0ptimizing the Premerger Notification Rule.Empirical Analysis Based on Micro-Data of China

Abstract

We leverage a historical dataset from the China Anti-monopoly Bureau to improve the premerger notification rule. We simulate the government's decision-making process and propose the Receiver Operating Characteristic curve to optimize it. Our focus is on balancing the total cost of inappropriately low thresholds or convoluted criterion (Type I error) and undue high thresholds or singular criterion (Type II Error). We demonstrate the current notification threshold levels of China are too stringent, and the Size-of-Transaction criterion holds incremental predictive power in the preliminary screening for further review, potentially addressing the concern of data-driven and platform-centric mergers.

主讲人简介

熊巧琴，深圳大学经济学院助理教授，清华大学博士，斯坦福大学访问学者。研究方向为产业经济学、数字和数据经济、法经济学。作品发表于《经济学（季刊）》、《经济学动态》，International Review of Economics & Finance等，参与编撰书籍《数据经济学》，部分论文被人大复印报刊资料和《中国社会科学文摘》转载。

组 织 者：李振，BIMSA数字经济实验室助理研究员，lizhen@bimsa.cn