Research specification

The final sample includes 625 firms’ observations.

Hypothesis H1 predicts that corporate governance is positively associated with crisis

40 _{The U.S. and U.K. government also announced similar policies around the same time (Erkens et al., 2012).} 41 _{For more information about the RESSET Financial Research Database, please s} 42 _{Among the 694 firms, controlling shareholders have the voting rights of less than 10% in 42 firms.}

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period stock return. As we discussed in the theoretical section, controlling shareholders’ expropriation ultimately reflects on stock return. Using stock return as the dependent variable, we actually test the effectiveness of corporate governance in deterring expropriation. The external shock during the financial crisis provides a quasi-experiment, through which we can examine whether the ex ante corporate governance mechanisms prior to crisis explain the ex post magnitude of stock price decline during the crisis. This method is also used in prior studies such as Mitton (2002), Baek et al. (2004), and Bae et al. (2012).

The regression specification is as follows:

, , 1 , 1 ,,

i t i t i t in d i t

R = + ⋅α B CG ₋ + ⋅Z X ₋ +α +ε (14)

whereRi t, denotes the stock return during the financial crisis. The crisis period we define

ranges from May 1st_{, 2008 to February 28}th_{, 2009, which covers 197 trading days. We first}

calculate the daily abnormal return based on long run event study. The Fama-French three factors model is employed to adjust the systematic risk (Fama and French, 1993). To facilitate interpreting the regression coefficients, we use annualized abnormal return as the dependent variable.

The independent variables are based on the observations at the end of fiscal year 2007.

, 1

i t

CG − denotes the control-ownership disparity and corporate governance prior to the crisis.

, 1

i t

X − represents the control variables, which include size, market to book ratio, leverage, and the proportion of intangible assets. αinddenotes the industry fixed effects, which is based on the 2-digit industry classification of China Securities Regulatory Commission (CSRC). To adjust for possible dependence in the residuals for the firms from the same industry, we use clustered standard errors at industry level following Froot (1989) and Kothari and Warner

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(1997). Appendix A shows the detailed description of all variables.

Hypothesis H1 also predicts that corporate governance is not significantly associated with stock return before or after the crisis. To be parallel with crisis period, the pre-crisis period is defined as between May 2007 and February 2008, and the post-crisis period is defined as between May 2009 and February 2010. We calculate the stock return for pre-crisis and post-crisis period, respectively. Accordingly, the independent variables for the pre-crisis regression are measured at the end of fiscal year 2006, and the independent variables for the post-crisis regression are measured at the end of fiscal year 2008.

Hypothesis H2 predicts that corporate governance is more effective when a firm is exposed to severer credit crunch shock. We test this prediction using the following regression equation:

, 1 , 1 2 3 , 1 , 1 ,,

i t i t i i t i i t in d i t

R = + ⋅α B CG ₋ +B Shock B CG⋅ + ⋅ ₋ ⋅Shock Z X+ ⋅ ₋ +α +ε (15)

whereShock_imeasures the extent of credit crunch shock that a firm is exposed to. A greater value ofShockirepresents the severer credit crunch shock during the crisis. Our coefficient of interest isB₃, which captures the moderating role of heterogeneous credit crunch shock. A positiveB₃suggests that the effectiveness of corporate governance increases with the severity of credit crunch shock.

Hypothesis H2 also predicts that the moderating role of heterogeneous credit crunch shock is more pronounced when a controlling shareholder has higher cash flow rights. We test this prediction by partitioning the total sample into subsamples based on controlling shareholders’ cash flow rights. If H2 holds, we should observe more significantB₃in the subsample with higher cash flow rights. We use four different threshold points of cash flow

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rights to partition the total sample, and they are the cash flow rights of 50%, 45%, 35%, and 25%, respectively.

We use a firm’s dependence on external finance to proxy for its exposure to the credit crunch shock. The credit crunch shock during the crisis restricts a firm’s investment in the attractive projects (Campello et al., 2010; Duchin et al., 2010; Cingano et al., 2016).44

We follow Rajan and Zingales (1998) to calculate the external finance dependence prior to the crisis at industry level. An industry’s dependence on external finance is defined as the ratio of external finance to total investment in 2006 and 2007, where external finance is calculated as total investment minus internal finance. We collect the data from the China

Fixed Asset Investment Yearbook (2006, 2007).

The firms that depend more on external finance demonstrate higher level of investment reduction during the crisis (Duchin et al., 2010). Dell’Ariccia et al. (2008) also find similar pattern through examining the impact of banking crises on real activities with the data from 41 countries between 1980 and 2000. Chinese firms rely more on bank loans rather than bond market or equity market (Allen et al., 2012), they are expected to be severely impacted during the crisis, and the firms that depend more on external finance should be exposed to severer credit crunch shock.

45

44 _{Campello et al. (2010) conduct a survey on 1050 CFOs around the world. They find that credit constrained firms cut their}

expenditures on technology development and capital accumulation. Duchin et al. (2010) and Cingano et al. (2016) also find that corporate investment significantly reduced during the global financial crisis.

45 _{Rajan and Zingales (1998) argue that external finance dependence reflects each industry’s intrinsic demand for external}

finance, which is determined by the production technology. Since Chinese firms could have different production technology, we do not directly use the external finance dependence measure from the U.S. firms.

Since the China Fixed Asset Investment Yearbook is based on the China National Economic Industry Classification (GB2002), we manually match it with the industry classification of China Securities Regulatory

102 Commission (CSRC).46

We test the validity of the proxy for heterogeneous credit crunch shock by examining the impact of external finance dependence on firms’ crisis period stock return. Since the credit crunch shock constrains firms’ investment on attractive projects, it would ultimately reflect on stock return.47