The Measure of a MAC: A Machine-Learning Protocol for Analyzing Force Majeure Clauses in M&A Agreements

Eric Talley and Drew O'Kane

Journal of Institutional and Theoretical Economics (JITE), 2012, vol. 168, issue 1, 181-201

Abstract: This paper develops a protocol for using a familiar data set on force majeure provisions in corporate acquisitions agreements to tokenize and calibrate a machine-learning algorithm of textual analysis. Our protocol, built on regular expression (RE) and latent semantic analysis (LSA) approaches, serves to replicate, correct, and extend the hand-coded data. Our preliminary results indicate that both approaches perform well, though a hybridized approach improves predictive power further. Monte Carlo simulations suggest that our results are generally robust to out-of-sample predictions. We conclude that similar approaches could be used more broadly in empirical legal scholarship, especially including in business law.

JEL-codes: C63 C81 C88 K00 K12 K22 (search for similar items in EconPapers)
Date: 2012
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Citations: View citations in EconPapers (5)

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