Wiley Agent-based Models and Causal Inference Book

Explore the connection between Agent-based Models (ABMs) and causal inference with this academic text from Wiley. While many scholars have overlooked the potential of ABMs for warranting causal claims, Manzo provides a strong argument for why this methodology is a valuable tool for researchers. The book begins by reviewing the significant progress ABMs have achieved as a credible methodology over the last several decades. It moves beyond simple descriptions to offer a deep comparison between ABMs and traditional methods such as Randomized Controlled Trials (RCTs), regression, and instrumental variables. By examining the inferential threats inherent in different approaches, the text demonstrates that ABMs share common vulnerabilities with standard methods, specifically regarding their reliance on untestable assumptions. This book is an essential resource for those studying computational and quantitative social science, offering a new perspective on how to validate causal claims through modeling.