Bayesian piecewise stochastic frontier model to estimate initial public offering pricing efficiency under issuance policy reforms

Abstract

AbstractPrevious studies measure the pricing efficiency of initial public offerings (IPOs) using stochastic frontier analysis, but it is conventionally assumed that all IPOs have the same stochastic frontier function. We study how to measure IPO pricing efficiency under successional issuance policy reforms such as China's Growth Enterprise Market (GEM), where IPOs issued in different time periods might have their own pricing frontiers. In this article, we propose a stochastic frontier model with multiple change points in the time dimension based on the piecewise stochastic frontier function and develop a Bayesian inference and Markov Chain Monte Carlo sampling approach to estimate parameters. An empirical analysis finds two significant structural breaks in the frontier function for China's GEM from October 30, 2009, to January 9, 2018. China's developed provinces have more listed companies but lower average pricing efficiency. After 2012, the average IPO efficiency in public utilities dropped from the first place to the end, but the average IPO efficiency in the conglomerates rosed from the last to the first. Furthermore, a cross‐efficiency analysis proves that gradual market‐oriented issuance mechanism reforms have improved IPO pricing ability.