The Extended Order in the lens of Complexity — Revelation for Complexity Economics


In our previous articles, we attempted to explain the fundamental order of incumbent financial systems via the lens of the Extended Order proposed by Hayek. We also introduced the differences between debt based extended layers and organic growth based constructive extended layers. Later, we illustrated the relationship between financial bubbles and Ponzi Schemes. Most recently, we have extended our focus onto the study of complex adaptive systems. You might ask, what is the relationship between Extended Order and complex system theory? We seek to answer that question in this article by demonstrating the difficulties Hayek faced when he was examining the emergence of the Extended Order. We will attempt to explain the differences between a complexity perspective and a traditional view. Finally we seek to demonstrate that complex adaptive system is a necessary model in the careful elaboration of the economic system implied by the Extended Order.

1. The Foresight of Hayek

The latter half of Hayek’s career saw witness to the birth of many works that were difficult to understand. In Hayek’s cognitive system, implied knowledge is the more important type of human knowledge when compared to knowledge that can be explained or identified. However, it is this type of discernible but unexplainable knowledge that created a fundamental problem for Hayek: “Dilemma of Expression”.

To Hayek, a “fuzzy” mind is more creative than a “clear” mind. He believed that wisdom that can only be felt is closer to the source of human creativity than wisdom that can be expressed rationally. The ideal economic system would thus be a type of self-organized order that is gently induced rather than the type of order that is forcefully put together through the strict control of every element of the system.

An emergent order is created by a set of interrelated building blocks. These building blocks will create specific circumstances in which agents can form expectations about the behaviors of others using their own knowledge and in turn moderate their own behaviors to prove the accuracy of these expectations.

Human rationality does not seem to be sufficient in the study of the Extended Order. More importantly, effective methods to examine the formation of intuitive knowledge did not exist in Hayek’s time.

Let us construct a thought experiment. Imagine a fantastical scenario where an idiot savant appeared before us. There exists a very creative original idea inside of his mind (at least he claims it to be so). Unfortunately, because no one can comprehend him, when he explains the idea to us, no one can make sense of the symbols in the idea. It is only when the original idea is actualized and implemented would the savant complained:” See, I told you so, this it the fruit of my idea!” If you are face to face to such an idiot savant, what would you think? If no one understood this “very creative idea” before its implementation, then what would be the use of such an idea?

If you are Morty, and Rick was telling you all about his doubtlessly very creative ideas, the best you can do is shrug your shoulders.

Hayek once expressed the sentiment that emergent order is a truly complex phenomenon. Its spontaneous emergence relies upon its accumulating strength. Meanwhile, this spontaneity often completely escapes the senses of those who are its contemporaries and whose actions eventually lead to its spontaneous emergence.

Luckily, Hayek was referring to descriptive language, whereas language has more than one dimension. The duality of language allows this obscure and unproven theory of Hayek to be accepted by a few believers who can understand the intricacies within. The problem is that evidence of the Extended Order is hard to be developed and thus it has been difficult to further extend Hayek’s theoretical framework.

2. Complexity perspective in a social network structure

You might ask, “Where is the problem?” It may be that Hayek had looked too far into the future. He saw the blueprint for a future economy but lacked the necessary technologies and social developments to make it come true. When Hayek had finished his landmark exposition “The Fatal Deceit”, that was just when Microsoft DOS became popular, when the era of personal computer began, when Santa Fe Institute started researching on complex system, and before World Wide Web was born.

Although Hayek had the foresight, without the assistance of computer and multi-agent simulation, he could only study individual agent through observations. Moreover, because the contemporary world was dominated by highly ordered, mechanistic and formulaic world view that mostly concerned itself with static expositions, a theory that sought to depict a dynamic world order that is formed by emergent mechanisms would be deemed alien and obscure even with the clearest language and to the most prepared minds.

What about a complexity perspective? When I was first faced with his question, many words surged into my mind and made it difficult to explain succinctly what complexity really is. Perhaps it is the change in perspective that is more difficult than changes in research techniques or methods of argument. Changes in perspectives also require people to adjust their beliefs, which are often extremely difficult. Unless it is necessary, people probably wouldn’t change the lens through which they seek to make sense of things. In other words, when people are prepared to change their perspectives, everything will look different, in which case the need to reinterpret everything becomes very pressing. Here we employed the explanatory framework of complex economics to illustrate the complexity perspective through cognitive layer, structural layer and procedural mechanism.

On the cognitive layer, single dominant models will be gradually replaced by multi-agent distributed models. In the process of constructing behavioral agents, we no longer need to assume agents will have common knowledge about each other, even less so that they should have the same ideal expectations based on common knowledge. In other words, there shouldn’t be a common standard which everyone looks to as guidance for its own actions. Agents with varied behaviors will independently construct their own understanding of the problems they are facing they are giving meaning to the world they are facing while using their limited cognitive resources to make decisions that would determine their actions. In this way, we no longer have to make the assumption that everyone’s actions must follow profit maximization principal, instead allowing each independent agent to act freely so long as the aggregate is operating in an ordered manner.

In terms of structure, network-oriented structure will be emphasized in a complexity perspective. In the lens of complexity, multi-agents will interact via network structures, properties such as the relative density of network connections will demonstrate the connected nature of such a systematic outlook. Meanwhile, the differentiated actions of multi-agents will lead to the emergence of new social roles as the social network changes; network organization has recursive properties. Reciprocity will have an impact between multiple layers of the organization.

In comparison to the search of an ultimate target, a complexity perspective emphasizes the recording and discovery of how new things are formed and developed. In the traditional optimization perspective, if the aggregate possessed a blueprint of the future, then we certainly can predict it; even if it is far into the future, the aggregate can still maintain this “bias” for quite some time. In a complexity perspective, this deterministic future which can be predicted loses its appeal. In its place is the focus on process and the emergence of new orders. Therefore, temporal variable is a significant variable to this perspective. Age, generational replacement is thus at the core of the process-oriented framework of complexity. Previously, we examined society the way we would examine a static physical container. Under the scope of complexity, we must examine society as an organism that has its own structure, evolutionary process, self-organization mode as well as life cycle.

Below is a comparative list that shows the differences between a complexity perspective and our traditional perspective:

3. Complexity Economics is Crucial to the Study of the Extended Order

Complexity economics pays particular attention to the formation of patterns, the changes in structures, innovation and the consequence of perpetual creative destruction. In its essence, it is the economics concerning the emergence phenomenon. Brian Arthur, the founder of complexity economics, repeatedly emphasized that complexity economics is not a branch of equilibrium economics. Instead, equilibrium economics is a peculiar case of complexity economics. The formation of economic structures and the evolution of technology through aggregation and reconfiguration are two main sources of inquiries for complexity economics, both have significant implications for the research of the Extended Order.

1. The Formation of Economies

There are two important questions in the field of economics, the first is the problem of distribution within an economy, the second is the formation of economic structures. Traditional economics is primarily engaged in the research of resource distribution within a stable economy. In such a system, the number of conditions and variables are considered stable and controllable, which is conducive to modelling. To answer why and how economic structures form is an entirely different enterprise.

Economics that is based on equilibrium models generally see the economy as a monotonous and rather static process of changes in existing economic conditions. Such treatment equates technology with production function while regarding economy as a carrier for contemporary technologies. Naturally, the appearance of new technologies will improve the production function as well as increase the quantities of goods produced. Labor and input resources will thus have higher level of productivity per unit. Consequently, as more wealth is invested into the invention of new technologies, the economy will move smoothly from one equilibrium point to another. The biggest problem with this model is that technologies that can become disruptive driving forces or have transformative power on the economic activities have little significance in the model, merely becoming conditioners of price and quantity. Such model describes the world mainly through changes in price and quantities without any considerations to changes in the economic structures.

2. Evolution of the Support System for Technology set

If we make the assertion that new technology set (a set of technologies that are mutually exclusive) indeed has the power to bring about disruptive changes to existing economic structures, then we will be able to trace the evolutionary process of technology set. In the process we can attempt to study the reinvigoration of economies through new technology sets, and how these new sets integrate into a supporting set that sees new technology set challenges each other to grow and invents new solutions to each other’s problems. As time goes by, this supporting set will lead to continuous changes of the economic structures. Such is the methodology of complexity economics. Below is the basic structural “algorithm” of complexity economics:

The algorithmic steps above is derived from Brian Arthur’s “Complexity Economics”. If we take a deeper look at these steps, would we not see its remarkable resemblance with the process of extension for new layers within the Ponzi Structures ( In fact, it seems like a clearer and more structured rendition of the extension of capital layers in the Extended Order in our first few articles.

This similarity should not be seen as a coincidence, rather, were Hayek born 50 years later, he might be equally surprised at the constructive capabilities of complexity economics. In fact, many concepts introduced by the Austrian School of Economics are very similar to those in the complex system framework. One can even say that complexity economics has only algorithmized and computerized the Austrian view for the 21st century.

3. Deducing the landscape of future economy

Last but not least, let us use this “algorithm“ we have just gone through to make some predictions about how the future economy will come into being.

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1. W. Brian Arthur, “Complexity and the Economy”;

2. Friedrich August Von Hayek, “The Fatal Deceit“;

3. Edgar E. Peters, “Complexity, Risk and Financial Markets”;

4. Dingding Wang, “Handouts of Behavioral Economics”;

5. Melanie Swan, “Blockchain: Blueprint for a New Economy”;



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