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

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  • Eric Talley
  • Drew O'Kane

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.

Suggested Citation

  • Eric Talley & Drew O'Kane, 2012. "The Measure of a MAC: A Machine-Learning Protocol for Analyzing Force Majeure Clauses in M&A Agreements," Journal of Institutional and Theoretical Economics (JITE), Mohr Siebeck, Tübingen, vol. 168(1), pages 181-201, March.
    • Handle: RePEc:mhr:jinste:urn:sici:0932-4569(201203)168:1_181:tmoama_2.0.tx_2-0
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    References listed on IDEAS

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    1. Ronald J. Gilson & Alan Schwartz, 2005. "Understanding MACs: Moral Hazard in Acquisitions," The Journal of Law, Economics, and Organization, Oxford University Press, vol. 21(2), pages 330-358, October.
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    Cited by:

    1. Marian Moszoro & Pablo T. Spiller & Sebastian Stolorz, 2016. "Rigidity of Public Contracts," Journal of Empirical Legal Studies, John Wiley & Sons, vol. 13(3), pages 396-427, September.
    2. Sarath Sanga, 2014. "Choice of Law: An Empirical Analysis," Journal of Empirical Legal Studies, John Wiley & Sons, vol. 11(4), pages 894-928, December.
    3. Christoph Engel, 2018. "Empirical Methods for the Law," Journal of Institutional and Theoretical Economics (JITE), Mohr Siebeck, Tübingen, vol. 174(1), pages 5-23, March.
    4. James P. Ryans, 2021. "Textual classification of SEC comment letters," Review of Accounting Studies, Springer, vol. 26(1), pages 37-80, March.

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    More about this item

    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; Data Access
    • 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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