Government control, regulatory enforcement actions, and the cost of equity

Transcription

1 1511 1/15/15 Government control, regulatory enforcement actions, and the cost of equity Kun Wang* Research School of Accounting and Business Information Systems The Australian National University Yanjun Liu Research School of Accounting and Business Information Systems The Australian National University Wanbin Walter Wang Research School of Finance, Actuarial Studies & Applied Statistics The Australian National University

2 Government control, regulatory enforcement actions, and the cost of equity Abstract This study examines the impact of the enforcement actions taken by the Chinese Securities Regulatory Commission (CSRC) on the implied cost of equity of Chinese listed firms, and how government control moderates the relation. We find that firms subject to enforcement actions have higher cost of equity when they are controlled by non-government shareholders or local governments. However, for firms controlled by the central government, there is no significant difference in the cost of equity between firms that are subject to enforcement actions and firms that are not. Further, the enforcement actions are associated with higher costs of equity for non-government-controlled firms compared to government-controlled firms. The results are robust to various sensitivity tests, including alternative measure of cost of equity to account for potential measurement error, and the use of two-stage least squares to control for potential endogeneity problems. Our results suggest that government control can provide benefit to firms in the form of lower equity financing costs when financial frauds occur. Keywords: ownership, enforcement actions, cost of equity, financial fraud, China JEL codes: G32, G34, G38, M41

3 1. Introduction Following a series of high-profile financial scandals at the beginning of this century around the world, financial fraud has drawn widespread attention of practitioners, regulators and academics. Although it is recognized that there is a need to understand fraud in a legal, political and economic context (Cooper et al., 2013), the literature on financial fraud focuses on the US market, and the consequences of fraud in emerging markets is under-researched. As the largest and the most influential emerging economy, China plays a crucial role in the world market. China is often seen as an interesting example that contrasts with the common view in law and finance literature, since it has weak legal and financial systems yet fast economic growth (Allen et al., 2005; Pistor and Xu, 2005). It is well recognized that legal and institutional environments can impact on the financial reporting incentives of firms (Bushman and Piotroski, 2006) as well as the development of financial market (Allen et al., 2005; Hail and Leuz, 2006). Given the importance of Chinese market and the institutional differences between China and the developed markets, it is important to explore the consequences of financial fraud in the context of China. This study investigates how the enforcement actions taken by the China Securities Regulatory Commission (CSRC hereafter) impact the cost of equity capital, and how government controlling interest in listed corporations moderates the relation. We use enforcement actions to represent financial fraud because it is a strong and unambiguous measure of financial fraud with low Type I error (Dechow et al., 2010). We focus on cost of equity to investigate the consequence of fraud because cost of equity is important for firms as it represents their financing cost, influencing the capital structure and profitability (Easley and O'Hara, 2004). Moreover, investor protection is 3

4 weaker and institutions are less developed in China compared to developed markets and even some other emerging markets (Allen et al., 2005). Therefore it is crucial to examine how investors risk perceptions change in reaction to the enforcement actions taken by the CSRC. This study is also motivated by the conflicting arguments and inconsistent evidence regarding the impact of government control of business corporations in the literature. Some studies (e.g., Allen et al., 2005; De Jonge, 2008; Chen, 2013) argue that the dual roles of both regulator and shareholder played by the government may impact the regulatory independence and the effectiveness of monitoring. Zou and Adams (2008) show that firms with state ownership are likely to have higher equity risks. In contrast, Boubakri et al. (2012) find that firms with political connections are perceived to be less risky by equity investors. The mixed evidence from previous studies further motivates this study to empirically investigate the impact of government control on the relation between financial fraud and the cost of equity. The ownership structure in China provides a unique setting to examine the effect of government control on financial markets. One typical characteristic of Chinese capital market is the government control of listed firms. Although there has been a privatization process of state-owned enterprises (SOEs) in last 30 years, the influence of the state control remains significant after SOEs were partially privatized through share issue privatization on the stock market (Chen et al., 2009a; Shailer and Wang, 2015). The CSRC is responsible for maintaining the financial integrity of listed firms and taking enforcement actions against financial frauds. However, the effectiveness of its regulation is often questioned because the CSRC reports to the State Council and is affiliated to the government (Allen et al., 2005; De Jonge, 2008; Chen, 2013). In such 4

5 circumstances, government control may impact investors perceptions of the effect of CSRC enforcement actions on the cost of equity. This study has several intended contributions. First, it aims to contribute to the literature on financial fraud in China. The limited literature on fraud in China focus on short-term market reactions to fraud (e.g., Chen et al., 2005; Aggarwal et al., 2014). Our study investigates the impact of financial fraud on ex ante cost of equity and extends the literature by providing insights into the impact of financial fraud on investors long-term risk perceptions. Second, this study contributes to the literature on ownership by examining the impact of government control on the relation between financial fraud and the cost of equity. Given the unique ownership structure and institutional environment in China, evidence on whether investors reactions to regulatory enforcement actions are influenced by government control of listed firms will further our understanding of the role played by the government in Chinese securities market. Third, the findings of this study have implications for the effectiveness of the CSRC. The CSRC has been making efforts to enhance its regulating efficiency and effectiveness especially in the past decade. In this study, we use the CSRC enforcement actions to represent financial fraud. Using a recent dataset, we investigate how investors value the information conveyed by CSRC s enforcement actions. The results are of interest to regulators, investors as well as researchers who are concerned with China s regulatory environment and the consequences of financial frauds. 2. Institutional Background A series of economic reforms have been initiated in China since late 1970s, transforming its economy from centrally-controlled to a more market-oriented 5

6 economy. China has developed rapidly in recent decades and become the world s largest emerging market. According to the World Bank, the GDP of China in 2012 using the PPP conversion factor ranks second in the world, only behind the US (World Bank, 2014), indicating that China is playing a crucial part in the world market. However, the rapid economic growth has not been matched by the development of laws and regulations in China. China is often perceived to have weaker and less regulated financial reporting environment compared with the developed markets, and the legal protection of investors is relatively poor (Allen et al., 2005; Pistor and Xu, 2005). Despite the underdeveloped institutional environment, the Chinese government has been making constant efforts to improve the regulating environment and enhance protections of investors, especially in the past decade. Two stock exchanges in mainland China, the Shanghai Stock Exchange (SHSE) and the Shenzhen Stock Exchange (SZSE), were both established in 1990 and has been growing rapidly since then. By the end of 2012, the total market capitalization of China s stock market reached around 3,700 billion (in US$), ranking only second to the US in the world (World Bank, 2014). During the beginning period of the development of Chinese stock market, regulations of the securities market were inconsistent and the responsibilities of the three main regulators, the State Council Securities Commission (SCSC), the CSRC and the People s Bank of China, were overlapping (Chen et al., 2005). In 1998, with the supervisory power of the SCSC and the People s Bank of China over the securities market being consolidated into the CSRC, the CSRC emerged as the sole regulator of securities market in China and assumed ministry status (Chen et al., 2005). The Securities Law passed in 1998 (and amended in 2005) empowered the CSRC as the independent governing authority over the securities market that reports directly to the State Council. The two stock exchanges are under ultimate supervision 6

7 of the CSRC. The restructuring aims to establish a more unified and centralized legal framework over China s securities market, as well as to enhance the consistency and efficiency of law enforcement. Basically the power of the CSRC can be divided into formulating regulation, investigation and supervision and legal enforcement. According to Article 179 of the 2005 Securities Law, the main duty of the CSRC include: formulating policies and regulations for the securities market; supervising the listing and trading activities of all kinds of securities; regulating the securities market behaviors of the listed companies, shareholders and other market participants; supervising securities exchanges and other organizations engaged in the securities business; investigating and penalizing the activities in violation of the relevant securities laws and regulations. The listed firms are subject to various securities laws and regulations enforced by the CSRC. Article Four of Solutions for Listed Firm Checks issued by the CSRC in 2001 prescribes two types of inspections conducted by the CSRC of all listed firms: regular inspection and special inspection. The CSRC also collects information from investors, employees, the media, police investigations and other sources (Chen et al., 2006). If suspected irregularities occur, the CSRC will initiate an investigation and collect evidence (Chen et al., 2005; Bian, 2014). Once the case is confirmed, the enforcement action will be taken with an announcement made to the public. As opposed to the case in the US, initiations of investigations are not disclosed and secrecy is maintained by the CSRC (Chen et al., 2005). If the misconduct is determined to be minor, the information will not be disclosed to the public (Wu et al., 2014). Common types of fraud include inflation of profits, information omissions, false representation, delay in disclosure, etc.the sanctions imposed by the CSRC fall into the following categories: internal criticism, public criticism, public condemnation and penalties, 7

8 while penalties include official warnings, confiscation of illegal proceeds, withdrawal of licenses or charters, monetary fines and other administrative penalties. The sanctions can apply to the company itself and/or to the individuals that are found guilty of the acts. For individuals, there can also be criminal sanctions if severe frauds are committed. During the development of the regulatory framework, the CSRC has been borrowing best practices from developed countries, such as the Securities and Exchange Commission (SEC) in the US; and it also fulfills similar functions as the SEC (Chen et al., 2006; Firth et al., 2011). As with the SEC, the CSRC tends to pursue the most certain and extreme cases of fraud (Dechow et al., 2010). Moreover, since the CSRC only publishes the confirmed cases, the enforcement action data used in this study should be a strong and unambiguous proxy for financial fraud. Despite that the CSRC has been attempting to enhance the regulatory framework, it is perceived to have some weaknesses. The most common criticism is that for most of the listed companies in China, the state is acting as both a player (controlling shareholder) and a referee (regulator) in the financial market (Allen et al., 2005; Chen, 2013). This conflict of interest may put the CSRC under political pressure and affect the effectiveness of the CSRC enforcement actions. Also, Chen (2013) points out that the CSRC is perceived to have high corruption rate, which can be attributed to its substantial power and limited accountability. From a comparative perspective, some research shows that the enforcement efficiency of the CSRC is much lower than the SEC in the US in terms of the sanction rates and the size of fines (Zhou, 2013). Taken together, the effectiveness of the CSRC enforcement actions remains to be an empirical issue. 8

9 3. Hypothesis Development The Impact of Enforcement Actions on the Cost of Equity As the main regulator of China s securities markets, the CSRC is responsible for maintaining market integrity and protecting investors through the enforcements against fraud. Fraud firms subject to enforcement actions are commonly accused of inflations of profits, financial misrepresentation or information omission. Since the CSRC tends to publish the confirmed cases only, firms subject to enforcement actions can be regarded as the most extreme cases of poor information quality. Therefore, our hypothesis development draws on the literature regarding the association between financial reporting quality and the cost of equity. It is generally recognized that information quality is negatively associated with the cost of equity. Cost of equity is the return required by equity investors when investing in a firm, which represents investors risk perception of the firm and affect investors asset allocation decision. It is also crucial to firms since it represents their equity financing costs. High quality information can reduce cost of equity as it conveys more precise information about the firm s operation to the investors (Biddle et al., 2009), which reduces information asymmetry and enhances the credibility of the firm. As argued by Easley and O Hara (2004), information risk is a priced risk factor that cannot be diversified away, which can affect firms cost of equity. In addition, Lambert et al. (2007) demonstrate that information quality can influence the cost of capital not only by affecting market assessment of future cash flows but also by affecting firms real decisions. There is limited research that specifically examines the impact of enforcement actions on the cost of equity (e.g., Dechow et al., 1996; Chen et al., 2005). However, 9

10 there is a rich empirical literature investigating the association between financial information quality and the cost of equity, especially in the US market. Prior research shows that higher information quality is related with lower cost of equity. A stream of research focusing on disclosure quality suggests that disclosure quality is negatively associated with the cost of equity for firms with low analyst following (Botosan, 1997), when the disclosure is in the annual report level (Botosan and Plumlee, 2002), and when the public information is more precise (Botosan et al., 2004). Other studies using earnings quality to represent information quality (e.g., Francis et al., 2004; Francis et al., 2005) and find that firms with poor accrual quality and other earnings attributes tend to have higher cost of equity. In terms of internal control weakness (ICW), Ashbaugh-Skaife et al. (2009) show that firms reporting ICWs have significantly higher idiosyncratic risk and the cost of equity than those not reporting ICWs. Likewise, some studies use financial restatements as an indicator of information quality and report that restatements can lead to increases in the cost of equity (e.g., Hribar and Jenkins, 2004; Kravet and Shevlin, 2010; Firth et al., 2011). These studies show that investors risk perceptions are influenced by the quality of the information disclosed by firms. Based on the above arguments and empirical evidence, if the enforcement actions are effective, the information should be valued by investors and have influence on their risk perception of these firms. This leads to our first hypothesis: Hypothesis 1. Firms subject to the CSRC enforcement actions have higher cost of equity than firms not subject to the CSRC enforcement actions. 10

11 The Impact of Government Control on the Relation Between Enforcement Actions and the Cost of Equity Prior studies (e.g., Allen et al., 2005; Bushman and Piotroski, 2006; Hail and Leuz, 2006) suggest that the institutional environment of a country can have impact on its financial systems. One substantial difference between Chinese and other capital markets is the influence of government on the financial market. One key feature of China s enterprise reforms is that the state retains a significant stake in listed firms and can still exert influential control on the firms. The literature acknowledges that government-controlled firms enjoy various privileges, such as preferential treatment by regulators (Berkman et al., 2011), and implicit government bailouts of failing firms (Khwaja and Mian, 2005; Borisova and Megginson, 2011), suggesting they are less exposed to risks in cases of adverse events. Consistent with this conjecture, prior studies on Chinese capital market find that, for firms that operate in disadvantaged situations such as financial distress, poor financial prospect, and low provincial institutional development, government-controlled firms are more likely to be propped up by controlling shareholders (Jian and Wong, 2010), receive more favorable tax treatment (Wang and Shailer, 2012), have a lower cost of debt (Shailer and Wang, 2015). As government-controlled firms are treated preferentially over non-government-controlled firms, investors may perceive government-controlled firms to be less risky compared to non-government-controlled firms if they are subject to enforcement actions by the CSRC. The above discussion leads to our second hypothesis: Hypothesis 2: The impact of the CSRC enforcement actions on the cost of equity is weaker for government-controlled firms than for non-government-controlled firms. 11

12 4. Research Design Measuring the cost of equity To measure the cost of equity, we estimate ex ante cost of equity rather than using realized returns as prior studies suggest that realized returns are a biased and noisy measure of expected returns, while the implied approach is more precise (Gebhardt et al., 2001; Fama and French, 2002). In the main tests, we estimate cost of equity using the PEG ratio approach introduced by Easton (2004). By comparing several approaches of cost of equity estimation, Botosan and Plumlee (2004) conclude that the PEG ratio approach performs consistently well and is predictably associated with other firm risk proxies, such as beta and leverage. Under PEG ratio approach, the cost of equity is derived from the following equation: r_peg = 2 1 (1) where r_peg is the estimated implied cost of equity capital; eps t+1 is the one-year-ahead earnings-per-share (EPS); eps t+2 is the two-year-ahead EPS; P t is the share price at the end of year t. This approach assumes zero growth in abnormal earnings beyond the forecast horizon. In the original equation introduced by Easton (2004), eps t+1 and eps t+2 represent one-year-ahead and two-year-ahead forecasted EPS reported by financial analysts. Since the analysts forecast data are not generally available in China, using analysts forecast reduces our sample size substantially. Therefore, we follow Chen et al. (2011) to use realized EPS in year t + 1 and t + 2 to replace the forecasted EPS. One limitation of the PEG ratio approach is that it only applies to firms with 12

13 positive EPS growth since the estimation involves a square root. Observations with negative EPS growth are therefore eliminated from the sample, which may result in selection bias. To address this issue, following Chen et al. (2011) we use an alternative cost of equity measure estimated based on the industry approach developed by Gebhardt et al. (2001) (hereafter GLS) in our sensitivity tests. The Model for Testing Hypothesis 1 The regression model used to test the first hypothesis is as follows: r_peg i,t = β 0 + β 1 ENFORCE i,t + β 2 BETA i,t + β 3 SIZE i,t + β 4 BMRATIO i,t + β 5 LEV i,t + β 6 GROWTH i,t + β 7 VOLUME i,t + β 8 TOP i,t + β 9 LOSS i,t + β 10 AUDITOR i,t + β 11 CROSSLIST i,t + (2) β 12 MKTINDEX i,t + ΣIND i,t + ΣYEAR i,t + ε i,t where r_peg is the estimated cost of equity capital. The test variable is ENFORCE, which equals 1 if a firm or its top management is subject to enforcement actions due to the violation of laws and regulations on financial reporting in year t and 0 otherwise. Since Hypothesis 1 predicts that firms subject to enforcement actions have higher cost of equity, we expect β 1 to be positive. We also control for other factors that may impact a firm s cost of equity, which are discussed below. According to the capital asset pricing model (Sharpe, 1964; Lintner, 1965), market beta represents the systematic risk of a firm and is related to the cost of equity. Firms with higher systematic risk may have higher cost of equity, therefore BETA is included as a control variable, and a positive sign is expected. It is estimated by regressing daily return data in past 52 weeks against the market proxy. For firms listed on the Shanghai Stock Exchange (SSE) and the Shenzhen Stock Exchange (SZSE), the market proxies used are the Shanghai Composite Index and the Shenzhen Composite Index respectively. This estimation method requires that firms have been 13

14 listed for at least 52 weeks to be included in our sample. Firm size (SIZE) is also controlled for, because larger firms tend to have a higher disclosure level (Lang and Lundholm, 1993), which reduces information asymmetry and consequently investors require lower returns due to the lower risks. SIZE is measured as the natural logarithm of the firm s total assets. Book-to-market ratio (BMRATIO) is found to be positively related to expected cost of equity (Fama and French, 1992; Gebhardt et al., 2001). Fama and French (1992, 1995) suggest that book-to-market ratio captures firms distress risk, therefore firms with high book-to-market ratio (high distress risk) are penalized with higher costs of capital. BMRATIO is calculated as the book value of equity divided by the market value of equity. We include leverage (LEV) because firms leverage is found to be positively correlated with the cost of equity capital (Botosan et al., 2004). Gebhardt et al. (2001) suggest that long-term growth rate has negative association with expected cost of equity. Therefore we include growth rate as a control variable, which is measured as the average sales growth rate over the last three years, and expect it to have a negative sign. Brennan and Subrahmanyam (1996) suggest that illiquidity can lead to higher costs of equity. Consistent with Chen et al. (2011), we use trading volume (VOLUME) to control for share liquidity, and expect it to be negatively related with the cost of equity. VOLUME is measured as trading volume divided by total number of shares outstanding CROSSLIST is a dummy variable equal 1 if a firm is cross-listed on an overseas stock exchange and 0 otherwise. Prior studies (e.g., Chen et al., 2006; Gul et al., 2010) suggest that firms issuing shares to foreign investors are subject to stricter regulatory requirements and operate in more transparent information environments, suggesting a lower cost of equity for firms cross-listed on overseas stock markets. TOP is the proportion of shares held by the largest shareholder. Chinese listed firms are 14

15 characterized by concentrated ownership, which may give rise to the agency problem between the controlling and minority shareholders and increases the expropriation risk to minority shareholders. Consistent with this concern, Wang and Shailer (2013) find that ownership concentration has negative relation with firm performance in emerging markets. In such circumstances, shareholders may require higher returns to compensate for their higher risks. We thus expect a positive association between TOP and the cost of equity. High-quality auditors can perform a corporate governance role by reducing information asymmetry and agency problems (Fan and Wong, 2005; Gul et al., 2010). To control for the impact of auditor quality, we include in the model AUDITOR, a dummy variable equal 1 if a firm is audited by one of the top 10 audit firms in China based on the comprehensive ranking of the Chinese Institute of Certified Public Accountants (CICPA) and zero otherwise. CICPA s comprehensive ranking is based on an audit firm s service revenue, the number of chartered accountants in the firm as well as the penalty record. We expect the coefficient of AUDITOR to be negative. Firth et al. (2011) argue that investors tend to hold ex ante perception that financial frauds are more likely to occur in places with lower market development levels. Therefore investors may require a higher cost of equity for firms `in less developed regions as compensation. We thus include MKTINDEX in the model to account for provincial market development level in China and expect it to have a negative sign. Follow Firth et al. (2011), we use the regional development index compiled by China's National Economic Research Institute (NERI) (Fan et al., 2011) to measure the level of market development in each province. A higher score indicates the province is more developed. Industry and year dummies are also included in the model to control for industry and year effects. 15

16 The estimation method is OLS regression with robust standard errors to account for autocorrelation and heteroscedasticity. In our sensitivity tests, we also use 2SLS model to control for the potential endogeneity issue of enforcement actions and government control. Model for Testing Hypothesis 2 The model for testing Hypothesis 2 is developed based on Equation 2. An indicator variable GOV, which represents government control, and an interaction term between the enforcement action and government control are added to Equation 2. GOV is an indicator variable equal 1 if a firm is ultimately controlled by the central government or a local government. Other variables are defined in Equation 2. The regression model for testing Hypothesis 2 is presented below: r _PEG i,t = β 0 + β 1 ENFORCE i,t + β 2 GOV i,t + β 3 ENFORCE i,t *GOV i,t + (3) β 4 BETA i,t + β 5 SIZE i,t + β 6 BMRATIO i,t + β 7 LEV i,t + β 8 GROWTH i,t + β 9 VOLUME i,t + β 10 TOP i,t + β 11 LOSS i,t + β 12 AUDITOR i,t + β 13 CROSSLIST i,t + β 14 MKTINDEX i,t + ΣIND i,t + ΣYEAR i,t + ε i,t In this model, (β 1 + β 3 ) represents the impact of enforcement actions on the cost of equity for government-controlled firms, while β 1 represents the impact of enforcement actions on the cost of equity for non-government-controlled firms. Therefore, the coefficient of the interaction term, β 3, reflects the difference between the impact of enforcement actions on the cost of equity for government-controlled firms and for non-government-controlled firms. If β 3 is negative, it indicates the impact of enforcement action on the cost of equity is weaker for government-controlled firms than for non-government-controlled firms, and thus supporting Hypothesis 2. 16

17 Sample Selection and Data Our sample is all Chinese listed corporations issuing shares on the Shanghai Stock Exchange or the Shenzhen Stock Exchange during with available data for regression analysis. We choose 2003 as our sample start year because Code of Corporate Governance for Listed Companies in China took effect in 2002, in which the disclosure of ultimate controller in annual reports becomes mandatory for listed firms. Other corporate governance practices are also improved as a result of the enactment of this code. However, the disclosed information about ultimate controller and corporate governance was still quite limited in Since this study aims to examine the impact of government control and the effectiveness of the CSRC in the context of China s recently improved financial environment, we decide to select year 2003 as the beginning year. Our sample period ends in 2011 because we need to use the observations in the most recent two years (2012 and 2013) to obtain one-year-ahead and two-year-ahead realized EPS for estimating the cost of equity capital for our sample firms. We use various sources to obtain data for this study. We use WIND to collect the raw data on ownership structure, and accounting and market information, and China Securities Markets and Accounting Research Database (CSMAR) to collect corporate governance data. We obtain scores for the provincial index of marketization from Fan et al. (2011). The information of top 10 auditors is collected from the official website of the Chinese Institute of Certified Public Accountants ( The raw data of enforcement actions are obtained from WIND. We include enforcement actions directly carried out by the CSRC as well as those carried out by other regulatory agencies (e.g., the stock exchanges, Ministry of Finance, and the Customs) because all financial frauds committed by listed firms are ultimately 17

18 regulated by the CSRC. A firm is classified as subject to enforcement if it or its top management is subject to enforcement actions due to the violation of laws and regulations on financial reporting in a year. There are 501 enforcement actions during our sample period. After merged with the data for cost of equity, government control, and other variables, 204 enforcement observations are included in the final sample. Summary Statistics The distributions of the fraud firms by year and industry are reported in Table 1. Panel A of Table 1 shows that there is no monotonous trend in terms of the year distribution. Based on our sample, the number of firms subject to enforcement actions peaked in 2005, and fluctuates moderately among other years. Panel B of Table 1 presents the industry distribution. The percentage of fraud firms within each industry varies. The two industries with highest incidence of enforcement actions are journalism and media industry and agriculture industry, while there are six industries with no fraud observations in the sample. Table 1 here Table 2 reports the descriptive statistics for fraud firms (204 observations) and non-fraud firms (5,637 observations) in the full sample. All continuous variables are winsorized at the 1st and 99th percentiles to mitigate the influence of outliers. The average level of the cost of equity for non-fraud firms is 15.7%, comparable to the average cost of equity of 17.1% for a sample of 17 emerging markets (excluding China) reported in Chen et al. (2009b). The cost of equity for fraud firms is 25.7%, substantially higher than non-fraud firms. The proportion of government-controlled firms in fraud group is much lower than that in non-fraud group (46.1% compared with 68.3%). Consistent with our expectation, the summary statistics indicate that 18

19 firms being regulated by the CSRC tend to have higher costs of equity. In addition, the fraud firms are less likely to be audited by the top 10 audit firms (28% versus 19.6%). Surprisingly, fraud firms have slighter lower market beta than non-fraud firms, but the variance is higher. For financial statement variables, there is a significantly larger proportion of loss firms and highly levered firms in the fraud group, suggesting that poor financial situation and high leverage may lead to higher incidence of fraud. 5. Empirical Results Table 2 here Results for Hypothesis 1 Main Results Hypothesis 1 predicts that firms subject to enforcement actions have higher cost of equity. The results for the first hypothesis test are reported in Table 3. Column 1 shows the results of the main model. The coefficient on ENFORCE is positive (β = 0.045) and significant at the 1% level, indicating that firms subject to enforcement actions have higher costs of equity than non-fraud firms, and thus providing strong support for the first hypothesis. For control variables, consistent with our predictions, beta, leverage and book-to-market ratio, and loss firms are positively associated with the cost of equity; and size, growth, and provincial market development levels have negative associations with the cost of equity. Contrary to our prediction, ownership concentration (TOP) is negatively related with the cost of equity. Share liquidity (VOLUME) and cross-listing do not have a significant relation with the cost of equity. Table 3 here 19

20 Alternative measure of cost of equity Estimating the PEG ratio as a measure of the cost of equity requires positive EPS growth, which may bias our sample towards growth firms. To account for this potential bias, we use the industry approach introduced by Gebhardt et al. (2001) (hereafter GLS) to estimate an alternative ex ante measure of the cost of equity. The valuation model is as follows: _ _ _ _ _ (4) where P t is the share price at time t; B t is the book value of equity at time t; FROE t+i is the forecasted return on equity (ROE) for period t + i; and r_gls is the estimated implied cost of equity capital. The industry approach assumes that the ROE of a firm linearly converges to the industry ROE beyond the forecast horizon. Gebhardt et al. (2001) use analysts forecast data for the first three years, which is the forecast horizon; and estimate the ROE for the following years through simple linear interpolation between period t + 3 ROE and the industry median ROE. In their model, the total estimating horizon is 12 years. A terminal value is estimated based on the forecasted ROE in year 12. Since the analysts forecast data are not generally available in China, we follow Chen et al. (2011) using reported ROE from t + 1 to t + 3 to replace the forecasted ROE. For example, to estimate the cost of equity in 2005, the reported ROE from 2006 to 2008 is used. In estimating the ROE for the following nine years, we follow Gebhardt et al. (2001) to employ the linear interpolation approach. In addition, Gebhardt et al. (2001) assume a constant dividend payout ratio when estimating the future book value. Consistent with them, we assume that the dividend payout ratio 20

21 remains at the same level as in year 3 for the following nine years when estimating the cost of equity. The results using GLS measure are reported in Column 2 of Table 3. The test variable ENFORCE remains positive and highly significant (at 1% level), indicating our results are robust to the selection of cost of equity measures. Endogeneity of Enforcement Actions It is plausible that fraud and cost of equity are determined simultaneously, resulting in simultaneity (or reverse causality) bias. For example, firms with certain characteristics related to the cost of equity may be more likely to face enforcement actions. We use the 2SLS approach to address the potential issue of reverse causality. In the first stage, we use a probit model to estimate the probability of a firm receiving enforcement actions. The first stage model includes all variables in the second stage model (Equation 2), plus additional regressors likely to be related to enforcement actions: GOV, OUTDIR, BOARDSIZE, DUAL, DIRBKGRD, and INSTINV. GOV is an indicator variable equal 1 if a firm is ultimately controlled by the government and 0 otherwise. The literature suggests that external financing (e.g., Dechow et al., 1996) and executive compensation (e.g., Denis et al., 2006) are two major incentives to commit financial fraud. Prior studies find that firms controlled by the government have preferential access to external funds at lower costs (e.g., Khwaja and Mian, 2005; Shailer and Wang, 2015) and tend to not adopt performance-related compensation scheme (e.g., Firth et al., 2006), suggesting they are less likely to commit financial fraud. It is argued that board attributes may impact the likelihood of a firm committing fraud (e.g., Beasley, 1996; Farber, 2005; Firth et al., 2011), we therefore include four variables for board characteristics: OUTDIR is the proportion of independent directors on the board, BOARDSIZE is the number of directors on the 21

22 board, DUAL is an indicator variable equal 1 if the positions of CEO and chair of the board are held by the same person and 0 otherwise, and DIRBKGRD is the percentage of directors that have relevant accounting, finance or economic background. Although institutional investors are relatively new participants in Chinese securities market, Wu et al. (2014) report that they do perform effective external monitoring in recent years by reducing the incidence of fraud. We thus also include INSTINV, which is an indicator variable equal 1 if a firm has institutional investors and 0 otherwise; In the second stage of the 2SLS model, we include the fitted values of enforcement actions obtained from the first stage as an explanatory variable in Equation 2. The results for the first and second stage of the 2SLS regression are shown in the last two columns of Table 3. After accounting for potential endogeneity problems, the coefficient of enforcement action is still positive and significant (p = 0.000). It suggests that our main results are robust to controlling for the potential endogeneity of enforcement actions. Results for Hypothesis 2 Main Results Table 4 presents the results for testing the impact of government control on the relation between enforcement actions and the cost of equity. The results of our main model using r_peg as the dependent variable are reported in Column 1. For non-government-controlled firms, firms that are subject to enforcement actions have significantly higher costs of equity than those not subject to enforcement actions (β 1 = 0.074, p = 0.000); while for government-controlled firms, there is no significant difference in the cost of equity between firms that are subject to enforcement actions 22

23 and those are not (p = 0.55 for H 0 : β 1 + β 3 = 0). The coefficient on the interaction term is significantly negative (β 3 = , p = 0.000), indicating that the impact of enforcement actions on the cost of equity is significantly lower for government-controlled firms than for non-government-controlled firms and thus Hypothesis 2 is supported. We obtain similar results (reported in Column 2 of Table 4) when using GLS method to estimate the cost of equity. Endogeneity of Government Control Table 4 here Apart from enforcement actions, government control can also be endogenous. It is plausible that the government decides which firms to control based on their cost of equity. We thus use 2SLS approach to account for the potential reverse causality. To perform the 2SLS analysis, we include two exogenous variables as instrumental variables in the first stage. The first variable is the number of listing years (LISTYEAR). One of the main purposes of the establishment of the Chinese stock market was to open an external financing channel for SOEs, therefore firms that were first listed on Chinese stock market were partially privatized SOEs, and the listing requirements favor SOEs against non-soes in early years. Therefore, we expect that the government is more likely to control firms that have been listed for a longer time. The second variable is EMPLOYEE, measured as the natural logarithm of total number of employees in a firm. Following the argument of Borisova and Megginson (2011), the state is inclined to control firms with a large number of employees due to the concern about employment rate. The results of the first and second stage of the 2SLS regression are reported in Columns 3 and 4 of Table 4, respectively. Consistent with the results of our main 23

24 model, the interaction term is significantly negative, indicating that our results are robust to accounting for the potential endogeneity of government control. Split Sample Test Using a single sample with interaction variables to test moderating effect can be less precise when coefficients of control variables differ between the groups examined (Hardy, 1993). We therefore use a split sample approach to test the effect of government control on the relations between enforcement actions and the cost of equity. We partition our sample into two sub-samples according to whether a firm is controlled by the government and re-run Equation 2. The results are reported in Columns 1 and 2 of Table 5 for government-controlled firms and non-government-controlled firms, respectively. Consistent with the results of our single sample test, there is no significant difference in cost of equity between firms that are subject to enforcement actions and firms that are not for government-controlled firms, while firms that are subject to enforcement actions have significant higher cost of equity for non-government-controlled firms. A χ 2 -test of differences in coefficients on ENFORCE for the two sub-samples shows that the impact of enforcement actions on the cost of equity is significantly lower for government-controlled firms than for non-government-controlled firms. Table 5 here Among the 1,897 firm years for non-government-controlled firms, 1,573 are privately-controlled by domestic individuals or families. There are 320 observations with various types of other non-government controlling shareholders, including collective enterprises, labor unions, and foreign investors. Four observations are jointly controlled by multiple types of controllers. Given the diverse nature of the 24

25 controlling shareholders of the 324 observations, including them in our sample may confound our results. To account for the potential confounding effect of these observations, we exclude them and re-run Equation 2 for the 1,573 privately-controlled observations. The results are reported in Column 3 of Table 5. The coefficient on ENFORCE is economically and statistically similar to the coefficient on ENFORCE for non-government-controlled sample (Column 2), indicating our results are not sensitive to the exclusion of non-government-controlled firms with different natures. Difference between Central and Local Government Control To investigate the potential different impact of central and local government control, we further partition government-controlled firms into two subgroups: firms controlled by the central government and firms controlled by local governments, and re-run Equation 2 for the two sub-samples. The results are reported in Columns 4 and 5 in Table 5 for central-government-controlled firms and local-government-controlled firms, respectively. For central-government-controlled firms, the coefficient on ENFORCE is not significant at traditional levels, While the coefficient of ENFORCE for local-government-controlled firms is significantly positive, indicating the enforcement actions do not significantly impact the cost of equity for firms controlled by the central government, but increases the cost of equity for firms controlled by local governments. The χ 2 -tests of differences in coefficients on ENFORCE across models for sub-samples show that the coefficients on ENFORCE for central-government-controlled firms and local-government-controlled firms are significantly lower than that for non-government-controlled firms, indicating that compared with non-government-controlled firms, the cost of equity for both the 25

26 central- and local-government-controlled firms are less affected by the enforcement action. Furthermore, the coefficient on ENFORCE for central-government-controlled firms is significantly lower than local-government-controlled firms, indicating that the impact of enforcements on the cost of equity is smaller for central-government-controlled firms than for local-government-controlled firms. The result may be attributed to investors perception that the central government is likely to have more sufficient resources to support firms under its control when adverse events occur. 6. Discussion and Conclusion Summary and Discussion The objectives of this study are to examine the relation between the CSRC enforcement actions and the cost of equity and whether government control moderates the relation. Our multivariate regression analysis shows that firms subject to enforcement actions tend to have higher cost of equity. The result is robust to the alternative measure of cost of equity and the use of the two-stage least squares approach to account for the potential endogeneity of enforcement actions. Our result suggests that the enforcement actions have effect on investors risk perception of firms in the long term. The finding complements Chen et al. (2005) and Aggarwal et al. (2014), who show that investors react negatively to the announcement of CSRC enforcement actions in the short term. We also find that the impact of enforcement actions on the cost of equity is greater for non-government-controlled firms than for government-controlled firms, and the relation between enforcement actions and the cost of equity is not significant for government-controlled firms. Our result is robust to the use of two-stage least 26

27 squares approach to account for the potential endogeneity of government control. Our finding provides similar insight as Chaney et al. (2011), who suggest that politically connected firms with lower financial reporting quality do not face higher costs of debt. While they focus on the perceptions of lenders in multiple markets (which do not include China), we specifically address the impact on equity investors perception in Chinese market. Additional analyses of the difference between central government control and local government control show that when subject to enforcement actions, local-government-controlled firms still experience an increase in cost of equity, although the magnitude is smaller than non-government-controlled firms; while the cost of equity for central-government-controlled firms is virtually unaffected. The finding might be explained by the ampler resources held by the central government to bail out firms under its control when they experience adverse events. Implications This study furthers our understanding of the positive impact of government control in the financial markets of emerging economies. Although some studies document inferior accounting and market performance of government-controlled firms compared to non-government-controlled firms (e.g., Chen et al., 2006), this study shows that government-controlled firms enjoy the benefit of lower equity financing costs, particularly when adverse events occur. This study complements and enriches the literature regarding the benefit of government control or political connection. For instance, Wang and Shailer (2012) find that corporate income tax is strategically used to prop government-controlled firms according to their financial prospects, and Chaney et al. (2011), Khwaja and Mian (2005), and Shailer and Wang (2015) emphasize the 27

28 preferential treatment of politically connected or government-controlled firms by debt investors and banks. We show the advantage of government control from a different perspective, which is the preferential treatment by equity investors in the event of financial fraud. In addition, despite the disadvantages of government control argued in the literature (e.g., Shleifer and Vishny, 1994), recently there is a general trend of increase in state ownership in emerging markets (Carney and Child, 2013). Using a sample of listed firms in the largest emerging market, China, this study helps explain why government control is still prevalent in emerging markets. Our results supports the view of Chen et al. (2009a) and Shailer and Wang (2015) that state ownership can be advantageous in a transitional economy with weak institutional environment. This study also has implications for the effectiveness of the CSRC enforcement actions. The increase in firms cost of equity when subject to enforcement actions shows that investors value the information conveyed by the CSRC regulation actions, which is consistent with the findings of Chen et al. (2005) and Aggarwal et al. (2014). Overall, this study indicates the regulatory environment in China s securities market is effective based on our sample in the recent decade. Limitations and Directions of Future Research Due to the limited analysts forecast data in China, in this study we follow Chen et al. (2011) using one-year-ahead and two-year-ahead reported EPS to replace analysts forecast data when estimating implied cost of equity. With the development of the financial services industry in China, the analysts forecast data are expected to be gradually enlarged and cover more firms, which may allow future studies to examine the cost of equity of Chinese listed firms using analyst forecast data. In addition, since 28

29 the institutional environment in China is dynamic and constantly developing, the results of this study may not be generalizable to future periods. Future studies can examine the impact of institutional changes when sufficiently long longitudinal panel data become available with the development of Chinese capital market. 29

30 References Aggarwal, R., Hu, M., Yang, J., Fraud, market reaction, and role of institutional investors in Chinese listed firms, Working Paper. Georgetown University. Allen, F., Qian, J., Qian, M., Law, finance, and economic growth in China. Journal of Financial Economics 77, Ashbaugh Skaife, H., Collins, D.W., Lafond, R., The effect of sox internal control deficiencies on firm risk and cost of equity. Journal of Accounting Research 47, Beasley, M.S., An empirical analysis of the relation between the board of director composition and financial statement fraud. Accounting Review 71, Berkman, H., Cole, R.A., Fu, L.J., Political connections and minority-shareholder protection: Evidence from securities-market regulation in China. Journal of Financial and Quantitative Analysis 45, Bian, J., China's securities market: Towards efficient regulation. Routledge, New York, the US. Biddle, G.C., Hilary, G., Verdi, R.S., How does financial reporting quality relate to investment efficiency? Journal of Accounting and Economics 48, Borisova, G., Megginson, W.L., Does government ownership affect the cost of debt? Evidence from privatization. Review of Financial Studies 24, Botosan, C.A., Disclosure level and the cost of equity capital. Accounting Review 72, Botosan, C.A., Plumlee, M.A., A re-examination of disclosure level and the expected cost of equity capital. Journal of Accounting Research 40, Botosan, C.A., Plumlee, M.A., Xie, Y., The role of information precision in determining the cost of equity capital. Review of Accounting Studies 9, Boubakri, N., Guedhami, O., Mishra, D., Saffar, W., Political connections and the cost of equity capital. Journal of Corporate Finance 18, Brennan, M.J., Subrahmanyam, A., Market microstructure and asset pricing: On the compensation for illiquidity in stock returns. Journal of financial economics 41, Bushman, R.M., Piotroski, J.D., Financial reporting incentives for conservative accounting: The influence of legal and political institutions. Journal of Accounting & Economics 42, Carney, R.W., Child, T.B., Changes to the ownership and control of East Asian corporations between 1996 and 2008: The primacy of politics. Journal of Financial Economics 107, Chaney, P.K., Faccio, M., Parsley, D., The quality of accounting information in politically connected firms. Journal of Accounting and Economics 51, Chen, D., Corporate governance, enforcement and financial development: The Chinese experience. Edward Elgar Publishing, Cheltenham, UK. Chen, G., Firth, M., Gao, D.N., Rui, O.M., Is China s securities regulatory agency a toothless tiger? Evidence from enforcement actions. Journal of Accounting and Public Policy 24, Chen, G., Firth, M., Gao, D.N., Rui, O.M., Ownership structure, corporate governance, and fraud: Evidence from China. Journal of Corporate Finance 12, Chen, G., Firth, M., Xu, L., 2009a. Does the type of ownership control matter? Evidence from China s listed companies. Journal of Banking & Finance 33, Chen, H., Chen, J.Z., Lobo, G.J., Wang, Y., Effects of audit quality on earnings management and cost of equity capital: Evidence from China. Contemporary Accounting Research 28, Chen, K.C., Chen, Z., Wei, K., 2009b. Legal protection of investors, corporate governance, and the cost of equity capital. Journal of Corporate Finance 15, Cooper, D.J., Dacin, T., Palmer, D., Fraud in accounting, organizations and society: Extending the boundaries of research. Accounting, Organizations and Society 38, De Jonge, A., Corporate governance and China's H-share market. Edward Elgar Publishing, Cheltenham, UK. Dechow, P., Ge, W., Schrand, C., Understanding earnings quality: A review of the proxies, their determinants and their consequences. Journal of Accounting and Economics 50, Dechow, P.M., Sloan, R.G., Sweeney, A.P., Causes and consequences of earnings manipulation: An analysis of firms subject to enforcement actions by the SEC. Contemporary Accounting Research 13, Denis, D.J., Hanouna, P., Sarin, A., Is there a dark side to incentive compensation? Journal of Corporate Finance 12, Easley, D., O'Hara, M., Information and the cost of capital. Journal of Finance 59, Easton, P.D., PE ratios, PEG ratios, and estimating the implied expected rate of return on equity capital. Accounting Review 79, Fama, E.F., French, K.R., The cross section of expected stock returns. Journal of Finance 47,