Corporate governance, value and performance of firms: New empirical results from a large international database

Transcription

1 Corporate governance, value and performance of firms: New empirical results from a large international database Abstract: Based on a large international database (2662 firms from 25 industries, operating in 24 countries) covering 55 governance factors, which span over 8 categories of corporate governance including board of directors, audit committee, charter/bylaws, antitakeover provisions, compensation, progressive practices, ownership and director education, the authors test the impact of corporate governance on firms value and performance. In line with earlier studies that exhibited a positive relationship between these variables, the present study documents an economically important and statistically strong correlation between governance, value and performance of the firm. We report that change of 1% in governance index is significantly associated with 0.19% increase in Stock Returns; 1.20% increase in Dividend Yield; 0.03% increase in Return on Assets; and 0.06% increase in Net Profit Margin. For Return on Asset and Net Profit Margin, the impact of one standard deviation change in governance is 4.9% and 5.65% respectively. Governance index is also positively associated with Tobin s Q (0.26% increase), and the magnitude of this effect is large, as one standard deviation change in governance results in about 15% increase in the value of Tobin s Q. Keywords: Corporate governance; governance metrics, ratings, rankings and scoring; firm value; firm performance. JEL Codes: G30 1

2 1. Introduction Corporate Governance has become very important to today s market practitioners and turns out to be a popular area of discussion around the globe. Investors regard corporate governance as an important criterion when making investment decisions. According to Global Investor Opinion Survey from McKinsey (2002), 15% of European institutional investors consider corporate governance to be more important than firms financial issues, such as profit performance or growth potential. Additionally, 22% of European institutional investors are willing to pay an average premium of 19% for a well governed company. At the same time, more and more countries started to tighten up rules and regulations in the governance field by adopting new standards, or codes of best practice to establish guidelines for publicly listed companies in an attempt to improve the overall governance of the firm. In OECD Principles of Corporate Governance (2004), it is acknowledged that an effective corporate governance system will lower the cost of capital and encourage firms to use resources more efficiently, thereby, underpinning growth. All these implicitly and explicitly support the belief of many: better corporate governance will result in higher firm value and more profitable firm performances. At a theoretical level, agency theory identifies several reasons why good corporate governance increases firm value and performance (Schleifer and Vishny, 1997). Basically, good governance involves better monitoring, greater transparency and public disclosure between the principal (the investor) and the agent (the manager). This leads to an increase in investor trust and, in the meantime, to a decrease in manager discretion and rent expropriation. Well governed firms are supposed to be less risky, have more efficient operations, and involve reduced auditing and monitoring costs. These elements tend to alleviate the cost of capital and generate higher expected cash flow stream, which in turn create higher firm valuation and higher performances. There exists different strains of studies that wish to verify this 2

3 belief, and already present increasing evidence that better corporate governance leads to higher firm value and higher performance. However prior works are either based on studies of the link on certain aspects of corporate governance 1, or on single country analysis 2, or based on cross sectional analysis 3. In this paper, our purpose is to add to this literature by re-examining the links between corporate governance, firm value and performance using a far more extensive database than the often-used ones. We use data of the largest corporate governance data provider to institutional investors, RiskMetrics / Institutional Shareholder Services. It has a distinct advantage over others as a data provider in that it is based on 55 governance factors for international companies 4, which span over 8 categories of corporate governance including board of directors, audit committee, charter/bylaws, antitakeover provisions, compensation, progressive practices, ownership and director education. We find an economically important and statistically strong correlation between governance, value and performance of the firm. We report that change of 1% in governance index is significantly associated with 0.19% increase in Stock Returns; 1.20% increase in Dividend Yield; 0.03% increase in Return on Assets; and 0.06% increase in Net Profit Margin (only at 10% level for this latter result). If we consider standard deviation change in governance, we obtain 4.9% increase in Return on Asset, and 5.65% change in Net Profit Margin. Governance index is also positively associated with Tobin s Q since it generates a 0.26% increase, and the magnitude of this effect is large, as one standard deviation change in governance results in about 15% increase in the value of Tobin s Q. 1 For example, board composition, shareholder rights, executive remuneration, insider ownership, or takeover defenses, see Hermalin and Weisbach (1998). 2 Especially the United States, see Gompers et al. (2003), Bebchuk et al. (2008), Core et al. (2006), but also Black (2001) and Black et al. (2006a) on Russia, Black et al. (2006b) on Korea, Drobetz et al. (2004) on Germany, and Beiner et al. (2006) on Switzerland. 3 See for example Drobetz et al. (2004) with data from a single study year. 4 The database contains up to 61governance factors for US companies. 3

4 The paper proceeds as follows. Section 2 gives a summary of related research and draws the set of our hypotheses. Section 3 describes the data and summarizes our firm-level value and performance variables. Section 4 reports on the relation between corporate governance measures, stock market performance, Tobin s Q, and operating performance (ROA, NPM). Section 5 concludes. 2. Literature background, and hypotheses From a theoretical point of view, corporate governance issues arise due to the separation of ownership and management. The principal-agent theory is the starting point of most of the discussions on corporate governance (Schleifer and Vishny, 1997). Agency problems may affect the firm value and performance through two ways: the expected cash flow for investors, and the cost of capital. First, agency problems make investors pessimistic, as they believe that future cash flow will be diverted. Alternatively, good governance increases investor trust and willingness to pay more, while it also renders manager diversion costly and expropriation unlikely. With good governance, more of the firm s profit would come back to (the investors) as interest or dividends as opposed to being expropriated by the entrepreneur who controls the firm (La Porta et al. 2002, p. 1147). If normally risk and expected return are negatively related since riskier stocks have to be compensated by a higher expected rate of return and involve higher costs in terms of monitoring, investors perceive well governed firms as less risky and better monitored. Consequently, they tend to apply a lower expected rate of return, which leads to a higher firm valuation. Also, as shown by Jensen and Meckling (1976), better governed firms might have more efficient operations, resulting in a higher expected future cash-flow stream. Second, the cost of capital is negatively related with measures of protection of 4

5 shareholder rights, and positively related with general measures of the quality of legal institutions (La Porta et al., 2002; Gompers et al., 2003). In that perspective, good governance would thus decrease the cost of capital since it reduces shareholder s monitoring and auditing costs (Drobetz et al. 2004; Lombardo and Pagano, 2002; Errunza and Miller, 2000). Therefore, better corporate governance structure and practice leads to better corporate performance, lower agency cost, and higher stock performance. From an empirical point of view, large strands of the empirical literature support this hypothesis. However most of the literature focus on certain countries (mainly the US), or certain aspects of governance such as, for example, board composition, insider ownership, executive compensation, Delaware corporate law, or takeover defenses 5. Here, the most recent and closely related literatures are Gompers et al. (2003), Bebchuk et al. (2008), Core et al. (2006), Klapper and Love (2004), Drobetz et al. (2004), Beiner et al. (2006) and Black et al. (2006a). We present the papers simply by the way they measure corporate governance. Yet, here, we do not give a summary of all sources of data that has been used in the corporate governance literature 6. We will see that while it is well established that particular aspects of corporate governance affect firm value, the overall effect of corporate governance on firm value or performance remains unclear. On that basis, we draw a set of hypotheses to be tested on the data provided by RiskMetrics / Institutional Shareholder Services Investor Responsibility Research Center (IRRC) 5 See Shleifer and Vishny (1997) for a survey, and also Demsetz and Lehn (1985), Morck et al. (1988), Stulz (1988). 6 For some recent and critical attempts to provide a survey of the data available, see Ertugrul and Hedge (2009), Koehn and Ueng (2005), or Bebchuk and Hamdani (2009). 5

6 The Investor Responsibility Research Center (IRRC) publishes detailed listings of corporate governance provisions for individual firms in corporate takeover defenses. Data are derived from a variety of public sources (corporate bylaws and charters, proxy statements, annual reports, 10K, and 10Q documents). All sample firms are drawn from the Standard & Poor s 500 and the annual lists of Fortune, Forbes, and Business Week. The report expands several hundreds firms, and are published in 1990, 1993, 1995, and Gompers et al. (2003) construct a firm-level governance index (G-Index) based on the prevalence of 24 governance provisions in firms surveyed by the Investor Responsibility Research Center. They add one point for every provision that reduces shareholder rights. They found that firms with higher index values, reflecting poor governance, e.g. less shareholder rights, have significantly lower valuation than firms with lower index values, though not necessarily lower operating performance. Bebchuk et al. (2008) find similar results with a governance index (entrenchment index) consisting of a smaller set of provisions (6 provisions). Finally, Core et al. (2006), contrary to Gompers et al. (2003), show that firms with weak shareholder rights exhibit systematically significant operating underperformance. However, studies using IRRC data can only examine the effects of the external mechanisms of corporate governance. G-index is more like a takeover defense index than a measurement of overall corporate governance. Secondly, since the reports are based on the largest US firms, there may be variations in the list of included firms from volume to volume, leading potentially to a sample bias problem. At last, the reports are not published each year, therefore these studies assume that firms governance provisions reported in a given IRRC volume were in place during the period immediately following the publication of the volume until the publication of the subsequent IRRC volume. Consequently, some important changes in corporate 6

7 governance may not be reported adequately Credit Lyonnais Securities Asia (CLSA) The CLSA report includes corporate governance rankings on 495 companies in 25 countries. The sample is selected based on two criteria: firm size and investor interest. The CLSA corporate governance questionnaire covers 7 broad categories. The questionnaire is then completed by Credit Lyonnais analysts in each country for the companies that they cover. They add one point to each Yes answer and then the percent of positive response to questions in each category is reported. Klapper and Love (2004) use firm-level data of 374 firms from 14 emerging countries. Their main governance index is the average of the first 6 categories in the CLSA report. They report that better corporate governance is highly correlated with better operating performance and higher market valuation. However this index is highly based on analysts subjective views. About 70% of the questions are based on objective facts and the remaining questions represent analysts opinion, which could be biased by knowledge of stock returns. Additionally, since CLSA has conducted only one study, the data generated from this study is quite static Single-market survey-based governance index These firm-specific corporate governance indexes are constructed by following broad surveys among listed companies in a single market. Black et al. (2006b) construct a Korean Corporate Governance Index (KCGI) for E.g., for instance, if there is no data for the period [ ], then data on [1990] is used instead. Respectively for missing data on [1994], data of [1993] is used; and for missing data on the period [ ], data of [1995] is used. 7

8 Korean companies based on a survey of corporate governance practices by the Korea Stock Exchange in The survey was sent out to all listed firms on the Korea Stock Market. The authors extract 38 variables from the survey questions, which are classified into 4 sub-indices, and then they combine sub-indices into the overall index-kcgi. They reported a worst-to-best change in KCGI predicts a 0.47 increase in Tobin s Q. Drobetz et al. (2004) document a positive relationship between governance practices and firm valuation for German public firms by constructing broad corporate governance rating related to the German Corporate Governance code. To construct their sample, they sent out questionnaires to 253 German firms in different market segments and received answers from about 36% of these firms. They assume constant historical ratings, due to the fact that their corporate governance data are limited to one observation, March Beiner et al. (2006) sent out a questionnaire based on the suggestions and recommendations of the Swiss Code of Best Practice to all Swiss firms quoted at the Swiss Stock Exchange in The index consists of 38 governance attributes divided into 5 categories. They reported that an increase in the corporate governance index by one point causes an increase of the market capitalization by roughly 8.52%. However there are several limitations with these studies. Firstly, most of the studies are based on one single year, or work under the assumption of constant historical ratings. Secondly, a country case study raises the question of generalization to other countries. And thirdly, since the index is created based on a survey, they bear all the problems that a survey study might have in statistical analysis Our work on the RiskMetrics / Institutional Shareholder Services data We contribute to the literature presented above by re-examining the links between 8

9 corporate governance, firm value and performance, using a far more extensive and much broader in scope of governance database than the often-used ones. We use the CGQ index (Corporate Governance Quotient) from RiskMetrics / Institutional Shareholder Services which is calculated on the basis of a rating system that incorporates 8 categories of corporate governance, leading to 55 governance factors. In this paper, the study period covered is , which yields the largest number of reporting firms with complete and consistent data. We focus on overall (aggregated) corporate governance ratings for a large range of international firms. Our sample is constructed with information on 2662 firms in 24 countries. They are: Austria, Australia, Belgium, Canada, Denmark, Finland, France, Germany, Greece, Hong Kong (China), Italy, Ireland, Japan, Luxembourg, Netherlands, New Zealand, Norway, Portugal, Singapore, Sweden, Switzerland, Spain, South Korea, and United Kingdom. Our sample-firms are from 25 industries: Diversified Financials, Capital Goods, Technology Hardware & Equipment, Materials, Commercial Services & Supplies, Consumer Durables & Apparel, Media, Insurance, Pharmaceuticals & Biotechnology, Transportation, Food Beverage & Tobacco, Banks, Telecommunication Services, Utilities, Energy, Automobiles & Components, Real Estate, Household & Personal Products, Software & Services, Retailing, Hotels Restaurants & Leisure, Food & Staples Retailing, Health Care Equipment & Services, Semiconductors & Semiconductor Equipment, Consumer Services. The relations we want to revisit with our data are described below. A Corporate governance and stock market performance The literature so far has identified a positive relationship between corporate governance and stock market performance. This logically leads us to work on the following hypothesis: H1: Better governed firms should have higher stock market performances, measured 9

10 on the basis of Stock Return or Dividend Yield. B Corporate governance and firm value The general consensus here is that corporate governance and firm value are positively and significantly correlated. We will thus consider the following assumption: H2: Better governed firms should have higher value, measured by the Tobin Q. C Corporate governance and operating performance Though there is no convergent result on the relation between corporate governance and operating outcome (see above the opposed results by Gompers et al. (2003) and Core et al. (2006)), we elaborate on the following assumption: H3: Better governed firms should have higher operating performance, measured by Return on Assets or Net Profit Margins. In the following section, we report the relationship between governance and stock market performance, firm market valuation as well as its operating performance. 3. Governance Index Constructions and Definition of Variables In this section we provide detailed description of the construction of corporate governance measure and the variables we use in our empirical analysis Corporate Governance Quotient Prior to being acquired by RiskMetrics in 2007, Institutional Shareholder Services operated independently as the largest corporate governance data provider to institutional investors. Institutional Shareholder Services developed its corporate governance rating system to assist institutional investors in evaluating the impact that a firm s corporate governance structure and practices might have on performance. The 10

11 goal of the rating is to provide objective and complete information on firm s governance practices. Importantly, the ratings are not tied to any other service provided by RiskMetrics / Institutional Shareholder Services and firms do not pay to be rated, although they are invited to check the accuracy of the ratings. The only way a firm can improve its rating is to make publicly disclosed changes to its governance structure and / or practices. The Corporate Governance Quotient (hereafter CGQ) is the output of a corporate governance scoring system that evaluates the strengths, deficiencies and overall quality of a company s corporate governance practices. It is updated daily on over 7500 companies worldwide. These ratings are based on a single set of policy standards inspired by OECD principles. CGQ rating for each company is generated by detailed analysis of its public disclosure documents (i.e. Proxy Statement, 10K, 8K, Guidelines ), press releases and company web sites. CGQ is calculated by adding 1 point if the firm under scrutiny meets the minimum accepted governance standard. The score for each topic reflects a set of key governance variables. Each variable is evaluated on a standalone basis. Some variables are also looked at in combination under the premise that corporate governance is improved by the presence of selected combinations of favorable governance provisions. For example, a company that has a board with a majority of independent directors and all independent key board committees (audit, etc.) receives higher ratings for each of these attributes in combination than it would if it had either one of them in isolation. Next, each company s CGQ is compared with other companies in the same index (here the index is MSCI EAFE index 8 ). All scores 8 It is a stock market index of foreign stocks, from the perspective of North American investors. The index is market capitalization weighted (meaning that the weight of securities is determined based on their respective market capitalizations.) The index targets coverage of 85% of the market capitalization of the equity market of all countries that are a part of the index. It is maintained by Morgan Stanley Capital International. The EAFE acronym stands for Europe, Australia, Asia and Far East. 11

12 are relative (percentile basis). For example Company A scores 24% (or 0.24) CGQ index score, this means that Company A is doing a better job (outperforming) in terms of corporate governance practices and policies than 24% of the companies in the MSCI EAFE index. Table 1 shows the corporate governance variables. A further detailed description of governance standards with the inclusion of the 8 different categories is provided in the Appendix. The data also provides sub-scores for each category, yet, the sub-scores are provided only for Canada and UK, therefore, we do not include sub-scores in this study. Table 1 Corporate Governance Quotient criteria Board Structure Audit Board Composition Audit Committee Nominating Committee Audit Fees Compensation Committee Auditor Rotation Governance Committee Auditor Ratification Board Structure Executive and Director Compensation Board Size Cost of Option Plans Changes in Board Size Option Re-Pricing Cumulative Voting Shareholder Approval of Option Plans Boards Served On - CEO Compensation Committee Interlocks Boards Served On - Other than CEO Director Compensation Former CEO's Pension Plans for Non-Employee Directors Chairman / CEOs Separation Board Guidelines Response To Shareholder Proposals Boards Attendance Board Vacancies Related Party Transactions Charter/Bylaws Features of Poison Pills Vote Requirements Written Consent Special Meetings Board Amendments Capital Structure Anti-Takeover Provisions 12 Option Expensing Option Burn Rate Corporate Loans Progressive Practices Retirement Age for Directors Board Performance Reviews Meetings of Outside Directors CEO Succession Plan Outside Advisors Available to Board Directors Resign upon Job Change Ownership Director Ownership Executive Stock Ownership Guidelines Director Stock Ownership Guidelines

13 Anti-Takeover Provisions Applicable Under Country(local)Laws Officer and Director Stock Ownership Director Education Director Education 3.2. Other Firm Variables In order to include firm-level accounting data, we merge the RiskMetrics / Institutional Shareholder Services database with some DataStream data. We use Stock Return and Dividend Yield as measures of firms stock performance, Tobin s Q as a measure of market valuation of the firm and Return on Asset (ROA), Net Profit Margins (NPM) as two main measures of firms operating performances (see more details on the choice of these dependent variables in paragraphs 4.2. to 4.4.). A summary of all the variables used in this article can be found in Table 2. Table 2 Summaries of Firm-Level Performance Variables Variables Description Stock Return Average Annual Return Dividend Yield Dividend Per Share as a Percentage of the Share Price Tobin s Q Market value of equity plus total liabilities divided by Total Assets ROA Return on Asset is the ratio of Income on Book Value of Total Asset NPM Net Profit Margin is the ratio of Income on Sales Size Logarithm of Total Assets R&D/Sales Ratio of [Research and Development] on Sales Sales Growth Average growth rate of Sales Intang Firm's intangible concentration estimated as [Property Plant and Equipment] on Sales MTBV Ratio of [Market Value of the Ordinary(Common) Equity] on [Book Value of Ordinary(Common) Equity] Market Capitalization [number of shares] * [share price] As argued by Denis (2001), an important issue in the analysis of the relationship between governance and performance is endogeneity. Firms with higher market values and performances could simply be more likely to choose better governance structures. One way to mitigate the problem of causality is to add appropriate control 13

14 variables, so as to test whether the relationship between governance and firm valuation are caused by some omitted variables. We therefore include the following as our control variable in this study: Size, the ratio of R&D and Sales, Sales Growth, intangible concentration, market to book value and market capitalization. We use the natural log of Total Assets, denoted Size as a measure of size. We control for Sales Growth simply because firms with good growth opportunities usually result in higher Tobin s Q. We control for intangible concentration as this may also result in higher Tobin s Q because, in general, the market values intangibles higher than their book values. We use Fixed Capital to Total Sales ratio as a measure of the relative importance of fixed capital in the firm s output, denoted Intang in the study. For stock market performance, we include the natural log of market capitalization (denoted LnMC) and natural log of market to book value (hereafter LnMTBV) to control for Size and the different investment opportunities available as well as growth opportunities. Since there are undoubtedly other, industry-related factors that affect valuation of firms, we decide to control for these industry factors with a set of SIC industry dummy variables. Finally, for some regressions, we include the natural log of market capitalization (denoted LnMC) and natural log of market to book value (hereafter LnMTBV) to control for Size and the different investment opportunities available as well as growth opportunities. 4. Corporate Governance and Firm Performance We conduct our analysis in three steps. The first is to explore the relationship between governance and firm s stock market performance. To investigate this relationship we use two measures, Stock Return and Dividend Yield. In the second step, in order to explore the relationship between governance and firm valuation, we use one valuation measure: Tobin s Q. The last step is to test the relationship between governance and firm s operating performances. Here the two measures that we use are ROA and 14

15 NPM Summary Statistics We begin by presenting some basic summary statistics on the variables that we include in this study. Table 3 Summary Statistics of Variables Mean Sd. Min 25% Median 75% Max CGQ Stock Return Dividend Yield Tobin's Q ROA NPM Size R&D/Sales Sales Growth Intang Ln(MTBV) Ln(MarketCapitalization) Table 3 provides a descriptive statistics of all variables included in our analysis. CGQ ranges from 0 to 1, with a mean and median of 0.54 and 0.56, and a standard deviation of Stock Return ranges from to 6.41, with a mean and median of 0.14 and 0.10, and a standard deviation of Dividend yield ranges from 0 to 45.98, with a mean and median of 2.41 and 1.89, and a standard deviation of Tobin s Q ranges from to 8.93, with a mean and median of 1.05 and 0.85, and a standard deviation of The mean and median of Return on Asset (hereafter ROA) are 0.07 and 0.06, the standard deviation is 0.084, and minimum and maximum values are and The mean and median of NPM are 0.17 and 0.10, with a standard deviation of 0.49, and minimum and maximum values of and

16 Table 4 provides the summary statistics of variables when we divide CGQ into five different quintiles (5%, 25%, 50%, 75%, and 95%). As can be easily observed, there is a slightly upward tendency in Tobin s Q as CGQ goes up, the mean of Tobin s Q of the highest quintile is 1.19 while that of the lowest is However, we included Size in the table to show that we cannot find this tendency with this variable. We can here simply conclude that firms with the highest CGQ ratings are not necessarily the largest ones. Table 4 Summary Statistics of Variables of CGQ in five Quintiles CGQ Stock Return Tobin's Q ROA NPM Size CGQ 5% 25% 50% 75% 95% No. Firms Mean/Median 0.13/ / / / /0.89 SD Mean/Median 0.12/ / / /0.12 SD / Mean/Median 0.96/ / / / /0.98 SD Mean/Median 0.07/ / / / /0.08 SD Mean/Median 0.19/ / / / /0.13 SD Mean/Median 16.94/ / / / /14.98 SD Table 5 provides the correlation of some of the main variables, with pair-wise correlation below the diagonal and Spearman correlation above diagonal. The significance levels are indicated with stars. The pair-wise correlation of CGQ and Tobin s Q is and the Spearman correlation between the two is , both of them are significant at 1% level. The correlation between CGQ and Size is negative at , and that of Spearman correlation is negative at however it is not significant. Table 5 Correlations of selected variables CGQ Tobins' Q Size R&D/Sales Sales Growth 16

17 CGQ *** *** ** Tobins' Q *** *** *** *** Size *** *** ** *** R&D/Sales *** *** *** ** Sales Growth *** *** This table provides the pair-wise correlation (below diagonal) and Spearman (above diagonal) correlations of Tobin s Q, CGQ, and control variables. The definition of all the variables can be found in Section 3. *** (**) (*) Indicates significance at 1% (5%) (10%), two-tailed level Governance and Stock Market Performance The choice of Stock Return and Dividend Yield are simple. If corporate governance matters for firm performance and this relationship is fully incorporated by the market, then a stock price should quickly adjust to any relevant change in the firm s governance. Dividend Yield is generally used as a measure of profitability. Also argued in Drobetz et al. (2004), Dividend Yield has the advantage that it is directly observable and is a stationary variable. Therefore, we expect that firms with better governance are more profitable and pay out higher dividends. Table 6 reports the regression results by using two performance measures as dependent variable respectively, and CGQ, LnMC and LnMTBV as independent variables. It also reports the sample size, adjusted R square, coefficients, standard errors as well as significance levels, which are indicated by stars. We can find a positive relationship between our governance indicator and all two stock market performance measures, all significant at 1% level. This can further be explained as firms with better governance have higher performance in the stock market, or improving firm s governance can result also in an improvement in the firm s stock market performance measured by Stock Return and Dividend Yield. One percentage change in governance indicator can result in around 0.19% change in Stock Return and 1.20% changes in Dividend Yield. 17

18 Table 6 Stock Market Performances Stock Return Dividend Yield CGQ *** *** (6.44) (7.14) LnMC *** *** (25.39) (-17.28) LnMTBV *** *** (23.41) (-4.89) Sample Size Adjusted R This table shows results of pooled OLS estimation of the determinants of firm-level market valuation and governance. The dependent variables are Stock Return, and Dividend Yield. CGQ is the governance indicator. LnMC is the natural log of Market Capitalization. LnMTBV is the natural log of market to book value. The definition of these variables can be found in section 3. Firm-level data is from T-values are shown in parentheses. *, **, and *** indicate significance level at 10%, 5% and 1% respectively Governance and Firm Value If good governance can improve firms stock returns, this should in the long run, translate into a higher firm valuation. As a measure of firm s value, Tobin's Q plays an important role in many financial interactions. Defined as the ratio of the market value of a firm to the replacement cost of its assets, it has been employed in a number of governance studies. Following Gompers et al. (2003), Bebchuck et al. (2008), Black et al. (2006a,b), we use Tobin s Q as the measure of firm value. We define our Tobin s Q as in Chung and Pruitt (1994), the approximate Q is simply defined as follows: Approximate Q = (MVE + PS + DEBT) / TA where MVE is the product of a firm's share price and the number of common stock shares outstanding, PS is the liquidating value of the firm's outstanding preferred stock, DEBT is the value of the firm's short term liabilities net of its short term assets, 18

19 plus the book value of the firm's long term debt, and TA is the book value of the total assets of the firm. The corresponding regression results are reported in Table 7. Table 7 Firm Valuations Tobin's Q (1) (2) (3) (4) (5) (6) (7) CGQ *** *** *** *** *** *** *** (8.47) (7.96) (6.81) (7.75) (8.71) (5.76) (6.12) Size *** ** *** ** (-2.66) (2.50) (-0.63) (-4.71) (-2.01) Sales Growth *** *** *** * ** (5.85) (6.98) (7.13) (1.71) (2.14) R&D/Sales *** *** *** (4.70) (13.25) (5.95) Intang * ** (-1.85) (-1.34) (2.36) ROA *** *** (31.93) (31.40) NPM ** (2.16) (-0.70) Industry Dummy No 4 digit No 4 digit No No 4 digit Adjusted R Sample Size This table shows results of pooled OLS estimation of the determinants of firm-level market valuation and governance. The dependent variable is Tobin s Q, which is defined as market value of equity plus total liabilities divided by Total Assets. CGQ is the governance indicator. Size is the natural log of Total Assets. Sales Growth is the annual average growth rate of sales. R&D/Sales is the ratio of R&D expenditure and Total Sales. Intang is the ratio of Property, Plant and Equipment and Total Sales. ROA is the Return on Assets. NPM is the Net Profit Margins. The definition of these two variables can be found in section 3. Firm-level data is from T-values are shown in parentheses. *, **, and *** indicate significance level at 10%, 5% and 1% respectively. We use a pooled OLS regression. We regress Tobin s Q against CGQ, control 19

20 variables and industry dummies. We progressively add additional control variables in regressions (1-7). The adjusted R squares are , , , , , , and respectively. CGQ is highly significant in each of the regressions. Column 1 is a simple regression of Tobin s Q against CGQ. It documents a significant positive relationship with the coefficient equals to In column 3, with the inclusion of control variables, we can see that the coefficient of CGQ decreases a little to , significantly at 1% level. In column 4, keeping everything else equal, by adding the 4-digit SICS industry dummies, the relationship between CGQ and Tobin s Q becomes stronger (the coefficient increases to ). If we take regression 7 as our final regression 9, CGQ is positively associated with Tobin s Q with a 0.26% increase, and the magnitude of this effect is large, as one standard deviation change in governance results in about a 15% increase in the value of Tobin s Q. A positive coefficient of Sales Growth indicates that firms with positive Sales Growth have higher Tobin s Q. The relationship of Intang and Tobin s Q remains negative without the inclusion of industry dummies, indicating that firms with higher proportion of intangible assets have higher Tobin s Q. Robustness check Here, we conduct two robustness checks for our results. First, following Gompers et al. (2003), La Porta et al. (2002), Bebchuck et al. (2008), and others, we employ industry adjusted Tobin s Q, which is defined as Tobin s Q minus the median Q of the corresponding industry. Accordingly, we exclude the industry dummies from the regression. The relationship between firm value and governance stays unchanged. Second, we further carry out the robustness check by running annual regressions. The relation stays valid and significant, yet its intensity varies quite a lot from one year to another. In general, the impact of CGQ on Tobin s Q is getting stronger with an 9 Columns 5 and 6 are not commented here since they are just two steps which allow to arrive at column 7. 20

21 exception in both 2005 and Results are shown in Table 8. Table 8 Robustness Check Industry adjustedq Tobin's Q CGQ *** *** *** ** ** *** *** (4.91) (3.62) (4.16) (2.55) (2.52) (4.32) (5.83) Size *** *** *** ** *** (-3.54) (-3.70) (-0.28) (-4.15) (0.39) (2.05) (5.68) Sales Growth ** * *** ** *** (1.96) (1.79) (3.45) (2.43) (0.96) (2.76) (1.23) R&D /Sales *** *** *** *** *** *** ** (8.83) (3.98) (4.74) (2.66) (2.69) (2.94) (-2.52) Intang *** ** ** *** ** *** (-1.42) (1.35) (2.18) (1.97) (2.58) (2.45) (2.66) ROA *** *** *** *** *** *** *** (31.41) (6.88) (10.42) (13.88) (13.94) (14.93) (12.01) NPM ** * (0.62) (2.22) (-1.18) (-1.41) (1.36) (1.88) (-1.15) Industry Dummy No 4-digit 4-digit 4-digit 4-digit 4-digit 4-digit Adjusted R Sample Size This table shows results of cross section regression by year. The first column is the result of the robustness check using Industry adjusted Tobin s Q, which is defined as Tobin s Q minus the median Q of the corresponding industry. In all the rest of the table, the dependent variable is Tobin s Q which is defined as market value of equity plus total liabilities divided by Total Assets. CGQ is the governance indicator. Size is the natural log of Total Assets. Sales Growth is the annual average growth rate of sales. R&D/Sales is the ratio of R&D expenditure and Total Sales. Intang is the ratio of Property, Plant and 21

22 Equipment and Total Sales. ROA is the Return on Assets. NPM is the Net Profit Margins. The definition of these two variables can be found in section 3. Firm-level data is from T-values are shown in parentheses. *, **, and *** indicate significance level at 10%, 5% and 1% respectively Governance and Operating performances We explore the relationship between firm s operational performance and firm s governance. In order to conduct the analysis, we use ROA and NPM as two performance measures. The results of the regressions are reported in Table 9. In regression 1-3, we regress ROA on CGQ and adding control variables progressively, which are Size, Sales Growth, R&D/Sales, and Intang. In regression 4 and 5, our dependent variable is NPM, and independent variable is CGQ, as well as two control variables, Size and Market to Book Value. The results show a significant positive relationship for both measures. One standard deviation change in CGQ is associated with a 4.9% increase in ROA. The coefficient is significant at 1% level. Firms with weaker corporate governance are less profitable. This relationship becomes stronger by adding control variables as well as the four-digit SIC industry dummies. The relationship of NPM and CGQ is also positive and significant at (only) 10% level. Table 9 Operating Performances ROA NPM (1) (2) (3) (4) (5) CGQ *** *** *** *** * (2.61) (4.85) (6.41) (6.88) (1.60) Size *** *** *** (6.92) (8.77) (-6.29) Sales Growth *** *** (7.89) (9.69) R&D/Sales *** 22

23 (-17.65) Intang (-0.70) LnMTBV *** (24.34) Industry dummy No No 4-digit No 4-digit Adjusted R Sample Size This table shows results of pooled OLS estimation of the determinants of firm-level operating performance and governance. The dependent variable is ROA on the left part of the table and NPM on the right part of the table (Here, the NPM is in its logarithm form). CGQ is the governance indicator. Size is the natural log of Total Assets. Sales Growth is the annual average growth rate of sales. R&D/Sales is the ratio of R&D expenditure and Total Sales. Intang is the ratio of Property, Plant and Equipment and Total Sales. LnMTBV is the natural log of market to book value defined as market value of equity divided by the book value of equity. Firm-level data is from T-values are showed in parentheses. *, **, and *** indicate significance level at 10%, 5% and 1% respectively Endogeneity test As already stated earlier, an important issue in this kind of analysis is endogeneity, since firms with higher market values could simply be more likely to choose better governance structures. Argued by Black et al. (2006a,b), there is already evidence of endogeneity in other corporate governance studies 10. The analysis reported in section 4.3 is based on the pooled ordinary least square regressions. In doing that, it is assumed that corporate governance affects corporate performance. To mitigate the problem of endogeneity, one can either use an extensive set of control variables for the omitted variable problems, as we did in our study. Moreover, the analysis can be extended by using two-stage least square regression (hereafter 2SLS), or using Durbin-Wu-Watson endogeneity test. To carry out the tests, additional variables 10 See, for instance, Hermalin and Weisbach (1998), Durnev and Kim (2005), Himmelberg et al. (1999, 2001), Bhagat and Black (2002), Gillan et al. (2003). 23

24 known as instrumental variables are needed. An ideal instrument should not have direct association with the dependent variables, and is intended to be correlated with the endogenous variables but not with the error terms. In our case, an instrumental variable is needed for the possible endogenous variable, CGQ. It has to be exogenous and not influenced by the dependent variable Tobin s Q, also it must be correlated with CGQ. In previous studies, variables lagged values are used as instrumental variables. Our choice of instrumental variable follows previous studies on corporate governance, the lagged value of CGQ. The lagged variable is chosen because the research data consists of a set of observations made at different points in time on large number of firms. Therefore there is tendency for the data to be correlated across observations but there is less likelihood that the earlier values of the variables are directly causing current values of the dependent variable. Here, we find the lag CGQ is marginally correlated with Q (0.0725) and strongly correlated with CGQ (0.9129). Two-Stage Least Square Regression There are two ways of running the Two-Stage Least Square regression. The first is to use two steps of ordinary least squares. This way includes running OLS twice for each endogenous variable. In our case, the first stage, CGQ is regressed against instrumental variable plus all other control variables. The second stage is estimated using the predicted value of CGQ from the first stage. The other way is to use directly the 2SLS method in STATA. Comparing the results with those reported earlier, there is a similar pattern of coefficients for the variables, the positive relationship between Tobin s Q and CGQ remains the same and significant at 10% level. The coefficient is (t-value is 1.85). When we replace Tobin s Q with natural log of Q, this relationship remains the same. Durbin-Watson Endogeneity Test We further verify our choice of instrumental variable using Durbin-Watson 24

25 endogeneity test. There are two steps in carrying out this test. In our case, in the first step, we regress CGQ on our instrumental variable and other control variables. In the second step, we regress Tobin s Q on CGQ, control variables and the first-stage residual term. A significant coefficient on the first-stage residual is evidence of endogeneity. The second-stage coefficient on instrumented-cgq is 0.38 and significant at 10% level (t-value is 1.85). The coefficient on the first stage residual is negative ( ) and insignificant with a t-value of Conclusions In this paper we addressed the question whether good overall corporate governance has a positive impact on firm value and performance. We investigated the link between corporate governance and firm value and performance by using a large sample database, RiskMetrics / Institutional Shareholder Services, and the Corporate Governance Quotient. Our sample covers 2662 firms from 24 countries within 25 different industries. We report several important findings in our study. 1. Firms with better governance have higher performance in the stock market. We report a 1% change in governance indicator can result in 0.19% change in Stock Return, and 1.20% changes in Dividend Yield. 2. Our result supports the hypothesis of a positive relationship between firm-level corporate governance and Tobin s Q. Specifically, one standard deviation change in CGQ results in about a 15% increase in the value of Tobin s Q. 3. We further find a positive relationship of corporate governance and firm s operating performance measure by Return on Assets. We find that one standard deviation change in CGQ can result in up to 4.9% increases in ROA, and 5.65% increase in NPM. 25

26 These results globally confirm former ones obtained in the literature, but using a more complete firm level data in terms of corporate governance components and country coverage. Especially, it adds to the result obtained in Gompers et al. (2003) in that it does not consider only external mechanisms of governance, but rather includes internal mechanisms as well. It also adds to Bebchuk et al. (2008), Black et al. (2006a,b), Drobetz et al. (2004), and Beiner et al. (2006), since CGQ is calculated for a large sample of international firms and on the basis of a large range of provisions. Finally, compared to Klapper and Love (2004), it is based on a 6 years study evaluating changes in the corporate governance best practice of firms in a more objective and complete way. It should naturally follow from our paper that in terms of policy implication, the standard of corporate governance is to be largely diffused. However, to promote such a conclusion, some further work still need to be done. We already noticed that changes in the standard deviation of CGQ produces important changes in Tobin s Q, NPM and ROA. Moreover, it appears from our regression results and robustness check (Table 8) that from 2005 to 2008, the influence of CGQ on Tobin s Q is becoming more and more important. This may suggest that corporate governance could stimulate value and performance of firms, while in the meantime rendering this value and performance more dependent on CGQ ups and downs. It may thus involve a greater sensitivity and potentially increased volatility of value and performances over time, produced by the adoption of the corporate governance standard. In order to test this assumption, an empirical investigation on the possible relationships between standard deviations of the different variables studied here has now to be carried out. This is the natural step that will structure our future research agenda. References Bebchuk, L., and Hamdani, A., The Elusive Quest for Global Governance Standards. University of Pennsylvania Law Review, 157,

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