Introducing a New Corpus of Definitive M&A Agreements, 2000–2020

Abstract

Contract design and architecture is an important topic within economics, finance, and law. However, attempts to study it are significantly constrained by the limited availability of public, high quality data. In this paper, we introduce a new corpus of 7929 Definitive Merger Agreements submitted to the SEC between 2000 and 2020 involving a transaction in excess of $100 million. Through a combination of machine learning and human evaluation, we associate these agreements with other metadata, such as deal size, industry classification, and advising law firms. In addition, we identify and make available the text of individual clauses contained in these agreements. In a final step, we provide an illustration of how these data can be used to generate novel insights into M&A contract design and drafting practices.