Self-Selectivity in Firm's Decision to Withdraw IPO: Bayesian Inference for Hazard Models of Bankruptcy With Feedback

• Published in: Journal of the American Statistical Association Vol. 105; no. 492; pp. 1297 - 1309
• Main Authors: Chen, Rong, Guo, Re-Jin, Lin, Ming
• Format: Journal Article
• Language: English
• Published: Alexandria, VA American Statistical Association 01.12.2010; Taylor & Francis Ltd
• Subjects: Applications; Applications and Case Studies; Bankruptcy; Bayesian analysis; Bayesian method; Business structures; Decision making models; Decision theory; Econometric models; Economic models; Estimation; Exact sciences and technology; General topics; Initial public offerings; Insurance, economics, finance; Mathematics; Modeling; Nonparametric models; Parametric inference; Parametric models; Probabilities; Probability; Probability and statistics; Sciences and techniques of general use; Statistical models; Statistics; Time dependence; Bayes estimation; Self-selectivity; Numerical linear algebra; Determinant; Bias; Finance; Econometric model; Statistical estimation; Statistical decision; Hazard model; Decision model; Statistical method; Numerical analysis; Feedback; Decision theory; Statistical model; Model specification; Survival probability; IPO withdrawal; Bayesian inference; Bayes decision; Biased estimation

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...