Complexity in Economics
This class is currently under development. Updates will be posted on a regular basis.
What do mountain goats and economic inequality have in common?
Why do gas molecules in a container and corporations behave the same?
Why are your friends on social media like the stock market?
In this class we will analyze and discuss the economy as a complex system. We will borrow concepts from other disciplines like astronomy, physics, epidemiology, psychology, biology, or even music to encounter economic agents and their behavior. In an interdisciplinary approach, we will learn a new way to understand economic actions across all subfields.
This class does not require any prerequisites and welcomes students of all majors and programs.
A great introduction video into complex systems and networks has been made by Petter Holme.
Description of the Class as approved by the Graduate School
The majority of economic academia is about equilibria: Self-adjusting forces, an invisible hand, will guide the economy and its agents on their pursuit for wealth and an optimal social outcome, so the wide-spread belief in the profession. Nevertheless, it is necessary to see the economy as an evolving system, as agents are constantly changing their strategies, driven by legal frameworks, innovations, and changing environments. The proposed class on Complexity in Economics will address precisely this understanding and treat the non-stationarity as the typical and expected outcome rather than a special case.
The department of economics is currently offering a large variety of classes for undergrad students, especially in the fields of intersectionality, environment, history, and social justice. It also offers more traditional classes like micro- and macroeconomics at different levels and statistics/econometrics in theoretical and empirical settings. The proposed class will move beyond those classes and focus on how the observed macro outcomes result from individual, constantly changing strategies and actions of many individuals. Moving on from the paradigm of utility-maximizing individuals and stationary equilibria, this class is specially designed to address the complex nature of social systems in their origin, behavior, and outcome.
The idea to see the economy as a complex system is not new. Adam Smith, Karl Marx, and Friedrich Hayek addressed complex interactions in society when they addressed the division of labor, firm profitability, and the emergence of prices. However, modern economics continues to think of the economy as a closed, static system rather than complex. The founding of the Santa Fe Institute in the 1980s was a big step to shift the understanding of the economy as a dynamic, nonlinear system which evolves from a spontaneous order. However, complexity economics has still not made its way into the classrooms, especially on the North American continent. Most programs are attached to physics or mathematics. The complexity revolution had more impact in Europe, spreading interdisciplinary research centers all over the continent, the most leading ones in Vienna, Groningen, Pisa, London, and Turin.
Complexity in Economics will differ in its setup from other class in economics, especially the introduction to the field will not be about economics at all. Due to the wide range of fields in which complexity studies are employed, this class will be interdisciplinary. Relying on concepts usually found in astronomy, physics, epidemiology, psychology, and biology, we will talk about the transmission of information, how gas molecules behave in a container, and how the social hierarchy of mountain goats came about. Applying these tools to genuinely economic questions might seem counterintuitive, but the evolution of systems and their behavior is similar across disciplines. So, for example, does the interaction of mountain goats, their decision to seek or avoid a fight shape the possibility of future conflict between individuals or the probability of survival of a specific individual in case of a predator attack. Decisions about interaction matter for individuals but also the outcome for the group. Those fundamental driving forces mirror the systemic parameters observed in income and wealth inequality, firm power, or success in the stock market. Approaches inspired by complexity economics have, for example, recently helped gauge the true extent of wealth inequality, determine systemically important firm-level drivers of aggregate fluctuations, or identify beneficial national specialization patterns for growth and development.
The class will be constructed around three main components. First, students will be introduced to seeing economic problems through the aforementioned interdisciplinary lens. By understanding problems in fields outside of economics, the skill set available to the student expands, critical assessments and solutions from outside of the standard-economic toolbox will improve the quality of economic analysis. This section will conclude by reading traditional thinkers like Smith, Marx, Hayek, and Friedman and how their interpretation of the basic economic principles has changed, while the described and discussed underlying problem has not. This emphasizes the ongoing developments in assessing and analyzing economic problems with different ideological lenses in the specific circumstances of a researcher's time. Second, the class will discuss the approaches in economics how problems are modeled and discussed in the profession. This brief discussion will start with static equilibria models, introducing more complexity, step by step: Continuing with bifurcation models, agent-based modeling, multiple equilibria, and lock-in effects, students will learn about the advantages but also limitations of those approaches. The main component of the class will be the third and final one. Linking economic problems to those of other fields, students will be introduced to the most state-of-the-art methods like network analysis, self-learning agents, self-organization, and information constrained statistical equilibria. These highly sophisticated methods require a deep mathematical understanding if they are correctly applied to real-world problems. Therefore, this class will be limited to a basic introduction which provides students with a solid starting point for their future learning experience. However, every student will be provided with the necessary knowledge to generate their own basic problem, which they model and analyze with one of the presented methods.
Meaningful discussions that this class will consistently touch on are the distinguishability between complexity and chaos, chances and limitations of policy interventions, and most importantly, finding the correct method to analyze a given problem on hand. Therefore this class will use numerical and analytical methods, introduce students to a few adequate software tools and encourage them to play around with the presented options.
The interdisciplinary approach this class takes provides an excellent opportunity for students to discover new fields of interest and provides them with a framework to address current economic and social problems rather than textbook answers. The pedagogy will frame this goal applied, building on the diversity and curiosity of the students. Developing the skills necessary to disentangle, analyze, and restructure (economic) problems will be based on the knowledge, and individual skills students bring already to class, whether mathematical, linguistic, or basic IT skills. This class will stand out from the curriculum the department provides so far as it is interdisciplinary in the methods and the topics students are invited to discuss and analyze. It will broaden their horizon on how economic problems can be addressed outside of a static equilibrium framework and borrow methods from other fields: Epidemiological models can explain fashion trends, similar as the social hierarchy of mountain goats is not too different from income distributions.
Seeking solutions outside of a standardized box is essential in a rapidly changing society. Looking beyond the obvious and known, getting to the bottom of things, and reformulating problems are important competencies in forwarding science and society. This class aims to transform students into modern and agile problem-solver.