Agent-Based Models in IO

In Industrial Organization, Agent-Based Models (ABMs) are neither new nor popular among mainstream economists. This section presents some interesting reading to those unaware of these models. It does not pretend to be exhaustive. It just shows some works (and conferences) where these models are a central topic.

Please, feel free to recommend me other readings that I may have missed and that you think could better illustrate to other people about this tool.

Introductory Works for Economists

Hamil and Gilbert (2016): Agent-Based modeling in Economics. 

This introductory book covers both Macro and Micro approaches, but what makes it relevant for me is that it is bundled with NetLogo code, which allows newcomers to learn-by-doing. Nonetheless, there are some aspects of the specific implementation of some cases that are questionable, but that is an advanced topic. I mainly recommend this book because it dedicates a whole chapter to the Cournot model, which may give microeconomists a good idea of what can be done.

Tesfatsion and Judd (2006): Handbook of computational economics, vol. 2: Agent-based computational economics

The title says everything. It is an old-but-reliable book about agent-based models. Although a little bit outdated in some aspects, it remains an interesting reading to understand the first steps in this literature. To be honest, I have not relied so much on this book but the motivation still holds. Each researcher has "its style", very much like writing. Thus, when reading, you feel that each author writes and sees ABMs differently, which is confusing if you are not familiar with the topic.

Examples of ABMs in IO Research

Katsamakas and Madany (2019): Effects of user cognitive biases on platform competition, Journal of Decision Systems

This work is a key example of what can be done with ABMs nowadays and how they can contribute to shedding light on some topics that otherwise would be confusing. In other words, the same approach can be taken by developing a theoretical model, but it may become mathematically intractable.

Katsamakas and Sanchez-Cartas (2023): A computational model of the competitive effects of ESG. PLoS ONE

An embarrassing self-promotion, but it is yet another example of what can be done with ABMs. Specifically, we combine a well-known theoretical model that becomes intractable when considering ESG effects, but we solve it using an ABM, which allows us to gain insight into how ESG can affect competition between two differentiated firms.

Barr and Saraceno (2005): Cournot competition, organization and learning. Journal of Economic Dynamics & Control

This work addresses a classical Cournot environment but from a completely different perspective than the one we are used to. Their Cournot firms are Artificial Neural Networks that receive signals from the environment and must set quantities while competing. The interesting point of that ABMs is that it allows us to address both market competition and firm structure.

Extra Article. Rand and Rust (2011): Agent-based modeling in marketing: Guidelines for rigor, International Journal of Research in Marketing

Although this work is much more related to marketing than to Industrial Organization, it provides key guidelines for all researchers that want to develop an ABM. In contrast with theory, which relies on very well-known mathematics, ABMs have no standard, so some guidelines are always welcome.

Conferences where ABMs are discussed

Every year, SCE organizes a conference on computational economics that covers different topics, among them ABMs. It is an interesting forum to exchange ideas about the methodology and uses of ABMs in Economics. However, the scope is broader than ABMs, so you can expect many other computation techniques. 

These two multidisciplinary conferences are organized together, and every year they cover different applications and uses of ABMs. In terms of topics, it is a much more broad conference, but many attendees come from computer science, engineering, and other disciplines. Thus, it is a great forum to learn about other techniques that are applied in other fields as well as the practical uses of ABMs.