The Measure of a MAC: A Machine-Learning Protocol for Analyzing Force Majeure Clauses in M&A Agreements
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.Download Info
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Bibliographic Info
Article provided by Mohr Siebeck, Tübingen in its journal Journal of Institutional and Theoretical Economics.
Volume (Year): 168 (2012)
Issue (Month): 1 (March)
Pages: 181-201
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Web page: http://www.mohr.de/jite
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Postal: Mohr Siebeck GmbH & Co. KG, P.O.Box 2040, 72010 Tübingen, Germany
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Related research
Keywords:Find related papers by JEL classification:
- C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
- C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data
- C88 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Other Computer Software
- K00 - Law and Economics - - General - - - General (including Data Sources and Description)
- K12 - Law and Economics - - Basic Areas of Law - - - Contract Law
- K22 - Law and Economics - - Regulation and Business Law - - - Business and Securities Law
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