Industrial Organization in Flux: Challenges in Merger Analysis and the Need for Disciplinary Reinvention

This article examines the pressing challenges facing Industrial Organization (IO) in the contemporary economic landscape, with a particular focus on merger analysis. The rapid pace of technological advancement and emergence of novel business models have strained conventional analytical frameworks. We explore how the rise of digital platforms, data as a competitive asset, and multi-sided markets have exposed gaps in our understanding of market power and consumer welfare. Through an examination of empirical methodologies, including structural models and difference-in-differences approaches, we highlight the limitations of current techniques in accurately predicting merger outcomes. The paper argues for a disciplinary reinvention of IO, drawing upon insights from behavioural economics, network theory, and data science. We posit that an interdisciplinary approach is essential for developing more robust analytical tools capable of navigating the complexities of modern markets and informing effective antitrust policy in an increasingly interconnected global economy.