Principal–principal agency problems and stock price crash risk: Evidence from the split‐share structure reform in China

Abstract

Manuscript Type: EmpiricalResearch Question/Issue: On April 2005, the China Securities Regulatory Commission (CSRC) launched the split-share structure reform to mitigate principal-principal agency problems.Using the reform as an exogenous shock, we examine the impact of principal-principal agency problems on stock price crash risk. Specifically, this study attempts to answer two questions:(1) Does the split-share structure reform in China decrease stock price crash risk? (2) Is the above effect induced by the mitigation of principal-principal agency problems?Research Findings/Insights: We find that the reform induces a significant decrease in crash risk after controlling for other predictors of crash risk, and this effect is more pronounced in firms with a higher proportion of shares held by controlling shareholders. Moreover, we find that the negative impact of the reform on stock price crash risk is more pronounced in firms with a high level of tunneling prior to the reform, which indicates that reform induces less tunneling, and adversely affects crash risk.Theoretical/Academic Implications: This study contributes to the literature in two ways.First, this study constitutes the first effort to explore the determinants of stock price crash risk from the perspective of principal-principal agency problems. Second, this study enriches the growing literature on the economic consequences of the split-share structure reform in China.Practitioner/Policy Implications: We draw two important implications from our results.First, our findings highlight that regulatory intervention is an important way to enhance corporate governance. This is particularly beneficial in China, a transitional economy which may lag in terms of general protection of investors and information disclosure. Second, this study also confirms that minority shareholders and listed firms benefit from the reform. Both are crucial to the healthy development of the capital market in China. KEYWORDScorporate governance, non-tradable shares, principal-principal agency problems, split-share structure, stock price crash risk

Board informal hierarchy and stock price crash risk: Theory and evidence from China

“…Panel B of Table reports summary statistics. The mean values for future crash risk measures, NSKEW T+ 1 and DUVOL T+ 1 , are comparable with those reported in prior studies on China (Cao, Xia, & Chan, ; Li & Cai, ; Sun, Yuan, Cao, & Wang, ). The mean value of HIERARCHY T (a board's informal hierarchy) is comparable with that reported in He and Huang ().…”

“…The mean value of CEO_STATUS T indicates that 19.8% of CEOs have a higher status than the majority of the directors on the board. The mean values of governance variables (i.e., IND T , DUALITY T , and BOARD T ) are closest to those reported in Sun et al, (). Moreover, the mean values of STATE T , RET T , SIGMA T , DTURN T , ABACC T , MTB T , ROA T , LEV T , and SIZE T are consistent with prior studies in the context of China (Cao, Xia, & Chan, ; Li & Cai, ; Li & Chan, ; Li, Wang, & Wang, ; Sun, Yuan, Cao, & Wang, ).…”

“…The coefficients of control variables, when significant, carry signs that are consistent with prior studies (e.g., Bhargava, Faircloth, & Zeng, 2017;Cao, Xia, & Chan, 2016;Chen, Hong, & Stein, 2001;Hutton, Marcus, & Tehranian, 2009;Jin & Myers, 2006;Sun, Yuan, Cao, & Wang, 2017). We find that the coefficients on lagged crash risk variables (NSKEW T and DUVOL T ) are significantly positive at the 1% level.…”

“…Table 1 reports summary statistics. The mean values for future crash risk measures, NSKEW T+1 and DUVOL T+1 , are comparable with those reported in prior studies on China (Cao, Xia, & Chan, 2016;Li & Cai, 2016;Sun, Yuan, Cao, & Wang, 2017 Sun et al, (2017). Moreover, the mean values of STATE T , RET T , SIGMA T , DTURN T , ABACC T , MTB T , ROA T , LEV T , and SIZE T are consistent with prior studies in the context of China (Cao, Xia, & Chan, 2016;Li & Cai, 2016;Li & Chan, 2016;Li, Wang, & Wang, 2017;Sun, Yuan, Cao, & Wang, 2017).…”

“…We also included industry (Fama–French 48‐industry classification) and year dummies in all models. Following prior studies on Chinese firms (Cao, Xia, & Chan, ; Li & Cai, ; Sun, Yuan, Cao, & Wang, ), we winsorized continuous variables at the 1% level at both tails.…”