dc.contributor.advisor | Heidi Nepf. | en_US |
dc.contributor.author | Khoury, Bassel | en_US |
dc.contributor.other | Massachusetts Institute of Technology. Department of Civil and Environmental Engineering. | en_US |
dc.date.accessioned | 2016-08-02T20:07:22Z | |
dc.date.available | 2016-08-02T20:07:22Z | |
dc.date.copyright | 2016 | en_US |
dc.date.issued | 2016 | en_US |
dc.identifier.uri | http://hdl.handle.net/1721.1/103839 | |
dc.description | Thesis: S.M., Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, 2016. | en_US |
dc.description | Cataloged from PDF version of thesis. | en_US |
dc.description | Includes bibliographical references (pages 103-104). | en_US |
dc.description.abstract | Empirical legal analysis is an emerging discipline of statistical and legal scholarship. Despite its importance, however, there is a lack of empirical research on the affirmative defense of force majeure, which eliminates liability for a breach of contract in the case of an unforeseeable and uncontrollable event that renders performance impossible. This study seeks to fill the gap in the empirical literature by addressing some central questions on preparing to litigate a force majeure defense. Relying on methods from categorical data analysis, I examine the various criteria that a litigator would use in assessing the strength of a force majeure defense based on contractual terms. This study was supported by a database of manually collected lawsuits, with which I analyzed 291 state and federal force majeure cases from the 19th century to the present day. The results highlight the key elements in a force majeure provision that weigh most heavily in favor of the party raising the defense. | en_US |
dc.description.statementofresponsibility | by Bassel Khoury. | en_US |
dc.format.extent | 104 pages | en_US |
dc.language.iso | eng | en_US |
dc.publisher | Massachusetts Institute of Technology | en_US |
dc.rights | M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. | en_US |
dc.rights.uri | http://dspace.mit.edu/handle/1721.1/7582 | en_US |
dc.subject | Civil and Environmental Engineering. | en_US |
dc.title | A poisson regression model for assessing force majeure claims | en_US |
dc.type | Thesis | en_US |
dc.description.degree | S.M. | en_US |
dc.contributor.department | Massachusetts Institute of Technology. Department of Civil and Environmental Engineering | |
dc.identifier.oclc | 953868751 | en_US |