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The Investment Opportunity Set and the Voluntary Use of Outside
EUROPEAN BUSINESS MANAGEMENT SCHOOL EBMS Working Paper EBMS/2000/8 (ISSN: 1470-2398) The Investment Opportunity Set and the Voluntary Use of Outside Directors: New Zealand Evidence M. Hossain, S. F. Cahan, M. B. Adams European Business Management School Singleton Park Swansea SA2 8PP UK Tel: 01792 295601 (International: +44 1792 295601) Fax: 01792 295626 (International: +44 1792 295626) e-mail: email@example.com The Investment Opportunity Set and the Voluntary Use of Outside Directors: New Zealand Evidence M. Hossain, S. F. Cahan, M. B. Adams* Abstract — This study examines whether the composition of boards of directors differs between high and low growth firms. Based on prior research, we hypothesise that firms with greater investment opportunities require more monitoring because managers in these firms have more discretion both in selecting investments and allocating resources between investments. Because outside directors can be more effective monitors than inside directors, we predict that outsiders will make-up a larger proportion of the board in high growth firms than in low growth firms. Using a cross-sectional sample of 77 New Zealand firms, our results suggest that the percentage of outside directors is related to growth for two of the four measures of investment opportunities which we employ. As expected, the percentage of outside directors is also related to a composite measure of investment opportunities. * Mahmud Hossain is Assistant Professor at Nanyang Technological University. Steven F. Cahan is Professor at Massey University. Michael B. Adams is Professor at the University of Wales - Swansea. The authors appreciate the comments of workshop participants at University of Exeter, Macquire University and Nanyang Technological University. Financial support received from the Massey University Research Fund is also very much appreciated. 1. Introduction The corporate governance role played by outside directors has been a topic of considerable controversy in both the academic and professional literature (e.g., Fama and Jensen, 1983; Bhagat and Black, 1997; Shleifer and Vishny, 1997; Klein, 1998). Fama and Jensen (1983), among others, argue that independent or outside directors can efficiently and effectively control management in agency settings where ownership and management are separate. For example, Klein (1998, p. 301) reports that "firms increasingly are replacing their inside directors with outsiders ... primarily [due] to external pressures from groups (for example, shareholder activists and the financial press) who actively advocate the perceived benefit of ... firms having boards totally independent from management." Therefore, outside directors are valued because their interests are more closely aligned with the owners when compared to inside directors who hold positions in the firm and who may have incentive to pursue activities that do not increase firm value.1 Numerous studies (e.g., Byrd and Hickman, 1992; Brickley et al., 1994; Agrawal and Knoeber, 1996) examine the determinants of board composition and/or the effectiveness of outside directors.2 However, none of these studies focus explicitly on the link between a firm's investment opportunities and the composition of its board. This is surprising as board structure is likely to be endogenously determined and is likely to be related to the firm's growth options. For example, prior research (e.g., Smith and Watts, 1992; Gaver and Gaver, 1993; Skinner, 1993) find that contracting mechanisms related to capital structure, dividend policy, compensation and accounting policies are related to the firm's investment opportunity set (IOS). In order words, because there are cross-sectional differences in investment options and different investment options imply variations in the levels and types of agency costs, firms will choose several contracting mechanisms to efficiently address these costs. We argue that board structure is another contracting mechanism that can be used to reduce agency costs. Accordingly, we expect to find cross-sectional variation in the proportion of outside directors on the board, and this variation should be a function of the firm's IOS. Using a final sample of 77 New Zealand- based firms, we find that the proportion of outside directors is positively related to two of three common measures of IOS. In addition, we find that board composition is inversely related to control variables for low inside ownership and firm size and positively related to control variables for leverage and the number of board meetings per year. In contrast, a control variable for Chief Executive Officer (CEO) tenure does 1 Others question the ability of outside directors to objectively monitor corporate decisions. For example, Patton and Baker (1987) point out that outside directors are usually nominated and appointed by top management, and often hold only a trivial fraction of the firm's shares. 2 See Bhagat and Black (1997) and Shleifer and Vishny (1997) for reviews of this literature. not appear to be an important determinant of board composition for our sample. Overall, our results add to the literature by showing that corporate governance is another managerial policy issue that is affected by IOS. We divide the rest of the study into five more sections. Section 2 develops our hypothesis. Section 3 provides background information on the institutional environment in New Zealand. Section 4 describes the research design, including the sources of data, the statistical model used and the measurement of the variables. Section 5 presents the results, while section 6 summarises and concludes the paper. 2. Hypothesis Myers (1977) argues that firm value consists of two main elements. These are: 1/ real assets (called assets-in-place) which are valued independently of managers' future discretionary investment, and 2/ real options (assets yet to be acquired) where the value of real options depends on future discretionary investments. Examples of the latter include expansion projects, new products, business acquisitions, and marketing programmes (Gaver and Gaver, 1993). Alchian and Woodward (1988) define IOS differently than Myers (1977). They view IOS as being related to a resource's "plasticity" and monitoring costs. They defined investments as plastic if they have "a wide range of discretionary, legitimate decisions within which the user may choose or that an observer can less readily monitor the choice" (Alchian and Woodward, 1988, p. 69). In comparing drug and steel manufacturing firms in the United States (US), Alchian and Woodward (1988) indicate that the former had wider initial options to control decisions about resources than the latter. The activities of drug companies may also be difficult to monitor and control because of the specialised nature of their activities. When managers have special information or specific knowledge about investment options, it can be efficient to let them choose which options to pursue (e.g., Jensen and Meckling, 1995). However, in such cases, agency costs also increase because managers may not always have incentives to maximise firm value (e.g., see Brickley et al., 1997). For example, managers may have incentive to empire-build by making diversified acquisitions that reduce firm value. Gaver and Gaver (1993, p. 129) write: "[A]s the proportion of firm value represented by growth opportunities (as opposed to assets in place) increases, the observability of managerial actions decreases. This is because it is difficult for outside shareholders, without the inside information and specialized knowledge of managers, to ascertain the menu of investment opportunities available to the firm." Where the principal delegates to an agent the right to initiate and implement decisions, it is important for the principal to retain decision control authority, i.e., the right to ratify and monitor decisions (e.g., Fama and Jensen, 1983; Brickley et al., 1997). Because managers have to make and implement more investment decisions when growth options are high, we expect that monitoring would increase to counteract the increase in managerial discretion.3 Oversight by boards of directors, particularly outside directors, is a common and generally effective form of monitoring (e.g., see Fama and Jensen, 1983). In addition, we expect monitoring by directors, who represent shareholders' interests, to be a particularly important form of monitoring in high growth firms because these firms rely more on equity financing than low growth firms. To be specific, Myers (1977) contends that agency costs of debt will be lower when firms have more real assets than real options because assets-in-place are generally acquired for specific business purposes. This constrains managerial discretion and lowers borrowing costs. On the other hand, real options can lead to underinvestment in the presence of fixed debt because debtholders have a priority claim to the cash flows arising from positive NPV projects (Myers, 1977). To control for underinvestment, Myers (1977) predicts that firms with more investment opportunities are likely to use equity rather than debt financing, and in their studies Smith and Watts (1992) and Gaver and Gaver (1993) find an inverse relation between IOS and debt/equity ratios. While agency problems between shareholders and debtholders are minimised when less debt is used, in high growth firms, conflict between shareholders and managers will increase as equity financing puts fewer restrictions on management activity relative to covenant-based debt (Skinner, 1993). Because the value of high growth firms is dependent upon managers' discretionary investment decisions, absentee shareholders will put in place ex ante mechanisms, such as outside directors, to monitor the initiation and implementation of decisions by management. Thus, we hypothesise: H1 Ceteris paribus, the proportion of outside directors on the board will be positively related to the level of IOS. 3. Institutional environment An important factor which is likely to influence the relation between board composition and IOS is the institutional environment in which the corporation operates (Smith and Watts, 1992). We argue that the institutional environment in New Zealand helps to provide a clean and powerful test of the IOS hypothesis for two reasons. First, recent changes in New Zealand’s company law have clarified and codified directors' duties. For example, the Companies Act 1993, which became effective 1 July 1994, requires that directors: 1/ act 3 Another way to address these agency costs is to better align the managers' and shareholders' interests. For example, both Smith and Watts (1992) and Gaver and Gaver (1993) find a positive relation between IOS and the incidence of market-based incentive contracts in the US corporate sector. In New Zealand, however, market-based incentive contracts are relatively rare. in good faith and in the best interests of the company; 2/ exhibit care, diligence, and skill that a reasonable person would exercise; 3/ avoid conflicts of interest; and 4/ exercise their powers for legitimate corporate purposes. The new Companies Act also increased directors' responsibilities regarding distributions to shareholders, repayments to creditors, and the accuracy of the company's financial statements. For example, under section 52 of the Companies Act 1993, directors are required to certify that the company will satisfy a solvency test before authorising a distribution (i.e., dividends) to shareholders. Likewise, directors now must ensure that financial statements of the reporting entity comply with applicable financial reporting standards (i.e., generally accepted accounting practice). These changes were brought about by problems with the previous companies law, i.e., the Companies Act 1955. For example, in 1989, the Law Commission noted that "the present [company] law relating to duties of directors is inaccessible, unclear, and extremely difficult to enforce" (quoted in Hodder, 1993, p. 38). Thus, by specifying directors' duties, the Companies Act 1993 highlights the director's monitoring role in corporate governance. In addition, because the monitoring function falls on the outside directors, the Companies Act 1993 sharpens the distinction between inside and outside directors, and this strengthens the power of our tests. Second, unlike the US where there have been several proposals to require boards with a majority or super-majority of outside directors (see Bhagat and Black, 1997, for a review), there have been no similar proposals in New Zealand. This is important because rather than adding outside directors to reduce agency costs, US firms may also add outside directors to avoid attention from activist shareholder groups. More simply, at least some US firms may use outside directors for cosmetic reasons or as “window- dressing”. Thus, using New Zealand data, we avoid this competing hypothesis and so provide a cleaner test of the IOS hypothesis. 4. Research design 4.1. Sample selection The sample used in this study initially comprised 80 firms selected from the 129 companies listed on the New Zealand Stock Exchange (NZSE) as at 31 December 1995 and included in the Share Market Review (1995) published by the NZSE. The sample consists of firms that: 1/ responded to our written request for annual reports for the year 1995; and 2/ agreed to participate in a postal questionnaire survey requesting information about the equity ownership structure, board composition and characteristics of board of directors. Ninety-four firms responded to our requests for annual reports. Of the 94 firms, 80 firms agreed to participate in the postal survey. However, this sample was reduced to 77 firms after three firms were excluded as outliers (see section 5). Thus, our final sample covers approximately 60 percent of the companies listed on the NZSE in 1995. Financial data items were extracted primarily from the published annual reports and supplemented with information obtained from Datex, a NZ financial information provider, and survey responses. While we examined early and late responses and detected no statistical differences in their responses, if non- respondents have systematically weaker corporate governance system (e.g., use less outside directors), the research findings may not be generalisable to all NZ firms. Therefore, we recognise this as a limitation of our research design. 4.2. Variables Outside directors are one of several internal mechanisms (e.g., stock option plan, auditing, voluntary disclosures) that a firm could use to control agency problems and improve firm value. Because the use of outside directorships may be correlated with other internal monitoring mechanisms, as they are all driven by a common firm-specific factor - IOS (Rediker and Seth, 1995), corporate governance decisions are likely to be made simultaneously within the firm. However, Smith and Watts (1992), Gaver and Gaver (1993) and Barclay and Smith (1995) argue that allowing for interdependencies (simultaneity) among policy variables would require specification of a system of simultaneous equations. At present the IOS literature does not provide adequate insights or direction to allow us to identify the appropriate structural form of this system of equations, and we adopt the approach used in much of the prior literature, i.e., we examine a single corporate policy decision and assume IOS is pre-determined.4 In line with Smith and Watts (1992), Skinner (1993), Barclay and Smith (1995) and Mian (1996), we specify the board structure-IOS relation using a reduced form Ordinary Least Squares (OLS) model where the proportion of outside directors on the board is the dependent variable and IOS is an independent variable. 4 Titman and Wessels (1988), Jensen et al. (1992), and Agrawal and Knoeber (1996) are examples of studies that use a simultaneous equation framework. However Smith and Watts (1992, p. 269) also comment that if "the structure they use is correct, the power of their estimates is increased, but if their structure is incorrect, they impose bias. Given our current knowledge of these empirical relations, we believe progress is better served by documenting robust empirical relations between policy parameters and exogenous variables before attempting to subdivide the relations into component effects." However, because IOS is not the only determinant of board composition, we control for other determinants of board structure in our OLS model. 4.2.1 Dependent variable We define the proportion of outside directors on the board (DIR) as the number of independent outside directors on the board divided by the total number of directors on the board. Independent outside directors are board members who: 1/ are not an active or retired employee of the firm, and/or 2/ do not have close business ties with the firm (e.g., a consultant or supplier). While our measure distinguishes between affiliated outside directors and independent outside directors (e.g., as in Lee et al., 1992), we collect this data by a postal questionnaire rather than from annual reports or proxy statements as most US studies have done. We use postal questionnaires because disclosures about directors in New Zealand are limited and because we wanted to collect information on CEO tenure and the number of board meetings per year (see section 4.2.3). However, we did check the reliability of the data obtained from the postal survey by comparing them with data derived from the annual reports for a sub-sample of firms. We detected no significant discrepancies.5 4.2.2 Independent variable - IOS IOS is measured by various proxies employed in the prior research. We use four of the most common, specifically: 1/ market value of the firm to book value of assets (e.g., Smith and Watts, 1992; Barclay and Smith, 1995; Baber et al., 1996 ); 2/ market to book value of equity (e.g., Gaver and Gaver, 1993; Lang et al., 1996); 3/ price-earnings (P/E) ratio (e.g., Smith and Watts, 1992; and Gaver and Gaver, 1993); and 4/ an ex-post measure, asset growth (e.g., Pilotte 1992) The market value of the firm to book value assets, MKTBKA, is a measure of the percentage of firm value attributable to assets-in-place. This measure assumes firms with more growth options will have market values far in excess of their book values. MKTBKA is computed as the market value of assets divided by book value of assets, where market value of assets is defined as the reported value of debt plus the market value of equity. Gaver and Gaver (1993) point out that using MKTBKA induces bias for firms with long-lived assets because typically assets are measured on a historical costs basis. However, because New Zealand-based companies can revalue their non-current assets to show current costs in the financial statements, this problem is not severe in the present study. Also, MKTBKA is the growth measure used most frequently in prior studies (e.g., see Jung et al., 1996; Mian, 1996). 5 A copy of the questionnaire is available from the first author on request. Another measure used in studies such as Gaver and Gaver (1993) and Barclay and Smith (1995) is the market equity to book equity ratio or MKTBKE. Because high growth firms will have more intangible assets that are not recorded but are priced by the market, MKTBKE should increase with increases in growth opportunities. MKTBKE is measured by the ratio of market value of equity to market value of assets where the market value of equity is estimated by the number of shares outstanding multiplied by share price at the calendar year end. A problem with using MKTBKE to proxy for IOS is that MKTBKE could also reflect other factors such as the ability of firms to earn monopoly rents on assets-in-place, and competition across firms (Ahmed, 1994), and the expected return on equity and risk (Penman, 1996). The third IOS measure is the P/E ratio (e.g., Chung and Charoenwong, 1991; Gaver and Gaver, 1993). The rationale for this measure is that because a firm's share price reflects future earnings and not the current period's income, the difference between current and future earnings will be more pronounced for high growth firms. As a result, high growth firms will trade at higher P/E ratios than low growth firms. However, a problem with this measure (as well as MKTBKA and MKTBKE) is that it relies on the market value of corporate shares. Because share prices decrease with increases in leverage, the market- based measures of IOS are likely to be sensitive to the firm's capital structure (Gaver and Gaver, 1993). The fourth measure is the growth in assets or ∆ASSETS. Pilotte (1992) contends that, under rational expectations, actual subsequent growth should be good proxy for anticipated investment. One problem with the ex post proxy is that they measure actual growth rather than the profitability on new investment. While these are the most common IOS measures, because each has limitations, we also factor analyse to construct a composite measure of IOS.6 4.2.3. Control variables 6 Because most firms in our sample are not engaged in research and development (R&D), we omit this variable even though it has been used in prior studies (e.g., Gaver and Gaver, 1993). Industry membership is another variable that has been used as a proxy for IOS in prior research (e.g., Chan et al., 1990). However, as Gaver and Gaver (1993) argue, cross-sectional variation in IOS is also likely at the firm level. Because we are interested in board composition which is a firm-specific decision, we also do not use industry membership. In testing H1, we control for other factors that may also affect board composition. For example, the degree of incentive conflicts and agency costs will be a function of managerial ownership (e.g., Jensen and Meckling, 1976; Fama and Jensen, 1983). Firms with low levels of managerial ownership will have more demand for outside directors, and prior studies (e.g., Bathala and Rao, 1995; Rediker and Seth, 1995) empirically document such a relation. We include inside ownership (defined as a percentage of common equity owned by directors and the “top five” managers) as a control variable. We measure inside ownership using a dummy variable. Morck et al., (1988) argue that firms that are 5 to 25 percent owned by management are likely to have lower market values. Consequently, we use a dichotomous measure INSDUM as a surrogate for inside ownership. INSDUM is coded 1 if inside ownership is less than or equal to 5 percent and greater than or equal to 25 percent , and 0 elsewhere. Likewise, Jensen and Meckling (1976) suggest that agency conflicts between shareholders and debtholders increase with leverage. To the extent that outside directors can mitigate these conflicts, the demand for outside directors should be positively related to levels of debt. In addition, because debt imposes fixed costs on the firm and increases the possibility and costs associated with bankruptcy (Jensen and Meckling, 1976), the need for additional monitoring by outside directors will also increase. We include leverage as a control variable where leverage is defined as the book value of long term liabilities divided by total assets (LEV). Hermalin and Weisbach (1988, 1991) suggest that long serving CEOs have a greater influence over the selection of board members and may include directors who are likely to be closely aligned with the CEO's interests. Menon and Williams (1993) argue that the effectiveness of outside directors will increase when boards meet more frequently. This suggests that outside directors are more useful when meetings are frequent, and meeting frequency should be positively related to the proportion of outside directors. In any case, we include CEO tenure (CEOTEN) and the number of board meetings as additional controls. Both items were obtained from our postal questionnaire survey. Firm size has been included as a control variable because prior research (e.g., Garver and Garver, 1993; Mehran, 1995) suggests that firm size is related to incentive control mechanisms including debt, dividends and managerial compensation. Further, Gaver and Gaver (1993) and Barclay and Smith (1995) predict that large firms have more information asymmetry between managers and outside stakeholders, and this creates demand for outside directors. However, Rosenstein and Wyatt (1990) suggest small firms will have more outside directors because large firms can rely on alternative monitoring mechanisms (e.g., institutional investors, stock analysts). Consistent with previous IOS studies (e.g., Mian, 1996), we use the book value of assets minus the book value of common equity plus the market value of common equity as a proxy for firm size. This amount is transformed using a natural log and is labeled LNSIZE. However, given the prior discussion, no directional sign is predicted for the coefficient. 4.2.4 Model specification We test H1 using the following OLS model: (1) DIR = b0 + b1 IOS + b2 INSDUM + b3 LEV + b4 CEOTEN + b5 BRDMEET + b6 LNSIZE +e where DIR, INSDUM, LEV, CEOTEN and LNSIZE are those described in sections 4.2.1-4.2.3, and b0 is the intercept and e is an error term which is assumed to be normally distributed with zero mean. IOS is either MKTBKA, MKTBKE, P/E, GSALES or a composite IOS measure depending on the exact model. 5. Results 5.1. Main statistical tests Table 1 provides descriptive statistics for DIR and the right-hand side variables. We also examined scatter plots of the distribution for the variables and identified two extreme values for P/E (i.e., 110 and 73.3) and extreme values for MKTBKA (9.314) and MKTBKA (19.01) for another firm. Because each of these values are more than 59 percent larger than the next highest value, these three firms are deleted, reducing the sample to 77 from 80. The mean for DIR is 52 percent indicating that on average outside directors comprise a majority of the board. The mean of inside ownership is 17 percent, and the mean for CEOTEN is 6 years. Each of these values is similar to those reported in prior US-based studies (e.g., Mehran, 1995; Dechow et al., 1996). <Insert Table 1 here> Table 2 gives a correlation matrix for the IOS and control variables. As predicted, individual IOS measures such as MKTBKA and MKTBKE are significantly and negatively correlated with leverage ( r = -0.409, p ≤ 0.001 and r = -0.379, p ≤ 0.001 respectively) which is consistent with previous IOS research (e.g., Smith and Watts, 1992; Gaver and Gaver, 1993; and Barclay and Smith, 1995 ). The INSDUM variable is significantly and negatively correlated with firm size ( r = -0.349, p ≤ 0.01) which is similar to prior studies (e.g., Jensen et al., 1992). Also, we find a significant positive correlation between firm size and P/E ratio (r = 0.429; p ≤ 0.001). Regarding correlations between individual IOS measures, only MKTBKA and MKTBKE are positively and significantly correlated (r = 0.911, p ≤ 0.001). However, there are no significant correlations between other IOS variables. This is surprising as Gaver and Gaver (1993) found statistically significant correlations among all individual IOS variables. However, our correlation tests are not nearly as powerful as the ones used by Gaver and Gaver (1993) since they use 1525 US firm-based observations. <Insert Table 2 here> Table 3 provides the multiple regression results for equation 1. The four models shown differ in term of the proxy used for IOS. Each of the models is statistically significant with R2 varying between 20 percent and 26 percent. The R2 statistics are comparable to similar models using US data (e.g., Brickley and James, 1987, R2 = 26 percent; Bathala and Rao, 1995, R2 = 19 percent). Though all four IOS variables have positive signs, only two, MKTBKA and MKTBKE, are statistically significant (p = 0.01 based on one-tailed tests). Thus, we find some evidence that investment opportunities require additional monitoring and give managers incentives to hire independent outside directors (Gaver and Gaver, 1993; Booth and Deli, 1996). This supports H1. <Insert Table 3 here> Of the control variables, firm size is significant at 0.05 level or better (two-tailed tests) with a negative sign in all three models. This is consistent with Rosenstein and Wyatt's (1990) view that small firms have fewer alternative monitoring mechanisms and, consequently, will rely on outside directors. INSDUM is significant with a negative sign in each of the models indicating that at low levels of managerial ownership, inside ownership is not sufficient to align the manager's interests with the shareholder's interests, and that at these levels, management may try to entrench itself by adding inside or affiliated outside directors. The coefficient for BRDMEET is positive and significant at 0.05 level (one-tailed tests) in all four models, indicating that frequently meeting boards are more likely to include outside directors to protect against such behaviour as earnings management and misuse of free cash flows (Menon and Williams, 1993). LEV is positively related to DIR at the 0.10 level (one-tailed test) in models 1 and 2 which suggests that firms with more debt rely on outside directors to minimise conflict between shareholders and debtholders. Finally, CEOTEN is not statistically related to board composition in any of the models, suggesting that this variable is not related to board composition which is contrary to US-based results reported by Hermalin and Weisbach (1988) and Bathala and Rao (1995).7 7 Following Hermalin and Weisbach (1991), the regressions were re-run using four piecewise variables for CEOTEN. However, the results were unchanged, and so these results are not reported here. 5.2. Additional tests8 5.2.1 Sensitivity analysis The empirical results presented in the preceding section select a particular point in time to observe the relation between board composition and IOS. One problem with the cross-sectional tests is that they do not examine explicitly whether the fraction of outside directors presently employed by a firm is due to the firm’s current IOS or due to its historical IOS. Furthermore, the cross-sectional tests do not examine the endogeneity, or reverse causation, between the fraction outside directors and IOS. For example, it is possible that a higher proportion of outside directors provides more effective monitoring, and this leads to higher company performance as measured by market to book ratios.9 Finally, our coefficient estimates may be “contaminated” by time invariant fixed firm effects. To partially address these problems, we investigate whether changes in the fraction of outside directors are related to the changes in IOS on a sub-sample of 53 firms10. Changes in the fraction of outside directors and IOS in year t are computed for each firm i over a five year period 1991-95. For example, the change in the fraction of outside directors in year t is computed by the ratio of an increase (decrease) in the fraction of outside directors from t to t-4 divided by the fraction of outside directors for the year t-4 where t-4 is 1991 and t is 1995. Thus, we estimate the following changes model: (2) ∆DIR =b0 + b1 ∆IOS + ∆e where b1 represents an uncontaminated estimate of the relation between IOS and DIR (i.e., fixed effects removed) and where b0 can be interpreted as a time effect. Table 4 contains the results for the changes model. The results indicate that two of the three IOS models are significant. Contrary to expectations, the coefficient for ∆P/E is not significant at conventional levels. However, the coefficients on ∆MKTBKA and ∆MKTBKE are positively and significantly related at 0.01 8 As in Gaver and Gaver (1993), we used factor analysis to extract a composite IOS measure form the individual IOS variables. The composite measures (proxied by IOSFAC and IOSDUM) yielded results similar to those reported in Table 3. Both IOSFAC and IOSDUM were significant at 0.05 level. To economise on space, however, we do not present these results in this paper. 9 We are grateful to an anonymous reviewer for making this point. Theoretically, a two- stage least square (2SLS) should be used to test simultaneous effect between the DIR and IOS. Because IOS hypothesis is not adequately developed and because a simultaneous relationship between DIR and IOS is difficult to predict on an ex ante basis (Bhagat and Black, 1997), 2SLS is not estimated in this study. 10 Estimation of a fixed-effects covariance model proved difficult on the small cross- sectional and time series data set available. In particular, there was collinearity between the dummy variable INSDUM and the fixed-effects parameters that inhibited the derivation of complete and meaningful coefficient estimates. and 0.05 levels respectively. These results are consistent with our cross-sectional results and suggest that the fraction of outside directors increases with contemporaneous increases in IOS. Taken together with our earlier tests, the results for IOS appear to be robust. <Insert Table 4 here> 6. Summary and conclusions This study has examined empirically the determinants of board composition in the NZ corporate sector. Based on Smith and Watts (1992) and Gaver and Gaver (1993), we use an efficient contracting perspective and predict that the use of independent outside directors will differ between high growth and low growth firms. The empirical results obtained from cross-sectional tests of 77 New Zealand firms indicates that the proportion of outside directors is significantly and positively related to IOS, leverage, and the number of board meetings, and is significantly and negatively related to low levels of inside ownership and firm size. In contrast, CEO tenure and high levels of inside ownership do not appear to be significantly related to the proportion of outside directors, at least for our sample. Our results support the view that high growth and the use of outside directors are related. Moreover, we show that the change in outside directors is related to contemporaneous changes in IOS. While both the determinants of board composition and the effect of IOS on corporate policy decisions have been examined extensively in the literature, our study is the first to explicitly examine the effect of IOS on board composition. In doing so, we contribute to, and provide a link between, the largely separate IOS and board composition literatures. From a policy standpoint, our results also suggest that the optimal composition of the board, in terms of inside and outside directors, will not be the same for high and low firms. Consequently, mandating that all firms use a majority or super-majority of independent outside directors could result in less efficient (i.e., sub-optimal) board structures from a societial point of view (Jensen, 1993). As with any research, a few caveats deserve mention. First, the empirical tests carried out in our study may suffer from omitted variables. For instance, theoretical and empirical research suggests the number of outside directorships held by CEOs is likely to be affected by supply side factors such as the CEO's career cycle and interlocking boards (Booth and Deli, 1996). Therefore, it is possible that the empirical relations shown in our study could be driven by cross-sectional differences in omitted supply-side factors that affect board composition. A second limitation arises from possible data measurement errors. If our proxies for IOS and outside directors are noisy, measurement error could potentially reduce the statistical power of the tests. Third, the explanatory variables used in our study are considered exogenous, but Smith and Watts (1992), Gaver and Gaver (1993) and others recognise that several explanatory variables used in this research, including IOS, may be endogenous. Fourth, the present study is essentially a single period, small sample analysis. 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Minimum Maximum Numberb DIR 0.520 0.500 0.273 0.000 1.000 77 IOS variables MKTBK 1.425 1.115 0.927 0.542 5.846 77 MKTBKE 1.611 1.270 1.264 0.318 7.881 77 P/E 11.022 9.950 7.516 -15.790 35.090 77 ∆ASSETS 0.185 0.044 0.669 -0.845 3.424 77 Control variables INSDUM 0.208 0.000 0.408 0.000 1.000 77 LEV 0.198 0.161 0.202 0.000 0.775 77 CEOTEN 6.003 5.000 4.188 0.500 18.000 77 BRDMEET 9.61 11.000 2.987 1.000 14.000 77 LNSIZE 7.919 7.940 0.809 0.606 10.132 77 a DIR = number of independent outside directors/total directors; MKTBKA = market value of firm value to book value of assets; MKTBKE = market value of firm to book value of equity shares; P/E = price per share to primary earnings per share; ∆ASSETS= Growth in total assets between 1991-95; INSDUM = percentage of insider (directors and top five managers) ownership INSDUM is coded 1 if inside ownership is less than or equal to 5 percent and greater than or equal to 25 percent , and 0 elsewhere; LEV = long term liabilities/total assets; CEOTEN = number of years the CEO has been on the job; BRDMEET =number of board meetings per year; LNSIZE = natural logarithm of firm value. b The sample size of 77 is obtained after omitting three outliers. TABLE 2. Pairwise correlation coefficients MKTBK MKTBKE P/E ∆ASSETS INSDUM LEV CEOTEN BRD LNSIZE A MEET IOS variables MKTBKA 1.000 MKTBKE 0.911b 1.000 P/E -0.111 -0.005 1.000 GSALES 0.397 0.243 -0.172 1.000 Control variables INSD -0.067 -0.098 -0.072 -0.085 1.000 LEV -0.409b -0.379b 0.033 0.186 0.038 1.000 CEOTEN 0.053 0.056 -0.083 0.044 0.194 -0.120 1.000 BRDMEE 0.005 0.007 -0.133 0.078 -0.147 0.182 0.002 LNSIZE -0.078 0.143 0.429b 0.318c -0.349c 0.050 0.086 1.000 a See Table 1 for variable definition and sample size. b Significant at 0.001 level based on two-tailed test. c Significant at 0.01 level based on two-tailed test. TABLE 3. Estimated Coefficients (t-statistic in parentheses) from OLS Regressiona,b Individual IOS Variables Control Variables Mdl MKTBKA MKTBKE P/E ∆ASSETS INSDUM LEV CEOTEN BRD LNSIZE Incpt MPrb R2 + + + + - + - MEET +/- +/- + 1 0.084 -5.801 0.388 0.004 0.017 -0.103 1.163 0.005 26.2% (2.565)c (-2.002)c (1.516)e (0.635) (1.754)d (-2.299)d (3.064) 2 0.060 -5.377 0.398 0.005 0.017 -0.124 1.344 0.005 25.9% (2.505)c (-1.869)c (1.541)e (0.656) (1.759)d (-2.669)c (3.490) 3 0.004 -4.816 0.181 0.005 0.019 -0.107 1.251 0.044 19.8% (0.915) (-1.662)c (0.701) (0.589) (1.877)d (-2.097)d (3.083) 4 0.406 -4.873 0.330 0.062 0.018 -0.094 1.355 0.026 19.3% (0.487) (-1.920)c (1.659) e (0.697) (1.753) d (-2.037)d (3.658) a Dependent variable = DIR. See Table 1 for variable definitions. Sample sizes are 79, 79, 78 , and 80 after omitting outliers. b Model probability is based on a F-statistic. Significance levels for t-statistics are based on one-tailed tests except for LNSIZE. c Significant at 0.01 level. d Significant at 0.05 level. e Significant at 0.10 level. TABLE 4. Estimated coefficient (t-statistic in parentheses) from OLS regression changes modela ∆ IOS variables Mdl ∆MKTBKA ∆MKTBKE ∆P/E ∆ASSETS Incpt MPrbb R2 + + + + +/- 1 0.110 0.404 0.005 14.34% (2.922)c (10.016) 2 0.054 0.422 0.020 10.87% (2.494)d (10.690) -0.001 3 0.468 0.596 0.56 ( -0.534) (9.197) -0.036 0.127 4 0.058 0.025 (-0.536) (1.938) a Dependent variable = ∆DIR where ∆DIR = DIR1995 - DIR1991/DIR1991. ∆MKTBKA = MKTBKA1995- MKTBKA1991/MKTBKA1991; ∆MKTBKE = MKTBKE1995- MKTBKE1991/MKTBKE1991; ∆P/E = P/E1995 -P/E1991/P/E1991, ∆Assets = ASSETS1995 – ASSETS1991/ ASSETS1991. Sample size is 53 based on all firms with data available for 1991 and 1995. b Model probability is based on a F-statistic. c Significant at 0.01 level based on one-tailed test. d Significant at 0.05 level based on one-tailed test.
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