Internal Control and Stock Price Crash Risk: Evidence from China

Abstract

This paper examines the role played by internal control and its five components (i.e. control environment, risk assessment, control activities, information and communication, and monitoring) in alleviating future stock price crash risk. Using a unique dataset from China, we find evidence that internal control is negatively associated with future stock price crash risk. Specifically, control environment, information and communication, and monitoring are significantly and negatively associated with future stock price crash risk. Moreover, the negative association between internal control and crash risk is significantly more pronounced in firms with weak internal and external governance (i.e. audited by non-Big 4 auditors, located in provinces with low market development, and less conservative in accounting) and with poor ability to mitigate impacts of extreme negative events (i.e. non-state-owned enterprises). Our study highlights the delicate role of internal control as a mechanism in preventing crash of stock price.

Notes

¹For example, Ogneva, Subramanyam, and Raghunandan (2007), Hammersley, Myers, and Shakespeare (2008), and Beneish, Billings, and Hodder (2008).

²For example, the corporate governance center of Deloitte cites the internal control index on its website (see http://www.corpgov.deloitte.com/site/chinazh/; accessed on 24 May 2015).

³We conjecture that there at least three reasons that could lead to different findings from Kim and Zhang (2014). First, the proxy of internal control quality in the two US studies is a dummy variable, while ours is a continuous variable which could lead to more powerful tests. Second, our data come from China, an emerging market with weaker legal institutions, poorer corporate governance environment, and less experience in risk management compared with the USA. Thus, the marginal effects of internal control quality on crash risk might be greater in China, which makes us easier to detect the effects of internal control on crash risk. Third, as pointed out by Kim and Zhang (2014, p. 856): ‘In untabulated tests, we find that ICW does not predict future realized crashes. This does not necessarily mean that ICW does not increase future crash risk; it may simply be that internal control-driven crashes have not materialized yet. More importantly, it does not mean that ICW does not increase investors’ fear of future crash risk.’ Therefore, it's possible that internal control-driven crashes exist in both the US and China.

⁴Introduction of the internal control index can also be seen in the Internal Control Index (2009) for China's Listed Companies: Formulation, Analysis and Evaluation as published in China Securities Journal and Shanghai Securities News and Establishing the Internal Control Evaluation System Meeting the Actual Situation in China as published in Securities Times both on 11 June 2010 and Internal Control Index (2010) for China's Listed Companies: Formulation, Analysis and Evaluation published on 6 September 2011.

⁵In Column (1) of Table 6, when BIG4 = 1, the estimated coefficient of IC_INDEX is insignificant. However, we notice that the coefficient of IC_INDEX is −3.135 in Column (1) and −1.116 in Column (2). Therefore, we need to be cautious when interpret the results.

⁶This index reflects the institutional heterogeneity across regions in China. This index has been widely used in studies, such as Wang, Wong, and Xia (2008), Chan, Lin, and Wang (2012), and Hung, Wong, and Zhang (2012).

Additional information

Funding

Jun Chen would like to acknowledge the financial support from the National Natural Science Foundation of China [grant numbers NSFC-71102085 and NSFC-71572181] and the Natural Science Foundation of Zhejiang Province [grant number Y7100206]. Wang Dong would like to acknowledge financial support from the National Natural Science Foundation of China [grant numbers NSFC-71302060 and NSFC-71332008].