标题:
经理自主权对高管薪酬水平的操纵效应研究评述与展望Study on the Manipulation Effect of CEO Power on Executive Compensation Level: A Literature Review
作者:
张长征, 王硕, 高灼琴, 赵欣
关键字:
经理自主权, 高管薪酬水平, 公司治理, 研究评述CEO Power, Executive Compensation Level, Corporate Governance, Literature Review
期刊名称:
《Management Science and Engineering》, Vol.4 No.1, 2015-02-26
摘要:
近年来上市公司业绩持续下滑与高管薪酬水平快速提升的反向变动日益引发公众的质疑和学者的关注，由此学术界在传统委托代理理论框架之外引入了经理自主权理论作为主要理论视角来研究高管薪酬水平问题。在此背景下，本文分别回顾并评述了美国、中国和世界其他地区基于经理自主权理论视角研究高管薪酬水平的历史进程与最新动态。结果表明，经理自主权对高管薪酬水平的正向操纵效应在学术界已达成基本共识，但是具体的操纵效应强度将因国家、行业、所有权属性等情境因素有显著权变性差异，而且学者对操纵效应发生机理也存在多种有待进一步检验的竞争性观点。整体而言，该领域研究结论的有效性越来越高，但也存在着诸多研究不足。未来研究应秉持扬弃精神，在经理自主权度量、控制变量选择、数据准确性提升和实证模型设计四个方面进一步丰富和拓展本领域研究。Recently the inverse change between the persistent decrease of list companies’ performance and quick growth of executive compensation level has received more and more attention both from the public and the scholars. Therefore, the theoretical circle introduces CEO power (or managerial discretion) theory as the main theory perspective on the studying of executive compensation level outside the traditional framework of principal-agent theory. Under this condition, the paper focuses on the historical process and the latest progress of the literature on the manipulation effect of CEO power on executive compensation level all over the world, but taking the studies in American and China as the key parts. Results show that the studies on this issue have received a consensus that the positive manipulation effect of CEO power on executive compensation level does exist, while the specialized manipulation degree will be different according to different countries, ownership characteristics, and industries. What is more, there are already many competing views on the mechanism of how such manipulation effect happens, which need to be confirmed further. On the whole, the validity of the research conclusions is getting higher, but there are still many shortcomings. The future studies should explore and enrich the literature in this field by especially emphasizing on the measure of CEO power, the choice of control variables, the enhancement of data correctness and the design of empirical models.