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Herrmann-Pillath, Carsten
Working Paper Rethinking evolution, entropy and economics: A triadic conceptual framework for the maximum entropy principle as applied to the growth of knowledge Frankfurt School - Working Paper Series, No. 146
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Suggested Citation: Herrmann-Pillath, Carsten (2010) : Rethinking evolution, entropy and economics: A triadic conceptual framework for the maximum entropy principle as applied to the growth of knowledge, Frankfurt School - Working Paper Series, No. 146, Frankfurt School of Finance & Management, Frankfurt a. M.
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Frankfurt School – Working Paper Series
No. 146
Rethinking Evolution, Entropy and Economics: A triadic conceptual framework for the Maximum Entropy Principle as applied to the growth of knowledge
by Carsten Herrmann-Pillath
Sonnemannstr. 9 – 11 60314 Frankfurt am Main, Germany Phone: +49 (0) 69 154 008 0 Fax: +49 (0) 69 154 008 728 Internet: www.frankfurt-school.de
Rethinking Evolution, Entropy and Economics
Abstract
Recently, the maximum entropy principle has been applied to explain the evolution of com- plex non-equilibrium systems, such as the Earth system. I argue that it can also be fruitfully deployed to reconsider the classical treatment of entropy in economics by Georgescu-Roegen, if the growth of knowledge is seen as a physical process. Relying on central categories of Peirce’s theory of signs, I follow the lines of a naturalistic evolutionary epistemology. In this framework, the three principles of Maximum Entropy (Jaynes), Maximum Power (Lotka) and Maximum Entropy Production can be arranged in a way such that evolution can be conceived as a process that manifests the physical tendency to maximize information generation and information capacity. This implies that the growth of knowledge is the dual of the process of entropy production. This theory matches with recent empirical research showing that eco- nomic growth can be tracked by measures of the throughput of useful work, mediated by the thermodynamic efficiency of the conversion of exergy into useful work.
Key words: Peirce, Georgescu-Roegen, maximum entropy, maximum power, natural selec- tion, semeiosis, physical inference devices, economic growth, useful work
JEL classification: B52, D80, Q57
ISSN: 14369753
Contact:
Prof. Dr. Carsten Herrmann-Pillath Academic Director, East-West Centre for Business Studies and Cultural Science Frankfurt School of Finance and Management Sonnemannstraße 9-11 60314 Frankfurt am Main, Germany
Email [email protected]
Submitted to the Annual Meeting of the Ausschuß für Evolutorische Ökonomik at the Verein für So- cialpolitik , Linz, Austria, July 1-3, 2010
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Content
1 Peirce: A neglected source of inspiration for evolutionary economics ...... 4
2 Triadism as a unifying conceptual perspective...... 5
3 The naturalization of the semeiotic triad ...... 7
4 Semeiotic triads as inference devices ...... 9
5 Autocatalytic cycles as archetypes of inference devices ...... 13
6 The energetics of semeiosis ...... 16
7 Implications for economic analysis ...... 22
8 Conclusion ...... 25
References ...... 26
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1 Peirce: A neglected source of inspiration for evolutionary economics
Charles Sanders Peirce was one of the most original and influential American thinkers at the turn from the 19th to the 20th century. He co-created American pragmatism and contributed to many different fields, such as logic, mathematics and metaphysics. His thinking was shaped by his profession as a learned scientist (chemistry and geodesy), thus differing in background from most academic philosophers of his times. His philosophy was part and par- cel of the general intellectual scenery, which also fostered the rise of institutionalism in eco- nomics and the creation of the first vintage of evolutionary economics. Yet, his work is strangely neglected in both the history of thought in economics and in modern treatments of evolutionary economics, mainly relegated to a few hints at his impact on the general intellec- tual climate, and on the role of his methodology for institutionalist economists (e.g. Hodgson 1999). References to Peirce mostly concentrate on Peirce’s methodological viewpoints and his philosophy of science, which is seen to be shared by influential institutional economists such as Commons and Ayres (Liebhafsky 1993). However, even in this regard John Dewey certainly is regarded to be the more influential thinker. This relative neglect is also condi- tioned by the sparseness of explicit references to his work by the early evolutionary econo- mists themselves, such as Veblen. But Peirce was also a pundit of capitalism, especially of what he perceived as an undue emphasis on competition. His metaphysical notion of ‘agapeism’ introduced a strong role of altruism into his view of evolution and assigned an almost cosmic role to universal love. This attitude might have distracted even institutional economists from a closer inspection of his other ideas.
In this paper, I wish to explore a Peircian perspective on evolutionary economics. My motiva- tion is not to provide an exegesis of Peirce’s voluminous works from the viewpoint of eco- nomics. With ‘Peircian’ I refer to certain central elements in Peirce’s thought which I believe can be of crucial importance to further push the case of evolutionary economics. That is, my reception is selective, and in places even contradicts some more specific opinions of Peirce himself. So, ‘Peircian’ actually refers to extensions and modifications of the original thought. The elements that I specifically consider are:
• the theory of signs
• the notion of fundamental randomness
• the concept of final causality
• and naturalism in the theory of mind.
I think that these ideas can help to clarify one fundamental issue in evolutionary economics (Metcalfe 2001): How can we conceive of economic evolution as growth of knowledge? In a Peircian view, we can develop a naturalistic conception of knowledge, which means, ulti- mately, that ‘information’ is conceived as a physical category. Based on this, we will be able to establish an unexpected connection between the Peircian approach and a newly emerging field in the analysis of non-equilibrium dynamical systems, namely the Maximum Entropy approach (for a most recent survey, see Kleidon et al. 2010). I will argue that the growth of
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Rethinking Evolution, Entropy and Economics knowledge is a physical process, hence being subject to physical laws. From this follows, that economic evolution follows physical laws, especially the laws of thermodynamics. So, we travel from Peirce to Georgescu-Roegen. I will argue that a Peircian perspective can help to remedy some flaws in the earlier economic uses of the concept of entropy, especially in the sense of clarifying the relation between information-theoretic and physical uses of the term (thus pursuing a line of thinking originating with Ayres 1994). The backbone of the entire argument is a naturalistic interpretation of evolutionary epistemology, which can be built on Peirce’s theory of signs. I will conclude in demonstrating a fundamental consequence for eco- nomic analysis, which is also of far-reaching practical importance: If the growth of knowl- edge is a physical phenomenon, we cannot argue that knowledge can be a substitute for other resources, thus possibly overcoming limits to growth that result from the laws of thermody- namics as applied on matter-energy deployments. Creativity cannot be substituted for energy (Kümmel 1998), as both are just two sides of the same coin.
2 Triadism as a unifying conceptual perspective
In my exposition I will focus on the theory of signs, because I think that this is a most ne- glected area in economics. The theory of signs is intimately connected with a basic philoso- phical stance in Peirce, which rejects dyadic conceptual structures and proposes triadic ones, in this respect similar to other thinkers such as Hegel. Peirce very often uses the distinction between ‘Firstness,’ ‘Secondness’ and ‘Thirdness’ to analyze a certain conceptual domain. These most universal categories assume different meanings in different contexts, and as I do not wish to indulge myself in mere exegesis, I just posit my interpretation, based on Peirce’s views (for an excellent collection of citations from Peirce, see the pertinent entries in Berg- man and Paavola, 2003; for a selection from Peirce’s works, see Peirce 1992, 1998). This is that Firstness relates to a phenomenon without any relation to another one (‘ x’), Secondness relates a phenomenon to another one (‘R xy ’), and Thirdness relates Secondness to a third phe- nomenon (‘R xyz ’). So, for example, Peirce referred the concepts of ‘possibility,’ ‘actuality’ and ‘necessity,’ or, the concepts of ‘entity,’ ‘relation’ and ‘representation’ to the three catego- ries, respectively (Burch 2010).
In our context, these uses boil down to a fundamentally different ontology as it is convention- ally assumed in the sciences, apart from certain interpretations of quantum mechanics and cosmology (i.e. referring to the Copenhagen interpretation on the one hand, and the anthropic principle on the other hand, see Penrose 2006: 728ff., 757ff.). This is because Thirdness in- troduces the notion of an observer into the basic assumptions, in the sense of that regularities in events can only be established relative to an observer’s position who interprets what is pure Secondness otherwise. In Peirce’s thought, this follows from his phenomenological approach to see the world as a system of appearances, the ‘phaneron’. In this sense, all reality is consti- tuted as staying in triadic relations with phenomena which are themselves a part of that real- ity, that is, there is no external standpoint from which the position of the observer can be ab- solutely determined. From this follows Peirce’s fallibilism and anti-foundationalism which is very close to the Popperian (1972) evolutionary epistemology. Against this background the theory of signs obtains a very broad ontological status, especially since the notion of regulari-
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Rethinking Evolution, Entropy and Economics ties in the world can only be understood in terms of Thirdness, which means, as a semeiotic relation.
This view emanates from Peirce’s foundational notion of ‘tychism’, which refers to the fun- damental randomness of the world. Randomness (‘possibility’) is Firstness, and Secondness is a relation between two random events. Regularities over those relations can only be estab- lished via the relation with a Third. Peirce believes that such a triadic conceptual structure is indispensible to explain how regularities (‘habits’) emerge in a random world. Therefore, and again very close to Popper (1982), Peirce rejects subjectivistic notions of probability, thus assigning the objective status of propensities to them (see also Bunge 1977: 179ff., 194ff., and for an opposing Bayesian view, Jaynes 2003: 60ff.). The movement from propensities to regu- larities is seen as a process involving unfolding sign relations, which results into a conjunc- tion of the physical world and the process of infinite semeiosis (Atkin 2006).
Consequently, Peirce believed that the physical world is evolving, such that one could not assign physical laws to primordial states of the world. The laws themselves emerge from tri- adic processes. I do not dwell on the potential relevance of this idea for recent development in physics and cosmology (especially with reference to evolutionary theories of a multiplicity of universes, see alternative approaches by Smolin 1997 and Susskind 2006), but confine myself to the insight that this approach fits very well into the project to explain how knowledge grows in the economy. This is because we can see the evolving economy as a complex system in which increasingly complex regularities emerge from some primordial, simpler states. Regularities are embodied in technologies, institutions, or behavioral patterns. A Peircian view would state that this emergence of complexity can only be explained by means of a tri- adic approach.
This triadic approach is at hand in the guise of Peirce’s theory of signs. Before exploring this, one clarification is necessary. If we have talked about an ‘observer’ previously, this does not necessarily imply a human observer, or, more generally, a ‘mind’. Again, this does not fully converge with Peirce’s original ideas, which, however, remain ambiguous at this point. Peirce partly assumes the position of panpsychism, which would posit that all phenomena have a mental quality, and which would reflect the ubiquity of ‘Thirdness’ in the fundamental onto- logical structures of the world. At the same time, as we shall see in more detail soon, he states that any sort of tertiary intermediating relation can count as ‘Thirdness’. In this case, the men- tal would be an emergent property of a more fundamental, non-mental process.
I will follow this second interpretation, which I call the ‘naturalistic’ one (Herrmann-Pillath 2010a). It is partly supported by Stone’s (2007) most extensive critical elaboration on Peirce’s theory of signs. On the one hand, Stone shows that Peirce does not relate the sign relation to mental acts, in the sense of a ‘meaning’ of signs. At the same time, Stone argues that the sign relation relates with purposes that the users of signs have. Purposes are not mental, but relate to living systems exclusively, which limits the scope of ‘Thirdness’ with reference to the ob- server. In this paper, I will only consider living systems, so that the extension of physical processes in general need not be clarified (which I support nevertheless, following recent ad- vances in the physics of information, see von Baeyer 2003, Lloyd 2006).
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So, the naturalistic approach to Peirce’s theory of signs corresponds to a majority view in the modern analytical theory of minds, which sees mental phenomena as supervening on physical phenomena, especially neuronal phenomena (McLaughlin and Bennet 2008). In our context, we do not need to delve into the intricacies of this discussion, but need to point out that my subsequent approach follows those positions which adopt an externalist view on superven- ience, such as in teleosemantic substitutions of the category of ‘meaning’ by the category of ‘function’ (Millikan 1989, MacDonald and Papineau 2006, Herrmann-Pillath 2010b). This non-Cartesian theory of mind is a necessary complement to the physical theory of knowledge which I will now develop from the vantage point of Peircian triadism.
3 The naturalization of the semeiotic triad
The first step of my argument is the naturalization of the theory of signs. The sign relation is a triadic one by necessity, because one has to distinguish between an object O, a sign S which stands for O, and an interpretant I to which S relates. In other words, a sign is always a sign of something for something. So, fire is an O, smoke is an S, and I is an animal that flees the fire once scenting the smoke. From this follows, that the same physical entity related to the sign can actually refer to different signs, such that, for example, the smoke means ‘dangerous fire’ for the animal, but possibly ‘human company’ to a straying wanderer in the forest.
I will now take a shortcut from what is a very rudimentary exegesis of Peirce to the concep- tual frame that I extract from that. This builds on an extended reconstruction of Peirce’s the- ory of signs that has been proposed by Stone (2007) and was further detailed by Robinson and Southgate (2010) with reference to the biological theory of evolution. In this reconstruction, the interpretant is seen as a ‘response’ R of any sort of system to the sign. This response is mediated via certain causal mechanisms which define the capacity of the system to respond in a particular fashion, designated as Q. Q is the set of structural features that causally connect O and R, given the presence of S in relation to the living system. Now, in the evolutionary con- text, this specific response pattern has emerged from natural selection. Natural selection oper- ates on both the emergence of Q and the emergence of S, in the sense that the conjunction of Q and S, i.e. the capacity of responding to a sign, relates to some general purpose P which is established in the process of selection. So, if an animal scents smoke and flees the fire, the animal has certain organismic features that enable it to respond to smoke in a particular way. In which way, does not matter as long as it serves the general purpose to avoid the negative impact of the fire. In Peirce’s words, the semeiotic relation establishes a relation between ‘particulars’ and ‘generals’, in the sense that selection does not deterministically favor one single particular response, but only classes of responses which are functionally equivalent.
Now, Stone argues that this transition from particulars to generals implies a transition be- tween different kinds of causalities. In a first step, this is the Aristotelian distinction between efficient and final causality. Efficient causality refers to the mechanistical causal chains that lead towards a particular behavior such as fleeing the fire. However, this is insufficient to an- swer the question why the animal manifests this behavior. A full explanation needs to rely on a ‘purpose’, or, the function of that behavior, which means a conjunction of R and P (for a
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Rethinking Evolution, Entropy and Economics recent analysis of functions in relations to purposes, see Perlman 2009). These functions have different scopes, such as the organismic functions that connect sensory perceptions with mo- toric actions. So, there is a hierarchy of functions, which lead to ultimate functions that emerged from the process of natural selection. So, fleeing the fire has the function to survive, and survival has the function to be able to reproduce, and so forth. Therefore a full explana- tion of the behavior of the animal has to relate to evolved purposes. This means to conjoin efficient and final causality: Only final causality explains why the animal flees the fire.
We end up with figure one, which is a systematic map of the triadic conceptual structure in the theory of signs (modifying a diagram in Robinson and Southgate 2010; for related dia- grams in the semiotic literature, see e.g. Brier 2008 or El-Hani et al. 2006). In this figure, we already argue in the completely naturalized framework, so for clarity I use X as representing the sign and R as representing the I, following the notation introduced by Stone (2007).
Figure 1: Basic structure of the semeiotic triad (Herrmann-Pillath and Salthe 2010)
Starting out from this conceptual structure, it is now possible to show how the semeiotic proc- ess is an information-extracting process. This is also crucial for providing the foundations on which the conceptual synthesis between entropy and evolution can be built.
In the triadic structure, the sign is both a token and a type. As a token, it is efficient-caused by the object. However, this is a relation between a large number of possible microstates of the object that efficient-causally connect with one sign (‘smoke’ can be caused by many different manifestations of fire). Thus, the sign can be seen as a macrostate. From this follows that the relation between O and X is one of X supervening on O, with multiple realizability of X.
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The character of X as a type results from the relation between X and R. This, however, means that the relation between X and O becomes dependent on the relation with P. In other words, we can say that there is a large number of microstates of an object, and which of them actually carry information is determined by the semeiotic relations that connect the microstates with P. In Stone’s (2007: 156ff.) analysis the token-type transition occurs because the projection of R onto P classifies R as a ‘general type of outcome’. This distinction is especially important, as it allows for the possibility of failure, hence misrepresentation in the teleosemantic literature (see e.g. Neander 2009, a point also emphasized by Robinson and Southgate 2010).
At this point, we can bring Peirce’s ‘tychism’ into play. Tychism, i.e. the basic ontological premise of randomness, is firstly pertinent to understand the relation between O and X. The relationship between the macrostate and the microstates can be treated along the lines of sta- tistical mechanics (on the conceptual parallel between supervenience in statistical mechanics and the philosophy of mind, see Sklar 2009). There is an overwhelmingly large space of pos- sible microstates in a certain domain of observation (such as a gas in a container), but the ob- server can define a certain set of macrostates which describe the system more parsimoniously, relating a larger number of microstates to the same macrostates. The sign as a macrostate effi- cient-causally relates with O because O produces X. But in spite of this unequivocal causal relationship, we cannot answer the question why X is a sign of O unless we consider the role of the sign in eliciting the response R. Yet, there is an efficient-causal chain that connects R and O via Q, for which the distinction between microstates and macrostates also holds: In Stone’s interpretation of Peirce, efficient causality connects particulars with particulars, leav- ing much room for various microstates connecting with the same macrostates. This is the first sense how the semeiotic triadism relates to information: Vita the projection of microstates into macrostates, information is compressed; hence informational gains are exploited, in the sense of algorithmic compressibility, relative to the goals of the system.
The second context where tychism is relevant is the relation between R and O. Again, the same response can be related to many different microstates of both the object and the living system which responds. However, this relation differs from the primordial O-X relation in terms of a specific hypothesis about natural selection. This hypothesis states that the system of which R is a part will assume the maximum entropy state with relation to its functions. So, we would relate tychism with a more specific hypothesis about systems dynamics. This is the second sense in which semeiotic triadism to information: As a structure inhering the evolu- tionary process, the mapping from microstates into macrostates generates new information, or, knowledge.
4 Semeiotic triads as inference devices
With this specific hypothesis, we extend the Peircian framework substantially, however, within the context of tychism. The Maximum Entropy approach (MaxEnt) has been recently developed into a universal tool to analyze the evolution of complex systems (for succinct overviews, see Kleidon and Lorenz 2005b; Niven 2009, and the special issue of the Philoso- phical Transactions of the Royal Society B, Kleidon et al. 2010 and the papers surveyed
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Rethinking Evolution, Entropy and Economics therein). Originally, it has been developed as a statistical tool for Bayesian optimization (Jaynes 2003), and as such has been also introduced into econometrics.
In the generalization, MaxEnt states that in order to predict the trajectories of change of com- plex systems, it is sufficient to determine the constraints under which the systems evolve, and to assign the maximum entropy to the microstates of the system which correspond to the pre- dicted macrostates (for a concise introduction, see Dewar 2009). In other words, the system will evolve into representational macrostates (the prediction about the macrostate of the ob- served system) which maximize entropy for representational microstates (the unobservable microstates of the observed system). At this stage of the argument, we do not yet relate this to the proposition that the systems maximize entropy in the physical sense (see below, section 6). At the same time, however, we do not refer to Shannon information entropy here. Yet, we analyze an information extracting process: The MaxEnt procedure is a statistical means to compress the information that is needed to explain and predict the behavior of complex sys- tems, and which therefore extracts new information about the system. As such, it is not a hy- pothesis about physical phenomena in the first place, but a method to check the validity of assumptions about physical phenomena. If MaxEnt fails, this implies that the assumptions about the constraints have been wrong, under which the systems operate.
In the original Bayesian approach, MaxEnt relates to the observer who tests predictions about physical systems, and who would change the physical hypotheses if MaxEnt fails. In the Peir- cian theory of signs, we can generalize this into a proposition about the evolution of interpre- tants, if we think of the ‘observer’ as an evolutionary process, in the sense of evolutionary epistemology (Popper 1972). Under natural selection, the distinction between microstates and macrostates is an economic one. Following an argument by Dewar (2009), I posit that in natu- ral selection, those systems will have an edge which economizes on their information process- ing. Under natural selection, predicting environmental changes is an essential property that even most simple living systems such as bacteria possess (Ben Jacob et al. 2006). The Max- Ent procedure means that predictions will only be based on that information which is neces- sary to generate correct anticipations, that is, as a principle of predictive parsimony. Then, we can interpret the X-R relation as one which links macrostates of O with macrostates R, relative to constraints under which the systems operate, such that the living system otherwise obtains a maximum variety of microstates. I summarize these relations in fig. 3.
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Figure 3: Maximum entropy and inference
(Herrmann-Pillath and Salthe 2010)
As a result, the semeiotic process can be seen as a mapping between the constraints under which an observed system operates, and which are manifest in the specific ways of macro- states supervening on a larger number of microstates (i.e. possible states under given con- straints), on the one hand, and on the other hand, the constraints that evolve under natural se- lection of observer systems, and which relate macroscopic systemic responses to microstates of the observing system, such that entropy is maximized. So, we can state that the triadic semeiotic process and the underlying features of living systems actually make up what might be called an ‘inference device’ (in the sense of Wolpert’s, 2001, 2008). The inference device is a physical system, and we do not refer to any sort of mental categories and human observ- ers. I fuse the previous two diagrams into figure 4 which shows the causal structure underly- ing the process of information extraction by means of natural selection.
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Figure 4: The triadic structure of physical inference devices
The argument can also be stated in an information-theoretic sense which actually leads back to earlier hypotheses such as Ashby’s law of requisite variety. Any inference device will also maximize information capacity when achieving the MaxEnt state. That is to say, MaxEnt both economizes on the process of extracting and accumulating information and maximizes the potential for the generation of new information (for a related approach without reference to MaxEnt properly spoken, see Brooks and Wiley 1988).
Let me substantiate this argument in relation to standard uses of evolutionary theory. The most straightforward interpretation of this argument in the context of evolutionary theory is to relate the triadic structure to the notion of adaptation. We then end up with fig. 5, which re- flects a standard biosemiotic argument according to which ecological niches are species- specific sign constructs. The object is the external physical world separate from an organism. Natural selection triggers changes of populations of organisms which lead towards adaptation. However, the match between environment and organism is mediated via the ‘Umwelt’, in the sense of von Uexkuell. The Umwelt is the set of signs that emanate from the environment and guide the behavioral responses of the organism. That means, all adaptations do not directly relate with the environment, but to certain representations of it, in the sense of macrostates that cover a large, even infinite set of microstates. The conjunction between the Umwelt and the responses is governed by natural selection, leading towards the emergence of generic re- sponses to signs. These generic responses are the species specific traits, such as the shape of fins of sharks.
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Fig. 5: The semeiotic conception of adaptation
Now, the MaxEnt approach implies that the species specific traits actually correspond to a large number of varieties in a population which do not affect the generic role of the trait in adaptation. So, MaxEnt is the theoretical foundation for the population approach to the spe- cies concept. But as we see, in the triadic approach an important aspect of the old essentialist species notion is conserved: This is the idea that members of populations share a set of prop- erties which define their relation with an ecological niche. At the same time, the central in- sight of the population approach is also maintained: Namely, that the maximum variety in a population is also necessary to create the potential for the evolution of new traits. This view has been recently cast into the slogan ‘survival of the likeliest’ substituting for ‘survival of the fittest’ (Whitfield 2007). It implies, formally, that species characteristics reflect ecological constraints, and that populations manifest maximum entropy states relative to those con- straints, such that, for example, certain statistical properties of the populations, and, espe- cially, changes of those properties through time, follow the maximum entropy formalism, such that adaptation can be interpreted as information-generating process (Dewar and Porté 2008, Frank 2009a,b).
5 Autocatalytic cycles as archetypes of inference devices
In order to analyze the relation between entropy and semeiosis more conclusively, we need to complete the triadic structure in terms of the causalities involved. Our workhorse is the theory of autocatalytic cycles which underlies almost all modern theories of the origin of life, with the hypercycle as a paradigmatic model (for analytical surveys see Küppers 1986; Lahav et al.
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2001). I refer to this model for two reasons. Firstly, the model allows for doing the first steps towards a physical interpretation of the MaxEnt approach. Secondly, the general structure can be applied far beyond chemistry and biology, and extends into economics (Padgett 1997, Padgett et al. 2003).
In chemistry, an autocatalytic cycle refers to a chain of chemical reactions in which one reac- tion either directly or indirectly (via joint products) produces outputs which catalyze another reaction, and so forth, until the n th reaction catalyzes the first reaction. The relation with eco- nomics is straightforward to establish: Here, catalysis would refer to the effects of positive externalities between different economic processes, such as in a team, or between companies of an industrial district (in mathematical economics, this class of models is defined by super- modularity or complementarity, see Amir 2005). Closing the loop of the externalities results into a highly efficient structure, which, however, shows the property of being fragile in the sense that the extinction of one member of the cycle will entail the collapse of the entire struc- ture (compare Kremer’s 1993 ‘O-ring theory’).
Now, Robert Ulanowicz (1997) has argued that ACs are the primordial and universal model for the interaction between three kinds of causality in physical systems, efficient, final and formal, following the original Aristotelian distinctions (for a modern view, see Ellis 2008). This follows from the following properties of autocatalytic cycles.
• Firstly, ACs are centripetal. That means, by lowering the threshold of the single chemi- cal reactions, the cycle tends to maximize the matter-energy throughput in relation to non-cyclic reactions in a given solution of components. This implies that the presence of cycles triggers competition in the sense of selection pressure on other processes that access the same resources.
• Secondly, this selection pressure differentiates into internal and external selection. Ex- ternal selection results from the aforementioned competitive pressure between different forms of reaction patterns. The most efficacious AC in terms of matter-energy through- put and speed will outcompete all other patterns, in terms of concentrations in the solu- tion. At the same time, the AC imposes internal selection of constituent components be- cause any changes of the components will affect the external performance of the cycle. This effect is intermediated via the internal linkages. For example, if for some reasons the productivity of one constituent process increases, this feeds back via the AC posi- tively, thus enhancing the original increase.
• Thirdly, the structure is autonomous from the constituent components in two senses. On the one hand, the AC does not depend on the individual components, which are fully substitutive as long as the catalytic function is preserved. On the other hand, this implies that there can be changes of the components, which are neutral with reference to the catalytic interdependence. From this follows, that the structure attains an independent ontological status, corresponding to a higher logical type, i.e. a meta concept.
• Fourthly, the emergence of autocatalytic cycles imposes directedness of changes in a given environment. This reflects the property of centripetality. The directedness corre-
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sponds to increases in performance, defined in terms of throughput. Thus, autocatalytic cycles are growth-enhancing.
Taking these properties together, we can reconstruct Ulanowicz’s argument in terms of the Peircian triad. This is done in fig. 6 where I also add a related diagram by Ulanowicz (1997: 52) in the bottom part.
Ulanowicz argues that an autocatalytic cycle shows three kinds of causality. Efficient causal- ity holds for all single relations between the different processes. This implies that if, for some reason, we are unable to identify the complete cycle, we will only see efficient causality at work. Formal causality comes into play when we consider the relative autonomy of structure in relation to constituent processes. That is, formal causality relates to internal selection in the sense that it emerges from the latter, such that a token/type transition happens. The autocata- lytic structure is a type that relates with a larger number of variants of tokens, which means, processes with neutral differences, where the criterion of ‘neutrality’ is deduced from the formal features of the structure. Thirdly, final causality underlies the directedness of the cycle, i.e. its feature of centripetal growth, which results from external selection.
Fig. 6: The semeiotics of autocatalytic cycles (Herrmann-Pillath and Salthe 2010)
In fig. 6, I relate these distinctions to the semiotic triad. For the different constituent process efficient causality holds. Specifically, this means that firstly, the emergence of the cycle is driven by efficient causality, and secondly, the growth process happens via efficient-causal
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Rethinking Evolution, Entropy and Economics mechanisms. These mechanisms are designated by the Q. Relating this with our previous dis- cussion, we can also distinguish between microstates and macrostates here. The efficient- causal processes link microstates with each other, that is, singular chains of causal events in which also all stochastic fluctuations of constituent characteristics matter. This corresponds to the statistical mechanics view that all macroscopic features can be reduced to microscopic interactions (such as temperature on atomic kinesis).
However, the specific outcomes of an AC cannot be explained by efficient causality alone. The semeiotic analysis reveals that formal causality is involved because the structure of the cycle operates as a sign, in the sense of a macrostate of the system that corresponds to a num- ber of microstates, that is, for example, a range of possible quantum fluctuations in the inter- action of the molecules or the possibility of neutral variations in the reaction net. Interest- ingly, this view corresponds to the more general observation that molecular structure is partly irreducible to the level of quantum interactions, and is effectively grasped by the specific for- mal language of chemistry that allows describing chemical bonds and molecular shapes (Del Re 1998, Ramsey 2000, Vemulapalli 2006). In fully-scale quantum reductions of molecular structure existing solutions need to rely on a seemingly hands-on technique to ‘plug in’ struc- tural assumptions into the corresponding Schrödinger equations, such that a top-down causa- tion is effectively introduced. This formal procedure corresponds to the role of formal causal- ity in the semeiotic triad. So, formal causality is revealed in the need for researchers to de- velop formal languages that explicitly describe the relevant formal structures, such as chemi- cal formula or biological taxonomy.
Finally, the directedness of the AC results from the final-causal link between the response and the purpose. This link is driven by the effects of natural selection. In Ulanowicz’s approach, the specific purpose appears to the maximization of matter-energy throughput. One has to be very careful here: We do not ascribe this property to the single cycle but to the system of competing ACs, hence the purpose is a population-level phenomenon, which is, however, reflected in single cycles in the sense that they form parts of the population, at a certain stage of the selective process.
This semeiotic analysis of the autocatalytic cycle shows that there is the possibility to relate the MaxEnt approach to energetic considerations, hence moving from the purely conceptual and methodological level to a physical interpretation. Evidently, the notion of a sign is no longer related to mental categories, but to the final causality of the evolutionary process, in which certain autocatalytic structures assume emergent properties which are sources of forces of formal causality. The ‘meaning’ of the sign is a specific function that results from selection and is manifest in the stability, resilience and differential reproductive success of a particular cycle in a population of cycles.
6 The energetics of semeiosis
The transition to a physical interpretation of semeiosis stands at the center of recent maximum entropy approaches in the analysis of complex non-linear systems in different domains, reach-
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Rethinking Evolution, Entropy and Economics ing from physics to biology (Martyushev and Seleznev 2006). In this case, the formal appara- tus of MaxEnt as a method of statistical inference is given a physical interpretation in the sense that the hypothesis is posited that such systems reach steady states in which the produc- tion of entropy is maximized. This hypothesis differs fundamentally from standard applica- tions of thermodynamics, which views the maximization of entropy as an equilibrium phe- nomenon. As such, in the past, following Schrödinger (1944), the equilibrium theory was seen as largely irrelevant for the analysis of living systems, and, per force also for economics, as those systems are non-linear non-equilibrium systems, i.e. states of complex order, which obviously represent states of low entropy in relation to their environment (Faber and Proops 1998). The Second Law might hold for the balance between these systems and their environ- ment, such that the matter-energy flow necessary to maintain the system eventually end up with exporting entropy into the environment. This idea was utilized by Georgescu-Roegen (1971) in his seminal contributions to the then incipient ecological economics. But this view does not imply that the systems manifest a physical tendency to evolve into physical states which maximize entropy production, but only refers to the equilibrium of the larger system of which they are a part and for which the condition of system closure holds at least approxi- mately. To the contrary, the Maximum Entropy Production Principle (MEPP) would imply, that the MaxEnt Principle has a direct physical meaning, in the sense that the MaxEnt state which an observer refers to in order to predict future states of a system is also a physical state in which the production of entropy is maximal.
There are different ways how we can arrive at that conclusion. In the current Peircian frame- work, and following the analysis of the autocatalytic cycle, I restrict my argument to the analysis of living systems, which is most interesting for the transfer into economics. I hasten to add that the term ‘living systems’ includes ecological systems, which are also examples of large-scale autocatalytic systems (Maynard Smith and Szathmáry 1995). Therefore, in the sense of the Gaia hypothesis, the argument also applies for the entire geobiological system of the earth, which is, as it stands to day, the result of interactions between living systems and their environment over very long time scales (Smil 2003, also with critical views on the origi- nal Gaia idea). This perspective also matches the approach of ecological economics.
The first step in connecting MaxEnt and MEPP is to introduce the Maximum Power Principle as an intermediating mechanism. This corresponds to the analysis of the autocatalytic cycle, with reference to the presumed forces of final causality. The MPP was firstly formulated by Lotka (1922a,b) who stated that natural selection would result into the tendency to maximize energy throughput of living systems. This argument directly corresponds to the centripetality and growth hypothesis about autocatalytic cycles, in the sense that MPP is a population level phenomenon. This has a very important Peircian implication: All the principles that we cur- rently put together have to be regarded as non-deterministic. This means, if one considers only certain temporal and spatial segments of the entire evolutionary sequence, stochastic fluctuations can result into states which violate the principles (actually, this idea was already ventilated by Boltzmann with reference to the cosmological validity of the Second Law). However, the principles hold on the higher level if one considers those fluctuations, which by themselves follow MaxEnt principles (for example, even with the same mean flux, a system will attain states with higher variances of fluxes and their rates, see Niven 2010). So, one can adopt the viewpoint that the different principles only hold on the level of the fully-scale evo- lutionary process, both in temporal and spatial terms (see also Vallino 2010).
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This view is very useful to understand the relation between entropy and the evolution of com- plexity. A standard argument against the entropy related approaches is that we observe sys- tems with increasing complexity, hence lower entropy. However, if we regard the entire evo- lutionary process as a stochastic process, we are dealing with truncated statistical distribu- tions, i.e. ‘drunkards’ walks’ in the sense of Gould’s (2002: 899ff.). Such a process results from stochastic fluctuations under certain constraints. In the case of living systems, an impor- tant class of constraints are minimum size constraints, including other structural constraints on organismic functioning (Bonner 1988). In this case, an observed trend of increasing com- plexity in evolution simply corresponds to the fact that the statistical distribution is truncated at the minimum constraint side, such that in the course of very long time spans, in the evolu- tion of living systems with higher complexity, larger size and so on will necessarily occur on the non-truncated part of the statistical distribution.
That being said, the MPP clearly applies for single systems in the population context. Lotka’s conjecture has been re-emerging in the literature again and again, in the context of analyzing biological evolution (Vermeij 2004), human ecosystems (Odum 2008) or generalized physical flow systems (Bejan and Lorente 2006, 2010). One most general approach is the ‘constructal law’ promoted by Bejan in numerous works. The constructal law states that over time, flow systems will only persist, if they increase access for the currents that flow through them. This definition directly corresponds to the autocatalytic cycle as a system though which energy and chemical components flow: Centripetality and directed growth of the cycle follow the con- structal law. Again, the constructal law applies on two levels. Firstly, it implies that there is a tendency of increasing throughputs in flow systems. Secondly, it implies that the capacity to adapt, that is structural flexibility and, more general, evolvability, is also an expression of the constructal law. The latter follows from the simple fact that systems which can more easily change structure in order to increase access to flows, will outcompete more rigid structures. The latter statement directly opens the conceptual connection with MaxEnt, because, as we have seen, the MaxEnt state of a system is also the state of maximum information capacity, hence evolvability.
Bejan and Lorente offer a simple framework for understanding the workings of the constructal law which allows clarifying the relation with the maximum entropy production principle (see fig. 7). Flow systems can be seen as ‘engines’ which transform inflowing exergy, i.e. useful energy, into outputs. For this process, the constructal law implies a principle of minimum en- tropy production, in the sense that power is maximized and dissipation minimized. Power is defined here relative to the evolved purposes of the system under scrutiny (for example, the purpose of the skin is to regulate heat flows in an organism). However, as long as this stage is considered in isolation, the final result of entropy maximization cannot be recognized, which is typically the case when viewing living systems as states of ‘higher order’. The simplest illustration is the notion of a ‘brake’, which can be extended as an analytical metaphor: An engine with maximum power production has to be stopped some time, which is only possible with dissipating the exergy used in the power flow. Similarly, a living system which deploys maximum power in the environment will cause many processes in which this power flow is ultimately dissipated, including the decay and ultimate death of that system. So, in this per- spective the ultimate physical consequence of the constructal law is the transformation of power flows into entropy production. From this follows that the MPP is only a subordinate hypothesis in the MEPP.
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Fig. 7: MPP and MEPP in the constructal law framework (Modified after Bejan and Lorente 2006)
There are two important additional aspects here. The first is that the different maximum power theorems in engineering and biology do not imply ‘efficiency’ in the economic sense, or minimum entropy according to some absolute standard. The maximum power state is inef- ficient in the sense that no global minimum of dissipation is achieved (this is a well-known theorem in engineering, see e.g. Odum 2008: 35ff. and Kleidon 2010: 184ff.). The second one is that we can now see the ‘engine’ as an intermediate mechanism that ultimately increases entropy production beyond the state which would be possible without the engine.
The second observation is the central one for our argument. If commonly the opinion is voiced that evolution countervails the Second Law, this mixes up observations about the complexity of the system with the effects the system has on the environment. The question is: How does the larger system differ between the states with and without the flow system, such as the living system? The MEPP then simply states, that both systems follow the Second Law, but the system with a more complex flow system will manifest gradients of dissipation which are steeper than the system without it. In other words, higher order is a mechanism of increas- ing entropy production (Annila and Kuismanen 2009, Annila and Salthe 2010).
This assumption stays at the core of recent theoretical and empirical work about MEPP. To give a specific example from ecology: Water flows on hills are processes that dissipate energy and generate entropy by moving downwards. Earthworms increase this entropy production by means of the burrows that are created by their activity (Zehe et al. 2010). Thus, the physical system without earthworms manifests less steep gradients in energy dissipation than the sys- tem with earthworms, because the soil structures are less connected. This is also a direct ap- plication of the constructal law. This example demonstrates that it would be misleading to focus on the earthworms as such when analyzing entropy production, and to argue that the evolutionary emergence of earthworms runs against the Second Law. For MEPP analysis it is central to take all systemic interdependences into consideration: Earthworms have evolved because they increase entropy production in the local ecosystem of which they are a part (and
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Rethinking Evolution, Entropy and Economics not, because the adapt to the environment in an optimal way, see Odling-Smee et al. 2003: 291, 374ff.).
This is also the reason why the research on MEPP was especially triggered by recent devel- opments in the geosciences which study, for example, the climate (Kleidon and Lorenz 2005, Kleidon 2009). The earth climate is a large-scale non-equilibrium flow system which mani- fests a strong interaction between biotic and abiotic components. In the first step, the MaxEnt approach is a method that might help researchers to reduce complexity in understanding this system, because it allows for focusing on the constraints under which the system operates, that is, there is no need for developing a full-scale mechanistic model of all causal factors that interact. In the second step, the successful application of the MaxEnt principle raises the ques- tion whether this implies also the physical maximization of entropy production. Our answer is now affirmative.
I summarize the theoretical synthesis in figs. 8a and 8b. The two figures are illuminating for proving our central argument that the growth of knowledge is a physical process which fol- lows the laws of thermodynamics. We can now state, in Peircian terms, that the growth of knowledge is identical with the evolution of signs, in the sense of evolving macrostates that undergird the functioning of living systems under natural selection. The causal link between the emergence of signs and the improvement of functionings is the information extracting and compressing function, that is, signs play the pivotal role in the process of inference that hap- pens via the evolution of functions, i.e. living systems.
We can now posit that this process follows both MaxEnt and MPP. MaxEnt relates to two processes. One is the process of sign-intermediated inference, which is accumulation of in- formation. This happens via the emergence of formal-causal structures which transform ex- ergy throughputs into useful work, i.e. power production, according to the evolved responses of the system under natural selection (compare Salthe 2007). That is, power production and knowledge generation are two sides of the same coin, which is the semeiotic process, result- ing into the emergence of intermediating macrostates that connect the observing and the ob- served system.
The accumulation of information is accompanied by the accumulation of information capac- ity. This corresponds to the MaxEnt principle which relates the responses / functions with the microstates of the observed system. Physically, this means that the observing system maxi- mizes entropy of its own microstates, with the macrostates of the two systems efficient- causally conjoined. This is a process of dissipation of energy that is involved in the non- functional efficient-causal impact of the observed system on the observing system, and the responses which are reflected in statistical features of the evolving population of observing systems.
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Fig. 8a: The relation between MaxEnt, MPP and MEPP (Herrmann-Pillath and Salthe 2010)
Fig. 8b: MaxEnt, MPP and MEPP in semeiosis
The response of the observing system follows MPP. This directly reflects natural selection according to the original Lotka’s conjecture. More specifically, this means, also correspond-
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Rethinking Evolution, Entropy and Economics ing to the constructal law, that the macrostates which are assumed by the observing system obtain those structural features which imply maximum power production. Thus, we can di- rectly state that the growth of knowledge, understood as accumulation of information, corre- sponds to the evolutionary trend to power maximization. Interestingly, this connection is manifested in a physical regularity which states that during structural evolution, the free en- ergy rate intensity of structural units is increasing monotonously (Chaisson 2001, 2005). In the semeiotic triad, this is the link between Q and R, such that Q manifests the property of free energy rate intensity.
MPP relates to MEEP over the long run, in the sense that all power production is eventually dissipated. From this observation we can draw our central conclusion: The growth of knowl- edge is a physical phenomenon that follows the Second Law. The core conceptual building block in this theory is the notion of the ‘sign’ in the Peircian sense. The sign is a physical en- tity, hence embodied knowledge in the more conventional sense also familiar to economists (see e.g. Foray 2004). As signs are traditionally related with ‘meanings’, this physical nature of signs was downplayed in favor of mentalist interpretations. However, a Peircian approach focuses on the physical side of the processes, and we can realize that the supposed ‘mental- ism’ in analyzing semeiosis reflects the complex interaction between three causalities in evo- lution. In this sense and also following the original Cartesian metaphysical error (Dennett 1991), mentalism just reflects the exclusive focus on efficient causality in modern science so far. Paradoxically, it is the claim that only efficient causality is a scientifically valid explana- tion that drives research into the direction of mentalism, because many phenomena in com- plex systems cannot be fully explained in this framework.
7 Implications for economic analysis
The concept of entropy had been introduced into economicy by Georgescu-Roegen, however, with a number of flaws resulting from one-sided readings of the pertinent literature in physics (Jaynes 1982). The Maximum Entropy approach offers a fresh view on the concept of en- tropy, because it applies on non-equilibrium open systems, and because it differentiates the fundamental laws of thermodynamics into more specific hypotheses about flow systems (of which the economy is only one example), which allows for a reconsideration of the statistical mechanics framework that met a vigorous, though eventually mistaken rebuttal by Georgescu- Roegen. This rebuttal was also rooted in some more fundamental philosophical convictions. These can be reconciled with the Maximum Entropy framework, if we consider its extension by means of Peircian categories (for a more detailed analysis, see Herrmann-Pillath 2010c).
The argument presented in this paper claims to be a major improvement over the original eco- nomic theory developed by Georgescu-Roegen. Georgescu-Roegen tried to apply the Second Law on the analysis of the economic process directly. This perspective was extremely useful to understand the role of energy flows, especially solar energy and physical storages of it, for modern economic systems. But it could not resolve the question whether ultimately the growth of knowledge is the force that countervails the Second Law. In neoclassical environ- mental economics, all resource constraints can be finally overcome by technological progress. Thus, what was missing in the Georgescu-Roegen framework is the explicit analysis of the growth of knowledge as a physical process. This missing link haunts ecological economics
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Rethinking Evolution, Entropy and Economics until today. For example, in the debate between Gilett (2006) and Lozada (2006) the direct thermodynamic relations in the physical processes that underlie the economic system remain under scrutiny, such as chemical processes in production (see also Buenstorf 2004). This lea- ves the core process in the economy out of sight, namely the generation of new knowledge. Its inclusion becomes possible once we follow the statistical mechanics framework on entropy, in the context of analyzing the physical mechanisms that enable complex systems to accumulate information. I propose that these mechanisms can best be understood in a triadic conceptual framework.
In the Peircian approach enriched by recent Maxium Entropy analysis, we can make this role of the growth of knowledge explicit. The surprising insight gained is that the growth of know- ledge, if understood as a physical phenomenon, is identical with the evolution of physical structures, hence embodied knowledge, that increase the dissipation of energy and, hence, the production of entropy, via the two mechanisms that can be described by MaxEnt and MPP.
The MaxEnt principle shows that systems will evolve into states in which information capac- ity is maximized, which reflects the exuberance of forms in the knowledge generating proc- ess. We are very familiar with this phenomenon from both biology and economics. In biol- ogy, the wasteful production of variant and the incredible richness of ecological systems cor- respond to the MaxEnt principle, as in economics these are the amazing variety of products and services or the wastefulness of the modern capitalist consumer society. At the same time, as it has been shown in the previously surveyed empirical research on exergy flows in the economy, the growth of knowledge may contribute to the increasing efficiency and sophisti- cation in the deployment of energy, but, and in this reflecting an original concern of Geor- gescu-Roegen’s, this does not lead to absolute decreases of energy throughputs. To the con- trary, the growth of knowledge follows MPP, such that all technological progress, even in the sense of energy-saving techniques, finally results in growing energy throughputs, hence ulti- mately the absolute growth of entropy production.
Econometric estimations of long-run growth have shown that the standard residual for techno- logical knowledge can be substituted by a measure that reflects the throughput of useful work in the economy (Ayres and Warr 2003, 2005, Warr et al. 2008, compare Kümmel 1998), which corresponds to the MPP as it is used by Vermeij (2004) or Odum (2008). For founding this empirical observation theoretically, and contrary to earlier views on the use of entropy in ecological economics (see the critique by Bünstorf 2004), we do not need to refer to the Sec- ond Law directly, which necessarily fails because the Earth system is an open system con- tinuously fed by solar energy. In place of this, we now argue that the dynamically evolving economy manifests a physical tendency to establish structural features in technologies and institutions which increase the gradients of energy dissipation and hence entropy production, and that these features correspond to embodied knowledge (cf. Annila and Salthe 2009). In the previously mentioned econometric investigations, these structural features are caught in the efficiency of the conversion of potential work, i.e. exergy, into useful work. This corre- sponds to the constructal law, as overview in figure 7. Growth follows a path pointing to- wards the maximization of useful work, hence following MPP (cf. Smil 2008: 380). In turn, this relates with MEPP, as the ultimate direction taken by economic evolution.
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In this sense, based on the Peircian approach we can undergird Georgescu-Roegen’s funda- mental proposition, though correcting its theoretical justification, namely that economic growth follows the Second Law, precisely because we take heed of the growth of knowledge. Hence, the growth of knowledge cannot solve the entropic dilemma. Actually, it is a part of it.
This conclusion does not necessarily support doomsday scenarios. Physically, human entropy production is a minuscule share in the entire thermodynamic flows in the sun-earth system and other geochemical forces (Gilett 2006). Global warming is a specific structurally caused phenomenon which could be remedied by appropriate technological changes, even while in- creasing entropy production in the physical sense. However, the Peircian argument increases the awareness that those structural changes, if engineered by human inventiveness, cannot change the physical nature of knowledge. The faster knowledge grows, the faster entropy will be produced.
Even though this insight does not necessarily implicate ecological disaster, there are some important conclusions even for applied economic analysis. In particular, it means that we suf- fer from a fundamental delusion if we expect that the progress of knowledge might eventually end up with a society that might live with less energy consumption in absolute terms. Sources of energy production will diversify, but the final result will always be increasing dissipation of energy. Thus, the central policy issue is not related to the production and consumption of energy, but to the mechanisms of entropy production, in the sense of how entropy is pro- duced, as distinguished from ‘that’. With regard to entropy production, the major problem is how far and in which way structural constraints cause entropy production to have locally det- rimental effects on ecosystems (such as pollution or global warming). Entropy production that is exported into the larger environment does not necessarily have a negative effect on ecosys- tem functioning. The major difficulty in understanding these constraints and their mechanisms is that we deal with complex non-linear systems, in which even small changes can trigger larger local effects which might run out of control, given the current state of knowledge.
Therefore, another policy view instigated by Georgescu-Roegen can be confirmed by our analysis. This is that a synthesis between the growth of knowledge and material conservativ- ism in systems design must be pursued. This refers to Georgescu-Roegen’s failed proposal to establish a fourth (or fifth) law of thermoydynamics which relates to the conservation of mat- ter. In the current context, this can be seen as factually referring to the idea that, given the complex non-linearities of change, the scale and scope of efficient-causal impacts of the growth of knowledge on the physical structures of the environment should be minimized, in order to maintain the current stability of systems. In practical terms, growth with structural conservatism means, for example, to create products that can be adapted to innovations, such that material waste production is kept at a minimum. This would expand the paradigm of ur- ban conservation programs onto the entire domain of product design. Beyond that, controlling structural features of ecosystems is fundamentally dependent on attitudes towards risk and uncertainty, which are themselves an endogenous variable to economic and cultural evolution.
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8 Conclusion
This paper proposes a conceptual synthesis between two lines of thinking that run totally se- parate from each other until now. One is Peirce’s triadism in the theory of signs, and the other is the Maximum Entropy approach in its different forms and applications. Going back to Peir- ce, this is possible because his philosophy was deeply impacted by the new developments of the sciences in his time, in particular, evolutionary theory and thermodynamics (Stone 2007: 117). Peirce’s philosophy builds on some fundamental principles which also define the core of these new theories, in particular, his tychism, i.e. the assumption of the fundamental ran- domness of the world. One of Peirce’s major questions was how to explain the emergence of regularities in a random world, which corresponds to the question how thermodynamics re- lates to evolution. The latter issue remains unresolved until today. The recent developments in the Maximum Entropy approach challenge established wisdom in heralding the slogan sur- vival of the likeliest . This slogan highlights the idea that evolution does not result into struc- tures which are less probable (in the Shannon sense, states of lower entropy), but to the con- trary, which are even the most probable ones, given certain constraints. Those structural fea- tures are the most probable ones which maximize the production of entropy, or, manifest the steepest and fastest gradients of energy dissipation, relative to the scope and time scale of the existence of the systems of which they form a part.
I have shown that this new theory can be applied to explain the growth of knowledge in the sense of the accumulation of new information and of the potential for new information. This explanation builds on Peirce’s theory of signs, strictly interpreted in naturalistic terms. Hence, I understand the growth of knowledge as a physical process. On a most fundamental level, Peirce’s triadism translates into the analytical conjunction of three different kinds of causality in semeiosis, efficient, formal and final. Only this conjunction allows for the explanation of the emergence of new information, i.e. the growth of knowledge. The conceptual linkage to thermodynamics is achieved in two steps. The first is to provide a naturalistic interpretation of the MaxEnt principle in the context of evolutionary epistemology, i.e. to substitute the Bayes- ian observer by the information generating evolutionary process, i.e. natural selection. The second is to relate this to the MEPP, with the MPP as an intermediating principle.
This approach offers a fresh view on the approach to ecological economics that had been se- minally proposed by Georgescu-Roegen. Georgescu-Roegen argued that evolution cannot be grasped by arithmomorphic concepts, which are mechanistically in the sense of efficient cau- sality. Yet, he has opened the way for the integration between economics and the sciences, especially physics. The inherent conceptual dilemmas can be solved in the context of a Peir- cian ontology and epistemology. This defines a research program in which categories tradi- tionally assigned to the humanities, such as meaning, can be related with physical concepts. This appears to be fruitful perspective for economics, which has been vacillating between the Geisteswissenschaften and the Naturwissenschaften since its inception.
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FRANKFURT SCHOOL / HFB – WORKING PAPER SERIES
No. Author/Title Year 145. Heidorn, Thomas / Kahlert, Dennis Implied Correlations of iTraxx Tranches during the Financial Crisis 2010 144 Fritz-Morgenthal, Sebastian G. / Hach, Sebastian T. / Schalast, Christoph M&A im Bereich Erneuerbarer Energien 2010 143. Birkmeyer, Jörg / Heidorn, Thomas / Rogalski, André Determinanten von Banken-Spreads während der Finanzmarktkrise 2010 142. Bannier, Christina E. / Metz, Sabrina Are SMEs large firms en miniature? Evidence from a growth analysis 2010 141. Heidorn, Thomas / Kaiser, Dieter G. / Voinea, André The Value-Added of Investable Hedge Fund Indices 2010 140. Herrmann-Pillath, Carsten The Evolutionary Approach to Entropy: Reconciling Georgescu-Roegen’s Natural Philosophy with the Maximum 2010 Entropy Framework 139. Heidorn, Thomas / Löw, Christian / Winker, Michael Funktionsweise und Replikationstil europäischer Exchange Traded Funds auf Aktienindices 2010 138. Libman, Alexander Constitutions, Regulations, and Taxes: Contradictions of Different Aspects of Decentralization 2010 137. Herrmann-Pillath, Carsten / Libman, Alexander / Yu, Xiaofan State and market integration in China: A spatial econometrics approach to ‘local protectionism’ 2010 136. Lang, Michael / Cremers, Heinz / Hentze, Rainald Ratingmodell zur Quantifizierung des Ausfallrisikos von LBO-Finanzierungen 2010 135. Bannier, Christina / Feess, Eberhard When high-powered incentive contracts reduce performance: Choking under pressure as a screening device 2010 134. Herrmann-Pillath, Carsten Entropy, Function and Evolution: Naturalizing Peircian Semiosis 2010 133. Bannier, Christina E. / Behr, Patrick / Güttler, Andre Rating opaque borrowers: why are unsolicited ratings lower? 2009 132. Herrmann-Pillath, Carsten
Social Capital, Chinese Style: Individualism, Relational Collectivism and the Cultural Embeddedness of the Instituti- 2009 ons-Performance Link 131. Schäffler, Christian / Schmaltz, Christian Market Liquidity: An Introduction for Practitioners 2009 130. Herrmann-Pillath, Carsten Dimensionen des Wissens: Ein kognitiv-evolutionärer Ansatz auf der Grundlage von F.A. von Hayeks Theorie der 2009 „Sensory Order“ 129. Hankir, Yassin / Rauch, Christian / Umber, Marc It’s the Market Power, Stupid! – Stock Return Patterns in International Bank M&A 2009 128. Herrmann-Pillath, Carsten Outline of a Darwinian Theory of Money 2009 127. Cremers, Heinz / Walzner, Jens Modellierung des Kreditrisikos im Portfoliofall 2009 126. Cremers, Heinz / Walzner, Jens Modellierung des Kreditrisikos im Einwertpapierfall 2009 125. Heidorn, Thomas / Schmaltz, Christian Interne Transferpreise für Liquidität 2009 124. Bannier, Christina E. / Hirsch, Christian The economic function of credit rating agencies - What does the watchlist tell us? 2009 123. Herrmann-Pillath, Carsten A Neurolinguistic Approach to Performativity in Economics 2009 122. Winkler, Adalbert / Vogel, Ursula
Finanzierungsstrukturen und makroökonomische Stabilität in den Ländern Südosteuropas, der Türkei und in den GUS- 2009 Staaten
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Private Equity und Familienunternehmen – eine Untersuchung unter besonderer Berücksichtigung deutscher 2008 Maschinen- und Anlagenbauunternehmen 106. Bannier, Christina E. / Grote, Michael H. Equity Gap? – Which Equity Gap? On the Financing Structure of Germany’s Mittelstand 2008 105. Herrmann-Pillath, Carsten The Naturalistic Turn in Economics: Implications for the Theory of Finance 2008 104. Schalast, Christoph (Hrgs.) / Schanz, Kay-Michael / Scholl, Wolfgang Aktionärsschutz in der AG falsch verstanden? Die Leica-Entscheidung des LG Frankfurt am Main 2008 103. Bannier, Christina E./ Müsch, Stefan Die Auswirkungen der Subprime-Krise auf den deutschen LBO-Markt für Small- und MidCaps 2008 102. Cremers, Heinz / Vetter, Michael Das IRB-Modell des Kreditrisikos im Vergleich zum Modell einer logarithmisch normalverteilten Verlustfunktion 2008 101. Heidorn, Thomas / Pleißner, Mathias Determinanten Europäischer CMBS Spreads. Ein empirisches Modell zur Bestimmung der Risikoaufschläge von Commercial Mortgage-Backed Securities (CMBS) 2008 100. Schalast, Christoph (Hrsg.) / Schanz, Kay-Michael Schaeffler KG/Continental AG im Lichte der CSX Corp.-Entscheidung des US District Court for the Southern District of New York 2008 99. Hölscher, Luise / Haug, Michael / Schweinberger, Andreas Analyse von Steueramnestiedaten 2008 98. Heimer, Thomas / Arend, Sebastian The Genesis of the Black-Scholes Option Pricing Formula 2008 97. Heimer, Thomas / Hölscher, Luise / Werner, Matthias Ralf Access to Finance and Venture Capital for Industrial SMEs 2008 96. Böttger, Marc / Guthoff, Anja / Heidorn, Thomas Loss Given Default Modelle zur Schätzung von Recovery Rates 2008
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95. Almer, Thomas / Heidorn, Thomas / Schmaltz, Christian The Dynamics of Short- and Long-Term CDS-spreads of Banks 2008 94. Barthel, Erich / Wollersheim, Jutta Kulturunterschiede bei Mergers & Acquisitions: Entwicklung eines Konzeptes zur Durchführung einer Cultural Due Diligence 2008 93. Heidorn, Thomas / Kunze, Wolfgang / Schmaltz, Christian Liquiditätsmodellierung von Kreditzusagen (Term Facilities and Revolver) 2008 92. Burger, Andreas Produktivität und Effizienz in Banken – Terminologie, Methoden und Status quo 2008 91. Löchel, Horst / Pecher, Florian The Strategic Value of Investments in Chinese Banks by Foreign Financial Insitutions 2008 90. Schalast, Christoph / Morgenschweis, Bernd / Sprengetter, Hans Otto / Ockens, Klaas / Stachuletz, Rainer / Safran, Robert Der deutsche NPL Markt 2007: Aktuelle Entwicklungen, Verkauf und Bewertung – Berichte und Referate des NPL Forums 2007 2008 89. Schalast, Christoph / Stralkowski, Ingo 10 Jahre deutsche Buyouts 2008 88. Bannier, Christina E./ Hirsch, Christian The Economics of Rating Watchlists: Evidence from Rating Changes 2007 87. Demidova-Menzel, Nadeshda / Heidorn, Thomas Gold in the Investment Portfolio 2007 86. Hölscher, Luise / Rosenthal, Johannes Leistungsmessung der Internen Revision 2007 85. Bannier, Christina / Hänsel, Dennis Determinants of banks' engagement in loan securitization 2007 84. Bannier, Christina “Smoothing“ versus “Timeliness“ - Wann sind stabile Ratings optimal und welche Anforderungen sind an optimale 2007 Berichtsregeln zu stellen? 83. Bannier, Christina E. Heterogeneous Multiple Bank Financing: Does it Reduce Inefficient Credit-Renegotiation Incidences? 2007 82. Cremers, Heinz / Löhr, Andreas Deskription und Bewertung strukturierter Produkte unter besonderer Berücksichtigung verschiedener Marktszenarien 2007 81. Demidova-Menzel, Nadeshda / Heidorn, Thomas Commodities in Asset Management 2007 80. Cremers, Heinz / Walzner, Jens Risikosteuerung mit Kreditderivaten unter besonderer Berücksichtigung von Credit Default Swaps 2007 79. Cremers, Heinz / Traughber, Patrick Handlungsalternativen einer Genossenschaftsbank im Investmentprozess unter Berücksichtigung der Risikotragfähig- keit 2007 78. Gerdesmeier, Dieter / Roffia, Barbara Monetary Analysis: A VAR Perspective 2007 77. Heidorn, Thomas / Kaiser, Dieter G. / Muschiol, Andrea Portfoliooptimierung mit Hedgefonds unter Berücksichtigung höherer Momente der Verteilung 2007 76. Jobe, Clemens J. / Ockens, Klaas / Safran, Robert / Schalast, Christoph Work-Out und Servicing von notleidenden Krediten – Berichte und Referate des HfB-NPL Servicing Forums 2006 2006 75. Abrar, Kamyar / Schalast, Christoph Fusionskontrolle in dynamischen Netzsektoren am Beispiel des Breitbandkabelsektors 2006 74. Schalast, Christoph / Schanz, Kay-Michael Wertpapierprospekte: Markteinführungspublizität nach EU-Prospektverordnung und Wertpapierprospektgesetz 2005 2006 73. Dickler, Robert A. / Schalast, Christoph Distressed Debt in Germany: What´s Next? Possible Innovative Exit Strategies 2006 72. Belke, Ansgar / Polleit, Thorsten How the ECB and the US Fed set interest rates 2006 71. Heidorn, Thomas / Hoppe, Christian / Kaiser, Dieter G. Heterogenität von Hedgefondsindizes 2006 70. Baumann, Stefan / Löchel, Horst The Endogeneity Approach of the Theory of Optimum Currency Areas - What does it mean for ASEAN + 3? 2006
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69. Heidorn, Thomas / Trautmann, Alexandra Niederschlagsderivate 2005 68. Heidorn, Thomas / Hoppe, Christian / Kaiser, Dieter G. Möglichkeiten der Strukturierung von Hedgefondsportfolios 2005 67. Belke, Ansgar / Polleit, Thorsten (How) Do Stock Market Returns React to Monetary Policy ? An ARDL Cointegration Analysis for Germany 2005 66. Daynes, Christian / Schalast, Christoph Aktuelle Rechtsfragen des Bank- und Kapitalmarktsrechts II: Distressed Debt - Investing in Deutschland 2005 65. Gerdesmeier, Dieter / Polleit, Thorsten Measures of excess liquidity 2005 64. Becker, Gernot M. / Harding, Perham / Hölscher, Luise Financing the Embedded Value of Life Insurance Portfolios 2005 63. Schalast, Christoph Modernisierung der Wasserwirtschaft im Spannungsfeld von Umweltschutz und Wettbewerb – Braucht Deutschland 2005 eine Rechtsgrundlage für die Vergabe von Wasserversorgungskonzessionen? – 62. Bayer, Marcus / Cremers, Heinz / Kluß, Norbert Wertsicherungsstrategien für das Asset Management 2005 61. Löchel, Horst / Polleit, Thorsten A case for money in the ECB monetary policy strategy 2005 60. Richard, Jörg / Schalast, Christoph / Schanz, Kay-Michael Unternehmen im Prime Standard - „Staying Public“ oder „Going Private“? - Nutzenanalyse der Börsennotiz - 2004 59. Heun, Michael / Schlink, Torsten Early Warning Systems of Financial Crises - Implementation of a currency crisis model for Uganda 2004 58. Heimer, Thomas / Köhler, Thomas Auswirkungen des Basel II Akkords auf österreichische KMU 2004 57. Heidorn, Thomas / Meyer, Bernd / Pietrowiak, Alexander Performanceeffekte nach Directors´Dealings in Deutschland, Italien und den Niederlanden 2004 56. Gerdesmeier, Dieter / Roffia, Barbara The Relevance of real-time data in estimating reaction functions for the euro area 2004 55. Barthel, Erich / Gierig, Rauno / Kühn, Ilmhart-Wolfram Unterschiedliche Ansätze zur Messung des Humankapitals 2004 54. Anders, Dietmar / Binder, Andreas / Hesdahl, Ralf / Schalast, Christoph / Thöne, Thomas Aktuelle Rechtsfragen des Bank- und Kapitalmarktrechts I : Non-Performing-Loans / Faule Kredite - Handel, Work-Out, Outsourcing und Securitisation 2004 53. Polleit, Thorsten The Slowdown in German Bank Lending – Revisited 2004 52. Heidorn, Thomas / Siragusano, Tindaro Die Anwendbarkeit der Behavioral Finance im Devisenmarkt 2004 51. Schütze, Daniel / Schalast, Christoph (Hrsg.) Wider die Verschleuderung von Unternehmen durch Pfandversteigerung 2004 50. Gerhold, Mirko / Heidorn, Thomas Investitionen und Emissionen von Convertible Bonds (Wandelanleihen) 2004 49. Chevalier, Pierre / Heidorn, Thomas / Krieger, Christian Temperaturderivate zur strategischen Absicherung von Beschaffungs- und Absatzrisiken 2003 48. Becker, Gernot M. / Seeger, Norbert Internationale Cash Flow-Rechnungen aus Eigner- und Gläubigersicht 2003 47. Boenkost, Wolfram / Schmidt, Wolfgang M. Notes on convexity and quanto adjustments for interest rates and related options 2003 46. Hess, Dieter Determinants of the relative price impact of unanticipated Information in 2003 U.S. macroeconomic releases 45. Cremers, Heinz / Kluß, Norbert / König, Markus Incentive Fees. Erfolgsabhängige Vergütungsmodelle deutscher Publikumsfonds 2003 44. Heidorn, Thomas / König, Lars Investitionen in Collateralized Debt Obligations 2003 43. Kahlert, Holger / Seeger, Norbert Bilanzierung von Unternehmenszusammenschlüssen nach US-GAAP 2003
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42. Beiträge von Studierenden des Studiengangs BBA 012 unter Begleitung von Prof. Dr. Norbert Seeger Rechnungslegung im Umbruch - HGB-Bilanzierung im Wettbewerb mit den internationalen 2003 Standards nach IAS und US-GAAP 41. Overbeck, Ludger / Schmidt, Wolfgang Modeling Default Dependence with Threshold Models 2003 40. Balthasar, Daniel / Cremers, Heinz / Schmidt, Michael Portfoliooptimierung mit Hedge Fonds unter besonderer Berücksichtigung der Risikokomponente 2002 39. Heidorn, Thomas / Kantwill, Jens Eine empirische Analyse der Spreadunterschiede von Festsatzanleihen zu Floatern im Euroraum und deren Zusammenhang zum Preis eines Credit Default Swaps 2002 38. Böttcher, Henner / Seeger, Norbert Bilanzierung von Finanzderivaten nach HGB, EstG, IAS und US-GAAP 2003 37. Moormann, Jürgen Terminologie und Glossar der Bankinformatik 2002 36. Heidorn, Thomas Bewertung von Kreditprodukten und Credit Default Swaps 2001 35. Heidorn, Thomas / Weier, Sven Einführung in die fundamentale Aktienanalyse 2001 34. Seeger, Norbert International Accounting Standards (IAS) 2001 33. Moormann, Jürgen / Stehling, Frank Strategic Positioning of E-Commerce Business Models in the Portfolio of Corporate Banking 2001 32. Sokolovsky, Zbynek / Strohhecker, Jürgen Fit für den Euro, Simulationsbasierte Euro-Maßnahmenplanung für Dresdner-Bank-Geschäftsstellen 2001 31. Roßbach, Peter Behavioral Finance - Eine Alternative zur vorherrschenden Kapitalmarkttheorie? 2001 30. Heidorn, Thomas / Jaster, Oliver / Willeitner, Ulrich Event Risk Covenants 2001 29. Biswas, Rita / Löchel, Horst Recent Trends in U.S. and German Banking: Convergence or Divergence? 2001 28. Eberle, Günter Georg / Löchel, Horst Die Auswirkungen des Übergangs zum Kapitaldeckungsverfahren in der Rentenversicherung auf die Kapitalmärkte 2001 27. Heidorn, Thomas / Klein, Hans-Dieter / Siebrecht, Frank Economic Value Added zur Prognose der Performance europäischer Aktien 2000 26. Cremers, Heinz Konvergenz der binomialen Optionspreismodelle gegen das Modell von Black/Scholes/Merton 2000 25. Löchel, Horst Die ökonomischen Dimensionen der ‚New Economy‘ 2000 24. Frank, Axel / Moormann, Jürgen Grenzen des Outsourcing: Eine Exploration am Beispiel von Direktbanken 2000 23. Heidorn, Thomas / Schmidt, Peter / Seiler, Stefan Neue Möglichkeiten durch die Namensaktie 2000 22. Böger, Andreas / Heidorn, Thomas / Graf Waldstein, Philipp Hybrides Kernkapital für Kreditinstitute 2000 21. Heidorn, Thomas Entscheidungsorientierte Mindestmargenkalkulation 2000 20. Wolf, Birgit Die Eigenmittelkonzeption des § 10 KWG 2000 19. Cremers, Heinz / Robé, Sophie / Thiele, Dirk Beta als Risikomaß - Eine Untersuchung am europäischen Aktienmarkt 2000 18. Cremers, Heinz Optionspreisbestimmung 1999 17. Cremers, Heinz Value at Risk-Konzepte für Marktrisiken 1999 16. Chevalier, Pierre / Heidorn, Thomas / Rütze, Merle Gründung einer deutschen Strombörse für Elektrizitätsderivate 1999
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15. Deister, Daniel / Ehrlicher, Sven / Heidorn, Thomas CatBonds 1999 14. Jochum, Eduard Hoshin Kanri / Management by Policy (MbP) 1999 13. Heidorn, Thomas Kreditderivate 1999 12. Heidorn, Thomas Kreditrisiko (CreditMetrics) 1999 11. Moormann, Jürgen Terminologie und Glossar der Bankinformatik 1999 10. Löchel, Horst The EMU and the Theory of Optimum Currency Areas 1998 09. Löchel, Horst Die Geldpolitik im Währungsraum des Euro 1998 08. Heidorn, Thomas / Hund, Jürgen Die Umstellung auf die Stückaktie für deutsche Aktiengesellschaften 1998 07. Moormann, Jürgen Stand und Perspektiven der Informationsverarbeitung in Banken 1998 06. Heidorn, Thomas / Schmidt, Wolfgang LIBOR in Arrears 1998 05. Jahresbericht 1997 1998 04. Ecker, Thomas / Moormann, Jürgen Die Bank als Betreiberin einer elektronischen Shopping-Mall 1997 03. Jahresbericht 1996 1997 02. Cremers, Heinz / Schwarz, Willi Interpolation of Discount Factors 1996 01. Moormann, Jürgen Lean Reporting und Führungsinformationssysteme bei deutschen Finanzdienstleistern 1995
FRANKFURT SCHOOL / HFB – WORKING PAPER SERIES CENTRE FOR PRACTICAL QUANTITATIVE FINANCE
No. Author/Title Year 23. Esquível, Manuel L. / Veiga, Carlos / Wystup, Uwe 2010 Unifying Exotic Option Closed Formulas 22. Packham, Natalie / Schlögl, Lutz / Schmidt, Wolfgang M. Credit gap risk in a first passage time model with jumps 2009 21. Packham, Natalie / Schlögl, Lutz / Schmidt, Wolfgang M. Credit dynamics in a first passage time model with jumps 2009 20. Reiswich, Dimitri / Wystup, Uwe FX Volatility Smile Construction 2009 19. Reiswich, Dimitri / Tompkins, Robert Potential PCA Interpretation Problems for Volatility Smile Dynamics 2009 18. Keller-Ressel, Martin / Kilin, Fiodar Forward-Start Options in the Barndorff-Nielsen-Shephard Model 2008 17. Griebsch, Susanne / Wystup, Uwe On the Valuation of Fader and Discrete Barrier Options in Heston’s Stochastic Volatility Model 2008 16. Veiga, Carlos / Wystup, Uwe Closed Formula for Options with Discrete Dividends and its Derivatives 2008 15. Packham, Natalie / Schmidt, Wolfgang Latin hypercube sampling with dependence and applications in finance 2008 14. Hakala, Jürgen / Wystup, Uwe FX Basket Options 2008
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13. Weber, Andreas / Wystup, Uwe Vergleich von Anlagestrategien bei Riesterrenten ohne Berücksichtigung von Gebühren. Eine Simulationsstudie zur 2008 Verteilung der Renditen 12. Weber, Andreas / Wystup, Uwe Riesterrente im Vergleich. Eine Simulationsstudie zur Verteilung der Renditen 2008 11. Wystup, Uwe Vanna-Volga Pricing 2008 10. Wystup, Uwe Foreign Exchange Quanto Options 2008 09. Wystup, Uwe Foreign Exchange Symmetries 2008 08. Becker, Christoph / Wystup, Uwe Was kostet eine Garantie? Ein statistischer Vergleich der Rendite von langfristigen Anlagen 2008 07. Schmidt, Wolfgang Default Swaps and Hedging Credit Baskets 2007 06. Kilin, Fiodor Accelerating the Calibration of Stochastic Volatility Models 2007 05. Griebsch, Susanne/ Kühn, Christoph / Wystup, Uwe Instalment Options: A Closed-Form Solution and the Limiting Case 2007 04. Boenkost, Wolfram / Schmidt, Wolfgang M. Interest Rate Convexity and the Volatility Smile 2006 03. Becker, Christoph/ Wystup, Uwe On the Cost of Delayed Currency Fixing 2005 02. Boenkost, Wolfram / Schmidt, Wolfgang M. Cross currency swap valuation 2004 01. Wallner, Christian / Wystup, Uwe Efficient Computation of Option Price Sensitivities for Options of American Style 2004
HFB – SONDERARBEITSBERICHTE DER HFB - BUSINESS SCHOOL OF FINANCE & MANAGEMENT
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