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• W2056572782 abstract "Abstract: The paper shows that variables commonly used in takeover prediction models also help to explain the likelihood of several other restructuring events, including divestitures, bankruptcies and significant employee layoffs. This finding helps to explain the larger misclassification errors in binomial takeover prediction models commonly used in prior research. The results show that modelling takeover prediction models in a binomial setting is likely to lead to misspecification in the parameter estimates and, further, result in erroneous conclusions about the determinants of takeover likelihood. The paper shows that controlling for other restructuring events by using a multinomial framework results in consistently lower misclassification errors in out‐of‐sample prediction tests, when compared to the benchmark of a typical binomial model." @default.
• W2056572782 created "2016-06-24" @default.
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• W2056572782 date "2007-06-15" @default.
• W2056572782 modified "2023-10-16" @default.
• W2056572782 title "Are Corporate Restructuring Events Driven by Common Factors? Implications for Takeover Prediction" @default.
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• W2056572782 doi "https://doi.org/10.1111/j.1468-5957.2007.02028.x" @default.
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