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Aecounting and Business Research. Vol. 39. No, 5, pp. 497-513, 2009 497

On the relatíon between corporate governance compliance and operating performance Heidi Vander Bauwhede

Abstract — Better corporate perfonnance has been cited as one of the main benefits of adopting good corporate govemance structures within organisations. However, in contrast to theory, a prior European study (Bauer et al., 2004) reports evidence of a negative relationship between corporate govemance and corporate performance. This study re-examines this relationship, and reports evidence of a positive relationship between the extent of compliance with intemational best practices concerning board structure and functioning and operating perfonnance when operating perfonnance is measured by the retum on assets (ROA). This resuh is robust to controlling for the firms’ compliance with best practices in other govemance areas, and holds for some other govemance dimensions, namely disclosure of corporate govemance and the range of takeover defences. Further tests indicate that greater compliance with intemational best practices conceming board stmcture and functioning is significantly associated with reporting less income from asset disposals and that studying a performance measure that includes this item obscures the inherently positive relationship between operating perfonnance and the extent of compliance with intemational best practices regarding board stmcture and functioning. The results provide some support for an often- cited motivation for the adoption of good govemance practices, and provide explicit evidence that the measure of operating perfonnance is cmcial in examining firm-level operating performance.

Keywords: corporate govemance; operating performance

1. Introduction This paper examines the relationship between corporate govemance compliance and operating performance for a set of large listed European companies. My focus is on compliance with intemational best practice in corporate govemance. Following Jensen (1993) and prior govemance research, I hypothesise that greater compliance with intemational corporate govemance best practices and, more specifically, best practices conceming the structure and functioning of the board, is associated with better operating performance, ceteris paribus.

I investigate the relationship between corporate govemance compliance and operating performance for a sample of European companies in 2000-2001, because, during that period, there remained consid- erable variation in corporate govemance practices

(see Wójcik, 2006; Bauer et al , 2008), notwith- standing that there were pressures from, for example, institutional investors or cross-listings to comply with intemational corporate govemance best practices and that in some countries local codes were, de facto, mandatory.”‘^

The study focuses on operating performance, and not stock market performance, in order to investi- gate fiirther the result of a prior European study (Bauer et al., 2004) on the relation between compliance with best practices conceming corpor- ate govemance and operating performance which seems to conflict with both theory as well as prior American results. More specifically, Bauer et al. (2004) report evidence of a negative relationship between ratings on the extent of compliance with intemational best practices and firm operating

The author is at Maastricht University and at Ghent University. She also has an affiliation to Katholieke Universiteit Leuven. She gratefiilly acknowledges Ping-Sheng Koh, Kevin McMeeking, Piet Sercu, Konstantinos Stathopoulos, participants at the 2006 European Accounting Association Annual Conference (Dublin, Ireland), the editor and two anonymous reviewers for usefijl comments. She also thanks Deminor for providing the govemance data. The usual disclaimer applies.

Correspondence should be addressed to Dr Heidi Vander Bauwhede, Maastricht University, Department of Accounting & Information Management, P.O. Box 616, Maastricht, 6200 MD, Netherlands. E-mail: H.VanderBauwhede@maastrichtuniversity.nl.

This paper was accepted for publication in July 2009.

‘ I refer to a study commissioned by the European commis- sion (Weil et al., 2002) and to the website of the European Corporate Govemance Institute (http://www.ecgi.org/codes/ all codes.php) for an overview of the corporate govemance codes in the European Union. Intemational govemance codes are, for example, those established by the Intemational Corporate Govemance Network (ICGN), and the Organisation for Economic Co-operation and Development (OECD).

^Some countries (such as the UK and Italy) required companies to disclose whether they complied with a (national) corporate govemance code under a ‘comply or explain’ approach. This approach requires firms to disclose whether (and to what extent) they comply with a particular corporate govemance code and, if they do not (fully) comply, to explain why they do not comply.

498 ACCOUNTING AND BUSINESS RESEARCH

performance, whereas theory (Jensen, 1993), pre- dicts a positive relationship^ and a prior American study (Larcker et al., 2005) finds some (albeit weak) evidence of a positive relationship. I primarily focus on board structure and functioning, and not on other dimensions of corporate governance (such as, for example, rights and duties of shareholders and range of takeover defences), because it is especially the structure and functioning of the board that can directly affect the operating efficiency and operat- ing performance of a company. However, for completeness, I also perform and report the results of some additional analyses on the relation between other dimensions of corporate governance and firm operating performance.

I use a sample of European listed companies for which a private rating agency issues a firm-level rating of the extent of compliance with inter- national best practices conceming board structure and functioning. Results of univariate and multi- variate tests indicate that the one-year ahead retum on assets (ROA) increases in the extent of compliance with intemational best practices con- ceming board structure and functioning. Tests show that the results are not affected by the potential endogeneity of the extent of govemance compliance. In addition, the results are robust to controlling for the firms’ compliance with best practices in other govemance areas, such as rights and duties of shareholders and-range of takeover defences, and to controlling for country-level performance. Moreover, I also find a positive relation between the extent of compliance with recommendations in some other govemance dimensions, more specifically disclosure on cor- porate govemance and range of takeover defences, and firm operating performance.

Further, additional analyses indicate that greater compliance with intemational best practices con- ceming board stmcture and fiinctioning is signifi- cantly associated with reporting less income from asset disposals and that studying a performance measure that includes the income fi^om asset disposals, such as the retum on equity (ROE) or net profit margin (NPM) used by Bauer et al. (2004), instead of a performance measure which is not impacted by the income fi^om asset disposals, such as the retum on assets (ROA), obscures the inherently positive relationship between operating performance and the extent of compliance with

^ Bauer et al. (2004) find indications of a positive relationship between govemance ratings, and stock retums and firm value, respectively.

intemational best practices regarding board struc- ture and functioning.

This study contributes to the literature on the relation between corporate govemance and corpor- ate performance. A first contribution is that the study reports a positive relation between the extent of compliance with intemational best practices on various govemance dimensions (board stmcture and functioning, disclosure on corporate govem- ance) and the operating performance of European companies. A second contribution is that this study reports evidence which indicates that the unex- pected negative relationship between corporate govemance compliance and operating performance as reported by Bauer et al. (2004)̂ * is due to poorly- govemed companies using the available discretion over the timing of asset sales to cover up their inherently lower operating performance. The key difference between this study and that of Bauer et al. (2004) is that the retum on assets is introduced as the preferred measure of operating performance because the income measure used in computing the retum on assets, i.e. operating income, is less influenced by discretionary items than the income measure used to compute the retum on equity or net profit margin, i.e. income before extraordinary items. The retum on equity and net profit margin are the performance measures used by Bauer et al. (2004).

The remainder of the paper is organised as follows. The next section develops the main research hypothesis. Section 3 describes the sample and data. Section 4 presents the empirical model. Section 5 presents the empirical results. Section 6 concludes.

2. Hypothesis development The various corporate govemance codes that have been issued since the late 1990s oflen refer to better performance as one of the key benefits of adopting their corporate govemance recommendations. This performance can be understood as better market performance (i.e. higher stock retums or firm

Examples of other studies that have examined the relation between govemance and perfomiance using samples from other countries (for example, the US, Australia, and various Asian and some (individual) European countries), and using and focusing on a variety of govemance attributes and performance measures, are: Larcker et al. (2006), Black et al. (2006), Brown and Caylor (2006a), Brown and Caylor (2006b), Dumev and Kim (2005), Larcker et al. (2005), Alves and Mendes (2004), Bebchuk et al. (2004), Klapper and Love (2004), Drobetz et al. (2004), Kiel and Nicholson (2003), Bhagat and Black (2002), Yermack (1996), and Klein (1998).

Vol. 39, No. 5. 2009 499

value)^ or as better operating performance. The expected relationship between compliance with corporate govemance recommendations and oper- ating performance is based on the argument that firms with a better govemance structure operate more efficiently which increases their operating performance (see, for example, Jensen, 1993). However, results of previous studies on the relation between govemance and operating performance are mixed. Larckeret al. (2005), for example, find some evidence of a positive relationship between an overall govemance metric (The Corporate Library Board Effectiveness Rating) and the one-year ahead ROA for a set of large listed American companies. By contrast, Bauer et al. (2004) find a negative relationship between an overall govemance score and operating performance for large European companies.

As with any govemance study, a crucial element in examining the relationship between govemance and performance is how one defines and measures ‘better govemance’. In this study, I use a rating, issued by a private rating agency (Deminor rating),^ that assesses the extent to which large listed European firms comply with intemational best practices conceming corporate govemance and, more specifically, the extent to which firms comply with intemational best practices conceming board structure and functioning.^ Higher compliance is implicitly assumed to be better govemance. However, this is not necessarily true. A first reason is that European companies may have adopted govemance mechanisms and practices that differ from the intemationally accepted best practices, but are better tailored to the specific context in which they operate. However, it is probably also true that

^ Examples of studies that have examined aspects of corpor- ate govemance and market performance in an American setting are Yemack (1996), Bhagat and Black (2002), Gompers et al. (2003) and Bebchuk et al. (2004). Beiner et al. (2006), Alves and Mendes (2004), Drobetz et al. (2004) and Kiel and Nicholson (2003) are examples of govemance-market perform- ance studies using samples of Swiss, Portuguese, German and Australian companies, respectively.

* In Section 3,1 provide more detail on the rating. ‘Most govemance studies use either a single indicator of

govemance, or an ‘arbitrary’ index. Larcker et al. (2006) argue that measurement error in these govemance metrics may be partly responsible for the mixed results on the association between tiie typical measures of corporate govemance and accounting and economic outcomes. Nevertheless, I prefer to use the ratings issued by an independent rating agency as measures of govemance compliance since these are publicly available and easily accessible for market participants. The aim of the study is to see whether these publicly available measures of the extent of compliance with intemational best practices are related to fiiture operating performance and can as such signal future operating performance to market participants, who can, in tum, use this infonnation for decision making.

there is less need for govemanee practices tailored to local contexts for the largest companies in Europe, which operate globally instead of locally. Whether large listed European companies benefit fi-om compliance with intemational best practices, and then specifically in terms of higher operating performance, is ultimately an empirical question. Another reason why higher compliance is not necessarily better govemance is that the best practices identified by Deminor are not always unequivocally related to better govemance. For example, evidence on whether CEO duality is bad govemance and board diversity is good govemance, is mixed (see, for example, Sonnenfeld, 2004; Massa and Simonov, 2007).* In order to refine the analysis I focus on the dimension of corporate govemance which is particularly likely to directly infiuence operating efficiency and operating per- formance, i.e. the structure and functioning of the board of directors.^ As Jensen (1993: 862-863) puts it, ‘The board, as the apex of the intemal control system, has the final responsibility for the function- ing of the firm. Most importantly, it sets the rules of the game for the CEO. The job of the board is to hire, fire, and compensate the CEO, and to provide high-level counsel’ and ‘ . . . the very purpose of the intemal control mechanism is to provide an early waming system to put the organisation back on track before difficulties reach a crisis stage.’ Jensen (1993) then also attributes the weak corporate performance from the early 1990s to problems with the intemal control activity (Jensen, 1993: 352) in the 1980s, which, in tum, stemmed from problems with the board of directors (Jensen, 1993: 862).

The major threat to a well-functioning board, and strong operating performance, is that the board is dominated by managers (especially in Anglo-Saxon countries) or majority shareholders (especially in continental European countries) who act in their ovra interest (instead of in the interest of all stakeholders), and cover up any underperformance by eamings management or manipulation to appease (minority) shareholders. Jensen (1993: 869) then also recognises that characteristics such as, for example, high-equity ownership by man- agers and board members, a small board, not many insiders on the board, and a CEO which is not the chairman of the board, are key elements of a well- functioning govemance system, which limits self- interested behaviour by managers, uncovers bad performance in time and takes the necessary actions

* I thank one of the anonymous reviewers for this observation. ‘ For completeness, I later expand the analyses to govemance

dimensions other than board structure and fiinctioning. The results are reported in Section 5.4.

500 ACCOUNTING AND BUSINESS RESEARCH

to ‘put the organisation back on track’ (Jensen, 1993: 863). These key elements of a well-function- ing board mentioned by Jensen (1993) are all covered by the intemational best practices concem- ing board structure and functioning. Therefore, I expect that higher compliance with intemational best practices conceming board structure and functioning is related to better operating perform- ance.

Although greater compliance with intemational best practices conceming rights and duties of shareholders and range of takeover defences may increase the pressure by investors and the market for corporate control on companies to perform well, it is less straightforward that this greater compliance with intemational best practices conceming rights and duties of shareholders and range of takeover defences is per se related to better underlying operating performance, for in the absence of a well- functioning board, managers and majority share- holders could still act in their own self-interest, underperform, and cover up weak performance by eamings management or manipulation.’””’ This leads to the following hypothesis: HI: A company’s operating performance increases

in the extent of compliance with intemational best practices conceming board stmcture and functioning, ceteris paribus.

3. Sample and data This study uses ratings of compliance with inter- national best practices regarding board stmcture and functioning which are supplied by a private rating agency, Deminor Rating. Deminor Rating (a sub- sidiary of Deminor Intemational) releases, since March 2001, corporate govemance ratings on the companies of the FTSE Eurotop 300 index.’^”^ The ratings are based on over 300 corporate govemance indicators, which were identified after consulting

‘”De Angelo (1988), for example, reports that, during an election campaign, managers exercise accounting discretion to portray a favourable eamings picture to voters.

As concems disclosure on corporate govemance, it is straightforward that mere disclosure per se cannot improve the operating performance of a company. However, the level of disclosure is highly positively correlated with the quality of the structure and the fiinctioning of the board: companies with well- structured and -functioning boards have no problem in disclos- ing this information, while companies with badly-structured and -functioning boards are less transparent about this. A positive association between high disclosure and good operating performance is then probably also due to a well-structured and well-functioning board than to the level of disclosure per se.

‘^On 25 May 2005, Deminor announced that it had sold its corporate govemance unit Deminor Rating to Institutional Shareholder Services (ISS).

‘^ Some other studies that have used Deminor data are Bauer et al. (2008), Bauer et al. (2006), Wójcik (2006), Wójcik et al. (2005), and Bauer et al. (2004).

institutional investors. The indicators can be div- ided into four categories: rights and duties of shareholders, range of takeover defences, disclosure on corporate govemance and board stmcture and functioning. Deminor Rating issues a rating of each one of the four categories. This study focuses on the rating regarding board stmcture and functioning. This rating covers indicators on the election of members of the company’s bodies, composition of the board, functioning of the board, remuneration of the company’s bodies and committees of the board.

Ratings are assigned by senior analysts from the different European offices of Deminor after all the most recent publicly available information on a particular company (i.e. not only financial reports, but also articles of association, agendas, resolutions and minutes of ordinary and extra-ordinary general meetings, investor’s handbooks and newsletters, intemet-sites and all other publicly available infor- mation) has been benchmarked against the best practice found in intemationally accepted stand- ards. Those intemationally accepted standards are established by, for example, the Intemational Corporate Govemance Network (ICGN) and the Organisation for Economic Co-operation and Development (OECD). A rating is measured on a scale of 5 to 1, with 5 representing the best practice (Deminor Rating, 2001: 9-10).

The sample studied in this paper consists of all companies from the FTSE Eurotop 300 for which there is a Deminor rating of board structure and functioning for the year 2000 and/ or 2001, as well as complete infonnation on the other variables in the model.’”* I exclude financial companies (FTSE industry sector code 80) because their financial stmcture is distinct from other companies and they are often subject to special mies and recommenda- tions. I delete observations with extreme observa- tions (i.e. values outside the 5* and 95* percentile) for the ratios in the model, namely leverage and the three measures of operating performance (i.e. ROA, ROE and NPM), for ratios easily take on extreme values. The final sample exists of 201 firm-year observations (from 118 different companies). Table 1, Panels A and B give a breakdown of the observations by industry sector and by country, respectively.

I obtain financial statement data from Worldscope.

‘ ‘ ‘The item that is most frequently missing is the Deminor govemance rating. This rating is missing because not all FTSE Eurotop 300 firms are followed by Deminor.

Vol. 39, No. 5. 2009 501

Table 1 Sample description Panel A: Breakdown of sample by industry*

Industry code

4 7 11 13 15 21 24 25 26 31 34 41 43 44 47 48 49 52 53 54 58 59 63 67 72 73 78 93 97

Industry description

Mining Oil & Gas Chemicals Construction & Building Materials Forestry & Paper Aerospace Diversified Industrials Electronic & Equipment Engineering and Machinery Automobiles Household Goods & Textiles Beverages Food Producers & Processors Health

Number of firms % Number of firm-years

Personal Care & Household Products Pharmaceuticals Tobacco General Retailers Leisure, Entertainment & Hotels Media & Photography Support Services Transport Food & Dñig Retailers Telecommunication Services Electricity Gas Distribution Water Information Technology Hardware Software & Computer Services Total

* Following the FTSE Global Classification System.

Panel B: Breakdown of sample by country”*

Country

Belgium France Italy

2 6 9 6 1 3 3 7 7 8 4 2 4 1 2 4 2 7 2 9 3 1 4 6 8 2 1 2 2

118

Number of firms % Number of firm-years

3 2.54 25 21.19 6 5.08

The Netherlands 8 6.78 Portugal Spain Switzerland Germany Denmark Norway Sweden Finland Ireland UK Total

1 0.85 7 5.93 7 5.93

12 10.17 2 1.69 1 0.85 8 6.78 1 0.85 1 0.85

36 30.51 tl8 100

** All but two countries in the sample (Switzerland other countries and Monetary

, but the UK, Denmark and Sweden Union).

6 49 10 13

1 13 13 21

3 2

12 2 2

54 201

and Norway) are part of the

1.69 5.08 7.63 5.08 0.85 2.54 2.54 5.93 5.93 6.78 3.39 1.69 3.39 0.85 1.69 3.39 1.69 5.93 1.69 7.63 2.54 0.85 3.39 5.08 6.78 1.69 0.85 1.69 1.69 100

2.99 24.38 4.98 6.47 0.50 6.47 6.47

10.45 1.49 1.00 5.97 1.00 1.00

26.87 100

are member of the Eurozone or EMU

3 10 15 11 2 5 4

12 12 16 8 4 7 1 3 8 4

11 3

15 5 1 8 8

14 4 1 3 3

201

1.49 4.98 7.46 5.47 1.00 2.49 1.99 5.97 5.97 7.96 3.98 1.99 3.48 0.50 1.49 3.98 1.99 5.48 1.49 7.46 2.49 0.50 3.98 3.98 6.97 1.99 0.50 1.49 1.49 100

European Union. All (i.e. Europe’s European

502 ACCOUNTING AND BUSINESS RESEARCH

4. Research design and model specification I test the relationship between the extent of compliance with intemational best practices con- ceming corporate govemance, and more specific- ally board structure and functioning, and the operating performance of large listed European companies by estimating the following operating performance model:

Performancei, = ßo + iS|CG.COMPi,

where:

i, +

(1)

Performanceit = ROA, where: ROA is one-year ahead retum on assets for firm i in year t;

CGCOMPLit = a rating proxying for the extent of compliance with intemational best practices regarding board structure and functioning for firm i in year t;

= leverage, as measured by the sum of short-term and long-term debt divided by total assets, for firm i in year t;

= the natural logarithm of total assets for firm i in year t;’^”^

Y2001it = indicator variable which takes one if the observation is from 2001, and zero if the observation is from 2000;

Xjt = a vector of industry dummies, i.e. indicator variables for the (two- digit) industry codes of the FTSE Global Classification system.

I measure the dependent variable in the operating performance model, i.e. one-year ahead firm-level operating performance, by the one-year ahead ROA. I use the one-year ahead, instead of the contemporaneous, ROA to make sure that the govemance systems described by the ratings are in place and operational at the moment that I start measuring operating perfonnance. Consistent with prior studies (e.g. Larcker et al., 2006), ROA is measured as operating income divided by average total assets.’^ For comparison, I also perform

‘^ Total assets are measured in thousands of Euros. Values initially stated in a local currency are converted to Euros by using the exchange rate at the balance sheet date.

I use the natural logarithm because I do not expect a linear relationship between operating performance and firm size.

” T h e average is computed as the sum of the value at the beginning of the accounting period and the value at the end of the accounting period, divided by two.

analyses in which I replace the one-year ahead ROA with the one-year ahead ROE and the one-year ahead NPM, because the ROE and the NPM were used as performance measures in the study by Bauer et al. (2004). The ROE is measured as eamings before extraordinary items dividend by the average book value of stockholders’ equity, and net profit margin is the ratio of eamings before extraordinary items divided by sales (see, for example, Gompers et al., 2003). As argued by Core et al. (2006) and Barber and Lyon (1996), the ROA is clearly the preferred measure of operating performance because it is less affected by discretionary items than the ROE and the NPM. This implies that I expect a stronger relationship between the extent of compliance with intemational best practices con- ceming board stmcture and functioning and the one-year ahead ROA, than between the extent of compliance and the one-year ahead ROE or the one- year ahead NPM. I will further refer to the three models as the ROA model, the ROE model and the NPM model.

The test variable is a measure of the level of compliance with intemational best practices con- ceming corporate govemance, and more specific- ally best practices conceming board stmcture and fiinctioning (CG COMPL). CG COMPL is prox- ied by Deminor’s rating of board stmcture and functioning. The rating takes a value from 1 to 5 with 5 indicating the highest compliance with intemational best practice. A positive sign on CG_COMPL indicates that greater compliance with best practices conceming board structure and fimctioning is related to better operating perform- ance, and is consistent with the hypothesis. I further include in the regression leverage (LEV), computed as the sum of short-term and long-term debt over total assets, to control for the well-known impact of leverage on ROE, the natural logarithm of total assets (LNTA) as a measure of firm size, a year dummy (Y2001) to control for the impact of the general macro-economic context on individual firm performance, and a vector of industry dummies.

5. Descriptive statistics and results 5.1. Descriptive statistics Table 2, Panel A, presents descriptive statistics for the dependent and independent variables of the operating performance model. Table 2, Panel A, shows that the mean one-year ahead ROA is about 6.6% (median 6.4%). The mean one-year ahead ROE is higher, and about 7.3% (median 10.2%). The mean one-year ahead NPM amounts to 2.9% (median 3.7%). Mean and median leverage is about 28%.

Vol. 39, No. 5. 2009 503

Table 2 Descriptive statistics and correlations^ Panel A: Descriptive statistics

Variable

ROA ROE NPM LEV LNTA

Panel B:

201 201 201 201 201

Mean

0.0658 0.0729 0.0289 0.2773

16.5757

StdDev

0.0482 0.1507 0.0769 0.1135 1.0492

Min.

-0.0352 -0.5838 -0.4580

0.0470 13.7591

Pearson correlation coefficients

ROA ROE NPM CG COMPL LEV LNTA

ROA

1.0000 0.5095 0.5224 0.1823

-0.1993 -0.4028

ROE

0.8328 0.0271

-0.1724 -0.1337

NPM

0.0190 -0.1640 -0.2297

0.0314 0.0433 0.0110 0.1868

15.8908

Median Q3

0.0635 0.0946 0.1019 0.1588 0.0365 0.0684 0.2794 0.3642

16.3970 17.2708

CG COMPL LEV LNTA

Max.

0.1966 0.3015 0.1626 0.4955

19.1507

-0.0092 1.0000 -0.0273 0.2066 1.0000

* Variable definitions:

ROA = one-year ahead return on assets for firm i in year t, and is measured as operating income divided by average total assets,

ROE = one-year ahead retum on equity for firm i in year t, and is measured as eamings before extraordinary items divided by the average book value of stockholders’ equity,

NPM = one-year ahead net profit margin for firm i in year t, and is measured as eamings before extraordinary items divided by sales revenues

LEV = ratio of short-term debt plus long-term debt over total assets for firm i in year t LNTA = natural logarithm of total assets for firm i in year t CG_COMPL = score fi^om 1 to 5 with higher scores indicating greater compliance of firm i in year t

with intemational best practice conceming board stmcture and fiinctioning

Table 2, Panel B, presents the Pearson correlation coefficients between the dependent and independ- ent variables of the operating performance model. The dependent variables, one-year ahead ROA, one-year ahead ROE and one-year ahead NPM are all positively correlated with CG_CO]V[PL. However, only the correlation of ROA and CGCOMPL is significant. The highest absolute value of the correlations among the independent variables is 0.21, which indicates that the regression results are not affected by multicollinearity.

5.2. Regression results I estimate the performance model using ordinary least squares (OLS). A concem in testing the relation between the extent of compliance with intemational best practices conceming corporate govemance, and more specifically board stmcture and fiinctioning, and the operating performance of large listed European companies is that firms with

good prospects may self-select into the group with stronger govemance stmctures, while firms with poor prospects may self-select into the group with weaker govemance stmctures. If this is indeed tme, the OLS parameter estimates are inconsistent. However, the results of a Hausman-like test for endogeneity as described in Gujarati (2003: 713) show that CG_COMPL is not endogenous with respect to any of the dependent variables (p on the fitted value of CG_COMPL > 0.10, two-sided). For the endogeneity test, I used the following first stage model (govemance compliance model), which is based on prior empirical disclosure and govemance studies (see, for example, Pincus et al., 1989 and Willekens et al , 2004):

CG_COMPLi, = 70 + y,FFLOATi, +

(2)

504 ACCOUNTING AND BUSINESS RESEARCH

where: FFLOATit= the free float of firm i in year t; ROA_Cit = the contemporaneous retum on assets for firm i in year t; Yit = a vector of country dummies, i.e. indicator variables for the country of domicile of the firms in the sample; Z^ = a vector of other exogenous variables from the operating performance model (i.e. second stage regression). The other variables are as defined in Equation (1). Re-performing the endogeneity tests (1) deleting the contemporaneous retum on assets in the first stage regression, or (2) replacing the contemporan- eous retum on assets with the past retum on assets in the first stage regression confirm that CG_COMPL is not endogenous with respect to any of the dependent variables. This contrasts with results in Renders and Gaeremynck (2006), and is most likely due to differences in research design. More specif- ically, to be sure that the corporate govemance systems are in place and operational at the moment that I start measuring operating performance, I use one-year ahead operating perfomiance measures (instead of contemporaneous operating perform- ance measures).

As there are two years of data, there are repeated observations on some companies. Although obser- vations are still independent across firms, they are no longer independent within firms. Therefore, the t-values are adjusted to control for within-company dependence by using clustered robust standard errors.’*

Table 3 reports the results of the OLS regression analyses. Columns 3, 5, and 7 show the results of models that use the one-year ahead ROA, the one- year ahead ROE and the one-year ahead NPM as the dependent variable, respectively. Table 3 shows that the performance models have explanatory power (adjusted R^ of 49.30%, 23.41% and 22.11%, respectively). The coefficient on CG_COMPL is positive and significant at the 1% level (one-sided) in the ROA model. The magnitude of the CG_COMPL coefficient (0.0054) suggests a dif- ference of 2.16% in the realised one-year ahead ROA between firms with the lowest and the highest rating of CGCOMPL (i.e. 4*0.54%). This result supports the hypothesis that operating performance is higher for firms that comply to a greater extent with intemational best practices conceming board stmcture and functioning. Consistent with the argument that the one-year ahead ROA is the preferred measure of operating performance, the coefficient on CG_COMPL is not significant for the ROE and NPM models.

‘̂ The results are qualitatively similar when not adjusting for within company dependence.

Table 3 fiirther shows that the one-year ahead ROA and one-year ahead NPM decrease in size (LNTA). In addition, the industry dummies (not reported) are significant predictors of all three performance measures.’^

5.3. Additional analyses Other measures of operating performance To confirm the evidence from the ROA model on the positive and significant relation between the extent of compliance with intemational best prac- tices conceming board stmcture and fiinctioning and operating performance, I replace the one-year ahead ROA in the operating performance model with two altemative measures of operating per- formance, i.e. the one-year ahead retum on cash- adjusted assets and the one-year ahead retum on sales (ROS) (see Barber and Lyon, 1996). The retum on cash-adjusted assets is measured by dividing operating income by the average cash- adjusted assets, i.e. total assets minus cash and cash equivalents. The ROS is operating income divided by sales. Table 4 reports the results of the operating performance regressions when using these altema- tive operating performance measures. Table 4 also reports the results of the regression when using the one-year ahead ROA as the dependent variable for comparison. Table 4 shows that the results on the test variable (CG COMPL) when using the alter- native operating performance measures are qualita- tively similar to the result when using the one-year ahead ROA.

Examining the difference in results between performance measures The results in Tables 3 and 4 report a significantly positive relationship between the extent of compli- ance with intemational best practices conceming board stmcture and fiinctioning (CG_COMPL) and performance for some performance measures (i.e. the one-year ahead ROA, the one-year ahead retum on cash-adjusted assets and the one-year ahead ROS, all measures which use operating income in the numerator), but not for other performance measures (i.e. the one-year ahead ROE) and one-year ahead NPM, two measures which use income before exfraordinary items in the numerator). Especially the difference in results when using the ROS and the NPM is striking, since the only difference between these two measures is the numerator. (The ROS uses operating income

” Deleting the industry dummies from industries with only one observation (i.e. health, transport, and water) or all industry dummies does not change the results on the test variable.

Vol. 39, No. 5. 2009 505

Table 3 Regression

Variable

results

Pred. sign

ROA

Coef. estimate (t-statistic)

Pred. sign

ROE

Coef. estimate (t-statistic)

Pred. sign

NPM

Coef. estimate (t-statistic)

Intercept

CG COMPL

LEV

LNTA

Y2001

Industry dummies

Adj. R-squared N Evidence of endogeneity

0.4252*** (7.14) 0.0054***

(2.38) -0.0291

(-0.90) -0.0197***

(-5.33) -0.0060*

(-1.82) Included

49.30% 201 No

0.4511* (1.70) -0.0034

(-0.39) -0.1930

(-1.32) -0.0144

(-0.88) -0.0258

(-1.59) Included

23.41% 201 No

regression model:

[TAj,-1-/Î4 72001 ¡,

+ ß5

0.4142*** (2.87) -0.0023

(-0.61) -0.0702

(-1.2) -0.0179**

(-2.04) -0.0106

(-1.10) Included

22.11% 201 No

¡̂ it + Si,

” This table reports the results of the OLS estimation of the following regression model:

Perfotroanceu = ßo+ ^iCG_COMPL¡, -I- ftLEVj, +

Where: PerfonTiance;, = ROA, ROE or NPM. ROA = one-year ahead retum on assets for firm i in year t, and is measured as operating income divided by average total assets; ROE = one-year ahead retum on equity for firm i in year t, and is measured as eamings before extraordinary items divided by the average book value of stockholders’ equity; NPM = one-year ahead net profit margin for firm i in year t, and is measured as eamings before extraordinary items divided by sales revenues; CG_COMPL¡, = score fi-om 1 to 5 with higher scores indicating greater compliance of firm i in year t with intemational best practice conceming board stmcture and fiinctioning; LEV¡, = ratio of short-term debt plus long-term debt over total assets for firm i in year t; LNTAj, = natural logarithm of total assets for firm i in year t; Y2001 ¡t = year dummy, =1 when an observation is fi’om 2001, zero otherwise; X¡t = a vector of industry dummies based on the FTSE Global Classification System two-digit code for the industry sector.

*,** and *** denote statistical significance at the 10%, 5% and 1% level respectively and is based on a one- tailed test if the sign of the coefficient is in the predicted direction, and is based on a two-tailed test otherwise. T-values are adjusted for within-company dependence by using clustered robust standard errors. Results on the two-digit industry dummies are not reported for parsimony.

whereas the NPM uses eamings before extraordin- ary items in the numerator. Both measures have sales revenues in the denominator.) This suggests that something that causes the difference between operating income and eamings before extraordinary items can explain why there is a significant relationship between performance and the extent of compliance with intemational best practices conceming board structure and functioning when using some performance measures, but not when using other performance measures. Some of the difference between operating income and eamings before extraordinary items is in interest payment and taxes. Moreover, given the Worldscope data definitions of operating income and eamings before

extraordinary items, some of the difference between the two income measures stems fi’om allocations to and/or fi-om reserves, irom minority interests, from equity in eamings,̂ *^ and from other non-operating income and expenses. These other non-operating income and expenses include items such as: non- operating interest income, non-operating dividend income, and the gain/ loss on disposal of assets, i.e. the income from asset disposals.

To further explore what causes the difference in the relationship between corporate govemance

^^ This represents the ‘pretax portion of the eamings or losses of a subsidiary whose financial accounts are not consolidated with the controlling company’s accounts’ (see Thomson Financial, 2003).

506 ACCOUNTING AND BUSINESS RESEARCH

Table 4 Regression results using alternative operating performance measures”

ROA Retum on

cash-adj. assets Return on sales

Variable Pred. sign Coef. estimate Pred. sign Coef. estimate Pred. sign Coef. estimate (t-statistic) (t-statistic) (t-statistic)

Intercept

CG_COMPL

LEV

LNTA

Y2001

Industry dummies

Adj. R-squared N

0.4252*** (7.14) 0.0054***

(2.38) -0.0291

(-0.90)

-0.0197*** (-5.33) -0.0060*

(-1.82) Included

49.30% 201

0.4722*** (7.11) 0.0050**

(2.02) -0.0399

(-1.15)

0.0220*** (-5.42) -0.0056

(-1.57) Included

50.05% 201

0.4829*** (4.55) 0.0062**

(2.09) 0.0901*

(1.93)

-0.0212*** (-3.57) -0.0048

(-1.09) Included

47.90% 201

This table reports the results of the OLS estimation of the following regression model:

Performancei, = î o + ;9iCG_C0MPLi, + + + Where: Performance;, = ROA, Retum on cash-adjusted assets or Retum on sales. ROA = one-year ahead retum on assets for firm i in year t, and is measured as operating income divided by average total assets; Retum on cash-adjusted assets = one-year ahead retum on cash-adjusted assets for firm i in year t, and is measured as operating income divided by average (total assets minus cash and cash equivalents); Retum on sales = one-year ahead retum on sales for firm i in year t, and is measured as operating income divided by sales revenues; CGCOMPLit = score from 1 to 5 with higher scores indicating greater compliance of firm i in year t with intemational best practice conceming board structure and functioning; LEVi, = ratio of short- term debt plus long-term debt over total assets for firm i in year t; LNTAj, = natural logarithm of total assets for firm i in year t; Y2001i, = year dummy, =1 when an observation is fi-om 2001, zero otherwise; X;, = a vector of industry dummies based on the FTSE Global Classification System two-digit code for the industry sector.

compliance (CG_COMPL) and performance when using the NPM instead of the ROS as the measure of performance, I compute the pairwise correlations between each one of the identified items which make up the difference between operating income and eamings before extraordinary income (scaled by sales) and the measure of corporate govemance compliance (CGCOMPL).^’ I fiirther adjust oper- ating income for each one of the items at a time and regress each one of the new income measures

^’ As the performance measures used in the primary analyses, these items and the newly computed perfonnance measures are on a one-year ahead basis.

(scaled by sales) on the measure of corporate govemance compliance (CGCOMPL) and the control variables, i.e. I replace the dependent variable in the performance model with a new performance meastire.

The results of these detailed analyses show that income fi-om asset disposals^^ (scaled by sales) is significantly negatively related to the extent of corporate govemance compliance (CGCOMPL) (correlation coefficient = -0.1869, p-value 0.10, one-sided, when using the new ROS, com- pared to a coefficient = 0.0062, p-value 0.15, one-sided, when using the new ROA, compared to a coefficient = 0.0054, p-value

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