As advanced economies come to the end of the process of industrialization and with the rise of information technology we are witnessing the birth of a new type of post-industrial economy, it is built on services, fueled by information and knowledge and it is increasingly integrated through global financial and supply chain networks. These huge changes in the deep architecture to our economies go far beyond our industrial paradigm and are necessitating a re-imagination of economy theory. General equilibrium models that were derived from classical physics got mathematized during the 20th century, these models give us a picture of the economy as composed of isolated, purely rational individuals, optimizing over a well defined set of preferences out of which we get a macro level general equilibrium in a somewhat static and timeless economy.
It was a paradigm that fitted well with industrial age mechanization. But today the limitations of general equilibrium theory are becoming more apparent as we build new models, models to individual agents that have bounded rationality, driven by a diversity of motives they are interconnected and interdependent. And it is out of these nonlinear interactions we get the emergence of economic institutions as network structures that are far-from-equilibrium, in an economy that is constantly changing from internal drivers as it develops over time through an evolutionary process.
This course is an overview to the new area of complexity economics, the application of models from complexity theory to the domain of economic science. The course is broken down into five main sections, we will start off with an overview to economic theory discussing our standard approach before going on to give a clear outline to the main ideas coming out of complexity economies. Next we will borrow from behavioral economics to build up a more complex model to economic agents as we talk about the idea of bounded rationality, different theories of value, choice theory and incentive systems.
In the third section we will be looking at nonlinear economics as we apply system dynamics to modeling micro economic phenomena, we will be talking about how feedback loops create nonlinearity and the process of self-organization out of which emerges non-equilibrium patterns of organization in the economy. Next we will apply network analysis to modeling macro level economic institutions such as markets, we will introduce you to the basics of network theory and go on to talk about economic networks, their topology, distribution and dynamics. In the final section will be looking through the lens of complex adaptive systems theory to understand how whole macro economies emerge out of the actions and reactions of many different organizations, we will use the model of a fitness landscape in order to help us understand the process of economic evolution.
In this video we give a quick overview to complexity theory, systems thinking and complex systems that will form the foundations to our discussion during the rest of the course.
In this video we will be firstly talking about what theories and paradigms are and providing a little insight to their basic workings before moving on to define this subject that we call economics. We will outline some of the major considerations involved in the study of economics, including trying to understand the logic behind the decision making of agents, theories of economic value, the dynamics of cooperation and competition, economic institutions and economic development
In this video we will continue on with our discussion surrounding standard economic theory
In this video we will continue on with our discussion surrounding the current economic context as we talk about the information revoltuion
In this video we give a brief overview to complexity economics, a modelling framework that sees the the economy as an open system, composed of heterogeneous agents with bounded rationality making choices within a particular context, which gives rise to networks of interactions that we call institutions and a macro level non-equilibrium to the economy that is in constant change driven by internal dynamics
In this video we continue on with our dicsuction on complexity theory
In this video we will be turning our attention to what insight and models complexity economics can offer us in trying to understand the basic building blocks of economics, people, aka agents. We will draw upon the new area of economics called behavioral economics to try and give some account of what people value, how people make choices and how they respond to incentives
Value theory within economics represents all theories that try to define what economic value is, where it comes from, why goods and services are priced the way they are and how to calculate some form of objective price, if such a thing exists. In this video we will be looking at the two major paradigms to the theory of economic value, the standard extrinsic paradigm based around the idea of utility and the alternative nonlinear paradigm of intrinsic value
In this video we will be looking through the lens of complex adaptive systems theory in order to try and interpret the macro dynamics within an economic system, we will firstly introduce you to the idea of a complex adaptive system before going on to build up a model to their dynamics through what is called a fitness landscape, a three dimensional state space for representing the whole system’s macro topology, we will talk about how this topology changes depending on the complexity of the environment and some of the strategies that agents use within these different environments
Think Academy is an e-Learning site dedicated to the area of systems thinking and complexity theory, our mission is to take the world of complexity and make it accessible to all. Systems and complex can be intimidating subjects with many sophisticated concepts, this is why we believe it is important to always start with the most essential, simplest elements of a subject making sure that students come away with a solid understanding of the core concepts behind each area. As Einstein said "Make everything as simple as possible, but not simpler"
Courses are curated and presented by Joss Colchester. Joss has extensive experience within the domain of complex systems both within academic research(mathematical modeling of complex system + network analysis) and has many years practical systems engineering experience(designing and developing complex web based information systems). He has a passion for taking abstract and complex concepts and making them concrete and accessible to as broad an audience as possible by combining clear and effective graphics with well structured course content.