Friedman, 2000) for an economic system, a system that evolves through successive increases in computational power and connectivity that manifests in real changes in the macro pattern of economic activities. So, it seems to us that it might also be useful to think of the macroeconomic order as a connected system of market rules and the behavioural, social/organizational and technological rules that attend them. mmm allows us to view this system from two perspectives; in terms of the efficacy of connections between the generic rules themselves and in terms of the relative frequencies of rule populations; it also allows the sources of rule variety to be specified and the consequent re-ordering of the macro system to be systematically traced through. This macromata perspective scales up the analytic power of Mirowski’s framework by connecting it to a sharper conception of Hayek’s catallaxy that honors still the emergent and self-ordering nature of an only
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partially designed order. Much of markomata theory elides agency by locating it firmly instead in the designer of constructed markets. But a macro analysis can never do that, as the enormity of the failure of the 20th century’s experiments with centralized planning attest. Perhaps mechanism design has always harbored this ambition, and it is germane to note that Hayek (1945) warned against this on the computational grounds of essentially distributed knowledge. His point was that knowledge grows better and faster in parallel (see Loasby, 1999). So maybe a massively parallel view of markets and the non-market rules on which they depend and with which they interact, each with adapted computational capacity, is an expedient conceptual basis for an evolutionary computational macroeconomics. No one likes it when historians do theory, and worse yet is when they are right. But Mirowski’s markomata framework is eminently workable as a general analytical framework for economics. It has ontological and analytic foundations in the theory of computation and evolution, a taxonomic basis that is both logical and historical, and moreover it makes coherent a significant body of modern microeconomic analysis. It is a powerfully extensible approach that shows real promise for the formalization of economic change as a growth of computational capacity in a market system through the evolution of generic rules. References Clark, J., Morrison, K., Potts, J., 2004. The allocation of complexity. Working Paper. School of Economics, University of Queensland. Dopfer, K., 2005. Evolutionary economics: a theoretical framework. In: Dopfer, K. (Ed.), The Evolutionary Foundations of Economics. Cambridge University Press, Cambridge, pp. 3–55. Dopfer, K., Foster, J., Potts, J., 2004. Micro meso macro. Journal of Evolutionary Economics 14, 263–279. Dopfer, K., Potts, J., 2004. Evolutionary realism. Journal of Economic Methodology 11, 195–212. Dopfer, K., Potts, J., 2007. General Theory of Economic Evolution. Routledge, London. Foster, J., Potts, J., 2006. Complexity, evolution, and the structure of demand. In: Holmen, M., McKelvey, M. (Eds.), Flexibility and Stability in the Innovating Economy. Oxford University Press, Oxford, pp. 99–120. Foster, J., 2005. From simplistic to complex systems in economics. Cambridge Journal of Economics 29, 873–892. Foster, J., 1997. The analytical foundations of evolutionary economics: from biological analogy to self-organization. Structural Change and Economic Dynamics 8, 427–451. Friedman, T., 2000. The Lexus and the Olive Tree. Anchor Books, New York. Hayek, F., 1976. Law, Legislation and Liberty, vol. II. Routledge & Kegan Paul, London. Hayek, F., 1945. The use of knowledge in society. American Economic Review 35, 519–530. Loasby, B., 2000. Market institutions and economic evolution. Journal of Evolutionary Economics 10, 297–309. Loasby, B., 1999. Knowledge, Institutions and Evolution in Economics. Routledge, London. Marshall, A., 1994. Ye Machine. Research in the History of Economic Thought and Methodology, Archival Supplement 4. JAI Press, Greenwich, CT, pp. 116–132. McMillan, J., 2002. Reinventing the Bazaar: The Natural History of Markets. Norton, New York. Mirowski, P., 2002. Machine Dreams: How Economics Became a Cyborg Science. Cambridge University Press, Cambridge. Mirowski, P., Somefun, K., 1998. Markets as evolving computational entities. Journal of Evolutionary Economics 8, 329–356. Morrison, K., 2004. Asset Price Dynamics Under Networked Expectations. Unpublished mimeo. Potts, J., 2001. Knowledge and markets. Journal of Evolutionary Economics 11, 413–431. Potts, J., 2000. The New Evolutionary Microeconomics: Choice, Complexity and Adaptive Behaviour. Edward Elgar, Cheltenham. Smith, A., 1776. The Wealth of Nations (Cannan edition 1994). The Modern Library, New York. Vanberg, V., 1994. Rules and Choice in Economics. Routledge, London. Weisbuch, G., Kirman, A., Herreiner, D., 2000. Market organisation and trading relationships. Economic Journal 110, 411–436.