首页|Self-Selectivity in Firm's Decision to Withdraw IPO: Bayesian Inference for Hazard Models of Bankruptcy With Feedback
Self-Selectivity in Firm's Decision to Withdraw IPO: Bayesian Inference for Hazard Models of Bankruptcy With Feedback
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NETL
NSTL
Amer Statistical Assoc
Examination on firm performance subsequent to a chosen event is widely used in finance studies to analyze the motivation behind managerial decisions. However, results are often subject to bias when the self-selectivity behind managerial decisions is ignored and unspecified. This study investigates a unique corporate event of initial public offering (IPO) withdrawal, where a firm's subsequent likelihood of bankruptcy is specified in a system of switching hazard models, and the expected difference in post-IPO and postwithdrawal survival probabilities serves as a "feedback" on a firm's decision to cancel its offering. Our Bayesian inference procedure generates strong evidence that incidence of withdrawal unfavorably affects the subsequent performance of a firm, and that the "feedback" is an important determinant in managerial decisions. The econometric and statistical model specification and the accompanying estimation procedure we used can be widely applicable to study self-selective corporate transactions.
Department of Statistics, Rutgers University, Piscataway, NJ 08854 Department of Business Statistics and Econometrics,Peking University, Beijing, China
Department of Finance, University of Illinois at Chicago, Chicago, IL 60607
Wang Yanan Institute for Studies in Economics, Xiamen University, Xiamen, China
NETL
NSTL
Amer Statistical Assoc
