TY - JOUR
T1 - Corporate integrity and hostile takeover threats
T2 - Evidence from machine learning and “CEO luck”
AU - Ongsakul, Viput
AU - Chatjuthamard, Pattanaporn
AU - Jiraporn, Pornsit
AU - Chaivisuttangkun, Sirithida
N1 - Publisher Copyright:
© 2021 Elsevier B.V.
PY - 2021/12
Y1 - 2021/12
N2 - 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.
AB - 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.
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U2 - 10.1016/j.jbef.2021.100579
DO - 10.1016/j.jbef.2021.100579
M3 - Article
AN - SCOPUS:85116824959
SN - 2214-6350
VL - 32
JO - Journal of Behavioral and Experimental Finance
JF - Journal of Behavioral and Experimental Finance
M1 - 100579
ER -