Standard Economic Theory

Updated: Dec 1, 2020

In this Article, we will be taking a brief overview of the internals workings of the standard theory of economics. We talk about how it is a framework that applies linear systems theory to economic analysis. In so doing, it defines the economy as a closed system, the core structure of which being a general equilibrium between supply and demand leading to a framework that is often defined as the “rationality-individualism-equilibrium nexus.” We discuss this idea of rationality of agent behavior, that is, individuals making consistent choices in isolation. We talk about zero sum interactions between agents and how methodological individualism de-promotes any conception of institutions beyond that of pure market mechanisms, which is seen to be the optimal method for macro-scale resource allocation. Finally, we talk about how linear systems theory gives us a certain view of economic dynamics that sees change coming from exogenous factors and economic development as an increase in gross throughput to the system.

This paper will not be a critic. If you are reading this paper, you would have probably heard many of the critiques leveled against standard economic theory. The limitations of our standard economic framework are not superficial. They are systemic in nature, meaning they are part of the very foundations and fabric of the framework. What we will be trying to do here is get an idea of why our traditional economic framework is the way it is. From this, we should gain a greater appreciation for it and gain a true understanding of where its limitations lie. Key to understanding this is in understanding what we call linear system theory. So we will spend quite a bit of time talking about that first.

Standard Economic Theory

The first thing we need to appreciate is that standard economics wants to be a quasi-hard science. It is quite explicit about the fact that it does not wish to be seen as a so-called soft science like sociology or anthropology. Hard sciences are what they are because they are supported by a formal mathematical language through which everything can be decisively proven to be correct or incorrect within that logical framework, and this rigor gives them their so-called hardness. Formal mathematical proofs and equations are the gold standards in terms of validation within modern science, and traditional economics wants this gold standard of validation. The important thing for us to note here is that in order to achieve this, it has adopted a particular theoretical framework. This framework is called linear systems theory.

Linear systems theory is a mathematical modeling framework that was most coherently formalized by Sir Isaac Newton and then fleshed out within the development of classical physics some three to four hundred years ago, where it has many successes. It has gone on to form the backbone of modern science. Economics like many other areas of science adopted this framework during the 19th century because it is a very abstract powerful framework, and by formalizing your theories within this framework you can get access to quite advanced mathematical machinery, the kind that supported classical physics such as linear algebra, calculus, differential equations and so on. In short, if you wanted to be a respected science in the 18th, 19th and much of the 20th century you had to adopt linear systems theory and that is what economics did.

Formal Languages

Linear systems theory is the dominant formal language behind mainstream economics. If you want to formalize an economic theory in standard economics then linear systems theory is largely all you have. Thus, everything has to fit into this formal language. Formal languages have alphabets and syntax that enable valid expressions. There are things that you can encode into that language and express within it, and there are things that you cannot encode or express with the language. Trying to use a formal programming language like C++ in order to describe the feeling of guilt would be a lost endeavor. That formal language was not designed to encode or communicate such a phenomena, it will not give you the vocabulary or methods for properly expressing such things, it may capture certain aspects but much will be left out. This is very much the same with standard economics it is using a language that is best suited for talking about simpler linear systems – as are commonly found in physics – and its limitations become apparent when presented with trying to encode and communicate more complex phenomena that lie at the heart of economic reality.

Linear Systems Theory

A full discussion to the internal workings of linear systems theory is beyond the scope of this paper. But in its essence, linear systems theory deals with closed systems. Close systems tend towards equilibrium. Equilibrium is a point of stasis where different forces acting on the system are counterbalanced. You can then use this concept of equilibrium as the “normal” state of the system and describe it in terms of the different forces acting on it and how they will drive it back to the equilibrium state. Likewise closed linear systems obey the additivity principle, meaning the whole is equal to the sum of its parts. The whole is never anything other than the sum of its parts. This is an important assumption that it is necessary to make if you want to get nice closed form equation based models.

Closed Systems

In order to use linear systems theory, it is necessary to define a closed system, and the primary aim is to identify an equilibrium within that system around which there is a balancing negative feedback loop. Standard economics has integrated economics with linear systems theory by defining equilibrium points such as supply and demand, and this is key to understanding why it is the way it is because everything has to come back to this equilibrium as the “normal” state to the system. What you do from here is assume this general equilibrium and then work backward by asking what rules governing the behavior of actors would result in this equilibrium. If you can come up with a theory to do that then you will be able to create a closed form equation based solution, and that is the primary aim of models within standard economics.

This means that standard economics does not ask, what choices do people make and what are the outcomes of those choices – which would appear to be the obvious questions to ask. But instead, because it is based upon the premise of the outcome already being an equilibrium, it has to work backward assuming there will be an equilibrium and then asking what agent behavior is consistent with that outcome. This places significant constraints and limitations on the whole framework as it will limit how agents act before we even go and get empirical data as to how they actually act. This is a constraint that leads to a number of problems further down the line when it is confronted with how people really act.

Individual Agents

This leads us to the model of agents within standard economics. Standard economics is sometimes described as being defined by what is called the “rationality-individualism-equilibrium nexus.” It is like this because this is how one needs to model individual economic agents in order to get general equilibrium, and thus make it compatible with linear systems theory. This is called rational expectation or model consistent expectation. Because everything has to add up to zero in the end in order to get a closed-form linear solution, the agents have to act in a rational fashion. Where rational is defined as acting in their own consistent, purely economic self-interest and out of the suppliers and the producers acting in this rational fashion we will get our negative feedback loop and the model will work.

In the standard view, economic agents are defined as rational actors, that is to say, agents that are governed by a logic of rational choice. Rational choice is defined to mean the process of determining what options are available, and then choosing the preferred one according to some consistent and independent criterion, with each agent performing this process autonomously according to their own well-defined preferences, thus each essentially performing an optimization algorithm. One thing to note is that these are expectation models, which means that they are not really saying that this is how agents act, but instead that this is how they should act in order to get our general equilibrium.


Next, we will talk about the standard theory of value. Within standard economics, economic value is a single homogenous variable that is well defined. It is a measure of the benefits provided by a good or service to an economic agent, what is called utility. Utility is a measure of preferences over some set of goods and services. The concept is an important underpinning of rational choice theory. Utility is an important concept in economics and game theory because it represents satisfaction experienced by the consumer of a good. A good is something that satisfies human wants. Since one cannot directly measure benefit, satisfaction or happiness from a good or service, economists instead have created ways of representing and measuring utility in terms of economic choices that can be measured. Utility is revealed in people’s willingness to pay different amounts for different goods.

This is determined primarily by the demand for the object relative to supply in a perfectly competitive market. Many neoclassical economic theories equate the value of a commodity with its price, whether the market is competitive or not. As such, everything is seen as a commodity and if there is no market to set a price then there is no economic value. This is, of course, an extrinsic formalization of economic value. Value is relative and it is relative to scarcity and competition.

Market Failures

Of course, there is no mention of intrinsic secondary value here, that is the value that an entity may have independent of an individual’s evaluation of it – such as a tree might have in providing ecosystems services to maintain a functioning ecosystem. There is no real way of defining secondary value or converting it into primary value. Thus, this formalization of value creates a dichotomy between primary economic value and secondary supporting value. If something does not have utility – that is to say immediate economic value to some actor – it cannot be properly brought into the framework and managed by the market. This formalization of value results in two types of commodities, one free market where all these conditions hold and another where they don’t hold and they have to be managed through government regulation. Where government provides the secondary evaluation mechanism that the market could not provide because these secondary values do not have immediate utility. This is called market failure. Market failure is when the evaluation of something in terms of its pure utility leads to far-from-optimal societal outcomes because these secondary values are not being taken into account by the market. More formally we call this secondary value a positive externality, it is called an externality simply because these models can not incorporate it into the framework built on a utility based value system.


The result of this dichotomy is the idea of externalities, that is, that value is being transferred from the primary economic domain of utility to secondary value which is not captured by the model, and thus outside of the market mechanism and considered an externality. Externalities can be both positive and negative, and of course, societies want more of the positive and less of the negative externalities. Thus, an alternative set of relations is defined by government regulation in order to capture and quantify these external forms of value and reconnect them back into the economic equation governing the actions of the agents in the system – through such mechanisms as subsidies, grants, taxes, tariffs etc.

The net result of this model of value in purely extrinsic terms as captured by the concept of utility is that the market becomes dependent upon regulation. Because this secondary value is externalized from the model – and thus the market system – while at the same time it is dependent upon it, the whole thing is not sustainable without regulation, but regulation is an artificial mechanism that places constant friction on the system.  As previously mentioned, value is a very complex thing and fundamental to any economic paradigm. How the framework defines it will have major consequences down the line.


Next, we will talk about the interaction between agents within the standard model. One of our key considerations within the domain of economics is the fact that during the course of the agents pursuing their valued ends, they will inevitably interact and how they interact will be of great importance to the overall enterprise. The interactions between economic agents within the standard model will be significantly constrained by the fact that, in order for linearity to hold, additivity has to hold. Additivity means that the whole can be nothing more than the sum of its parts. Within the Walrasian economy – which is the standard general equilibrium theory of the economy – there cannot be any macro properties that cannot be derived in theory from micro properties.

All interactions between agents need to be additive for equilibrium to hold. Additive interactions are within game theory called zero-sum. Zero-sum interactions define a certain subset of possible interactions between agents. What one wins, the other loses, meaning everything sums up to zero and additivity holds. These are zero-sum interactions between agents. When the Neoclassical paradigm is taken to its natural conclusion, relations between agents both external to an organization and internal to the organization are defined as zero-sum. Which is somewhat counter-intuitive because we typically think of organizations as forms of collaboration. But by creating a hierarchy where the gains and losses of an agent at any level within the hierarchy are counter-balanced with the gains and losses of an agent above or below in the hierarchy, we again get a zero-sum game, and thus, a model for defining organizations as nothing more than the sum of their parts. Again, this is important because it means the additivity principle holds and linear models will work. Organizations are then defined to exist primarily simply because of transaction costs.

Of course, within game theory, there is another possible class of interactions between agents, what is called non-zero-sum. Through non-zero-sum interactions – such a synergies or interference – value is added or subtracted from the combined system by the relation between the agents. Thus, the whole is not a simple aggregate of the parts and it is non-additive, thus nonlinear, thus not compatible with general equilibrium theory. This model can only really help us in describing and modeling one type of interaction. Any type of interaction that adds or subtracts value to the organization as a whole cannot be properly formalized – because of the requirement for additivity which is an inherent part of linear systems theory.


This approach leads to the idea of the efficient market hypothesis, the idea that without external intervention causing friction the market will always clear and be the best mechanism for macro-level resource allocation, what is called Pareto optimality. In order to have so-called efficient markets, every agent must be a price taker. Agents are price takers when they act on the belief that the terms on which they can transact can not be affected by their own behavior. These conditions only really hold within a pure market. Thus, this model only really works and describes pure markets, which of course is just one type of market amongst others. But within this paradigm, pure markets are always seen to be the most efficient. Anything that deviates from the free market is seen to be suboptimal and these deviations are thought to derive from exogenous factors that add friction to the system.

Macro-level regularities or institutions within economies are explained within the standard model through the use of what is called methodological individualism, which within economics is the position that economic phenomena can be explained by aggregating over the behavior of agents. Any form of macro-level structure or institution is believed to be fully derivable from micro-level phenomena – although in practices this is not really possible. Methodological individualism is not particular to economics. It is used in many areas of the social sciences and it will give us linear solutions.


Lastly, in our discussion on standard economic theory, we will look at what models it presents for analyzing economic dynamics. The first thing to note is that because it is based on linear systems theory, we are always going to get general equilibrium. Equilibrium is a point of stasis, a static point. It is going to be very difficult to describe how things change when everything is dependent upon them always adding up to zero and thus staying the same. The net result will be that there is nothing inside of the model that will allow us to describe the development of the whole system.

Any change is going to involve some period of non-equilibrium. We do not have the language to describe non-equilibrium. Non-equilibrium is simply non-existent in this language, so all we can really do is ascribe change to exogenous factors, saying that they are outside of the system – such as natural disasters, social unrest, innovation in technology, cultural factors etc. We will simply say that these exogenous factors knock the system out of its natural state of equilibrium and then describe how it will go back to equilibrium again. This is what these models will allow us to do. They will not allow us to think about the economy as a dynamic system that is constantly changing due to internal drivers.

If we can’t really talk about how the whole system changes over time within its environment and our focus is internal to the system – which it always is with analytical modeling – we will define change and growth in terms of how much the system processes, that is the quantity of economic activity which is captured by the metric of GDP. Quite simply then, growth will be defined as more economic activity, more throughput to the system. Which is one way of defining our overall objective within economics; which can be defined as the use of efficient means towards achieving valued ends. Standard economic theory gives us a picture of the economy as forever progressing in a linear fashion without the capacity to describe how it may evolve through abrupt phase transitions – as experienced during financial crises for example – into new overall patterns of organization.


Formal languages are very abstract conceptual mechanisms and their high level of abstraction gives them a lot of power, but also they are in many ways quite dangerous in that they can systematically prevent us from seeing certain facts that may be blatantly obvious without them. Like all modeling frameworks, linear systems theory has its achievements and its failings. It has relevant applications and inappropriate applications. Many other areas of science have come to recognize both the achievements and limitations of linear systems theory. In particular, we could cite physics – which since the early 20th century when general relativity and then later on chaos theory presented it with the limitations of this modeling framework – has managed to a certain extent to develop and incorporate both linear and nonlinear methods and use them when appropriate.

Theories are like tools that aid us in trying to describe the world around us. There is little point in asking whether a tool is correct or incorrect. What is of value to ask is whether the tool we are using is appropriate for the job that we are using it for. A hammer is appropriate for putting a nail into a piece of wood, but not appropriate for putting a screw in. Thus, whether the tool is appropriate is relative to the function we are trying to perform. Linear systems theory applied to economics has offered us a lot of insight and traction on this very complex phenomenon that is an economy. Like all theories, it has its capabilities and limitations. After all, it has provided the theoretical framework for supporting the development of the vast machinery of coordination that is advanced industrial economies. It is in many ways a great achievement in that it enabled the important stage in our development that was the Industrial Age. But if we want to try and describe something very complex like an economy, we are going to need different tools, but economics has kind of gotten stuck with the one toolbox.

As the economist, Eric Reinsert put it: “We are in the situation described by Mark Twain that if you choose a hammer as your tool, you are going to spend the rest of your life looking for things that look like nails. And this is what economics is doing. Instead of saying, here we have a real world problem – what angle should we look at this from and what tool should we use, we come to all situations with the same tools.”

Our global economy is in a state of rapid and fundamental change – both its technology infrastructure and social institutions. As we come to an end of the life cycle of industrial age systems of organization, we are in the process of rapidly building a new post-industrial, global, services and information economy. These are major structural transformations that are working to increasingly reveal the limitations to our standard economic theory and necessitating a new paradigm and models.

Systems Innovation

  • LinkedIn
  • YouTube
  • Twitter
  • Facebook