A conceptual sitemap

This website is an open repository of concepts, definitions and further information on evolutionary economics. It will be amended and enlarged continously, being a network as this is the case with the object of EE, that is economic systems. As I have already explained, the relation between the concepts is not strictly ordered, but is explicit in the fuzzy semantic fields in which ideas are related to each other. This entry will present a summary impression of these fields that make up the entire mind map of EE.

There are basic concepts (always on top of the fields), intermediate and specific ones, with the latter closely related to analytical techniques, the intermediate to hypotheses and the first to ontological assumptions.

Ontological assumptions are of a very general kind. One starting point is to understand the economy as consisting of >systems that maintain >order via matter-energy flows across their boundaries. This is grasped by the concepts of >entropy, >energy and >order and provides the fundamentals of one branch of EE, ecological economics. An economic system is continuous >production, with consumption simply being an intermediate stage of production, and not a final objective.

How is order created? Well, if there is no exogenous creator (at least for single systems, we refrain from any religious implications), >evolution is the only process that we know which leads to the endogenous emergence of order. How does evolution work? The most basic mechanism is >variation, selection and retention, which, however, is evolving, too, in terms of the specific processes underlying these three phenomena. The evolution of evolution is the precondition for generalizing certain hypotheses of evolutionary theory across disciplines like biology and economics, like, for example, the theory of >hypercycles as a mechanism of the emergence of novelty. This generalization has to be done with great methodological care.

Economics and evolutionary theory are closely related anyway, because the possibility of >novelty emerging from evolution presupposes a situation where abundant variations of systems are selected in an environment that is characterized by a state of relative scarcity of the resources that are needed for maintaining their state of order. Hence, EE implies the idea of a universal economy. The relation between EE and so-called mainstream economics can be clarified here: Given scarcity, in closed systems general formal principles like Lagrange optimization work, which lie at the core of equlibrium analysis. This is the mainstream approach, hence simply a special case of general systems theory in EE, which focuses on non-equilibrium, open systems.

From this follows another important conclusion. Every state of order that emerges from evolution can be said to represent >knowledge about the functional relations that make this state possible. Evolutionary theory implies that the world is knowledge. This is called the principle of >bimodality: Every observed regularity can be interpreted as a >rule representing knowledge. This entails the methodological guideline always to try to figure out a >meaning of the regularity, because the meaning helps us to identify the rule and to relate this to the function of the regularity. In evolutionary theory, meaning and function are two sides of the same coin, and the task of science is to get both related to the same and the right coin. This means that there is no fundamental difference between "Verstehen" (Understanding) and "Erklären" (Explaining), or between "Geisteswissenschaft" and "Naturwissenschaft".

In that context, one of the most interesting research issues is to understand the rules determining human >action and which make up the >capacity to act. The knowledge on which human action is based is a very complex structure of rules, which are partly referential (like knowledge of mathematics) and partly non-referential (like inborn capabilities). No human individual fully knows the meaning of his knowledge. Hence, the obvious fact that knowledge always contains self-referential knowledge has far-reaching implications for scientific analysis, which are, again, ontological in nature. There are several >impossibility theorems related to self-referential knowledge that in turn provide the theoretical rationale for basic ontological presumptions like >singularity. Singularity implies that the general theoretical structures that we use in explanations necessarily have to distinguish between individual phenomena and >population level phenomena, the latter resulting from the patterns of variety on the individual
level. There are many methodological implications of this so-called "population thinking", as, for example, the importance of >taxonomy in evolutionary explanations. Taxonomy is a way to get hold of structures of knowledge.

For economics, this leads to a new definition of its core concern, namely that economics investigates into the role of knowledge and ignorance for human action in economic systems, and how knowledge is created and maintained. Every economy is a knowledge economy, and scarcity is always relative to knowledge. For the application of evolutionary analysis, important modifications of basic evolutionary hypotheses have to be made because human action includes mental phenomena, communication and interaction. To get hold of this, EE regards economic systems as >networks of >transaction, >communication and >perception. As opposed to traditional equilibrium approaches, these networks are conceived as being non-integral, that is there is a specific structure of linkages and non-linkages. The >market is a special kind of network, with money serving as a primordial means of communication. Non-integral networks cannot be understood in terms of >equilibrium analysis, apart from the use of equilibrium as stable patterns of
mutual expectations. There are different special methods to analyze networks, as for example, the theory of >games.

Networks, hence, show regularities. These are >institutions, which, therefore, are a special kind of knowledge in terms of their rules. Institutions are one aspect of structure in economic systems. Another important one is >technology, which results from human action in economic systems to maintain order as matter-energy. The third primordial structure is >power. Power is fundamental in economic systems because competition in networks always works in two dimensions, i.e. efficiency/efficacy and status (which is a specification of frequency-independent and frequency-dependent selection). Power also results from the functional need to stabilize institutions through sanctions. Since this is in turn dependent on institutions, evolution in economic systems necessarily appears to be a multi-level process with phenomena like >group selection. The totality of structures is called order. In economic systems, order is bimodally related to >culture, with order being the functional and culture being the meaning side of the coin.

Evolutionary analysis of economic systems is shaped by fundamental premises as well as specific methodological requirements. For example, the analysis of institutions may focus on understanding how certain distributions of knowledge across actors leads to the emergence of institutions to stabilize expectations facing uncertainty and partial ignorance. Doing this, patterns of >time may become important, because changes in the economy occur with divergent speed and frequency on different systemic levels. Another question is how technology evolves over time. Here, attention has to be paid to interactions between market structures and firm organizations, where the knowledge is stored guiding the application of technology. Very often, these complex processes cannot be observed directly. Researchers try to understand the underlying mechanisms via >simulation and compare resulting surface patterns with empirical data. Other research aims at understanding long-run phenomena which requires the use of history. Human action in history, however, is embued with meaning, so that a grasp of hermeneutics becomes indispensible. A last example is to understand human decision making, where EE rejects the standard concept of rationality and instead takes >reason as the fundamental concept. Reason is the complex result of the evolution of rules, which are stored in patterns of >cognition and >emotion. To research into these rules, EE turns to methods like experimental economics.

Evolutionary Economics, broadly understood, is science with a special twist: The world is knowledge, and we stay in ignorance, but have to act. This is the fundamental starting point for evolutionary pragmatics and normative recommendations given by EE. There are some general rules for evolutionary pragmatics, as, for example, never claim and pretend almost perfect knowledge, or never forget that any action has many unintended consequences.

This is a simple map of the labyrinth into which you can enter now. The entry is: