Corporate integrity and hostile takeover threats: Evidence from machine learning and “CEO luck”

Viput Ongsakul, Pattanaporn Chatjuthamard, Pornsit Jiraporn, Sirithida Chaivisuttangkun

Research output: Contribution to journalArticlepeer-review

11 Scopus citations

Abstract

Exploiting an innovative measure of corporate integrity based on machine learning and textual analysis, this paper explores the effect of hostile takeover exposure on corporate integrity. Using a measure of takeover vulnerability principally based on state legislation, we find that a more active takeover market raises corporate integrity, corroborating the notion that the disciplinary mechanism associated with the takeover market induces managers to enhance corporate integrity. Specifically, a rise in takeover exposure by one standard deviation results in an improvement in integrity by 4.00%. Further analysis confirms the conclusion including propensity score matching, entropy balancing, and instrumental-variable analysis. Our study is among the first to employ this novel text-based measure of corporate integrity. Finally, additional analysis based on ”CEO luck” validates the conclusion.

Original languageEnglish (US)
Article number100579
JournalJournal of Behavioral and Experimental Finance
Volume32
DOIs
StatePublished - Dec 2021

All Science Journal Classification (ASJC) codes

  • Finance

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