Thành viên hội đồng quản trị độc lập cùng lúc tại nhiều công ty và tài trợ bên ngoài: Bằng chứng thực nghiệm ở thị trường mới nổi

Nội dung text: Thành viên hội đồng quản trị độc lập cùng lúc tại nhiều công ty và tài trợ bên ngoài: Bằng chứng thực nghiệm ở thị trường mới nổi

1. INTERNATIONAL CONFERENCE FOR YOUNG RESEARCHERS IN ECONOMICS & BUSINESS 2019 ICYREB 2019 INDEPENDENT DIRECTOR BUSYNESS AND EXTERNAL FINANCE: EVIDENCE FROM AN EMERGING MARKET THÀNH VIÊN HỘI ĐỒNG QUẢN TRỊ ĐỘC LẬP CÙNG LÚC TẠI NHIỀU CÔNG TY VÀ TÀI TRỢ BÊN NGOÀI: BẰNG CHỨNG THỰC NGHIỆM Ở THỊ TRƯỜNG MỚI NỔI Tran Thi Ngoc Vy University of Economics, The University of Danang vyttn@due.edu.vn ABSTRACT Extant literature presents mixed results on the role of busy directors play in corporate performance However, little research has been done examining whether busy independent boards affects corporate external finance, and whether this impact (if any) differs between group and non-group firms. In this paper, we address these issues directly using unbalanced panel data of 445 top Indian firms sourced from the BSE 500 and the CNX 500, from 2000 to 2014. Within the two-step system GMM framework, the study shows a negative association between busy independent boards and firms’ external finance. It also reveals that, compared to non-group firms, group firms with greater connectedness of independent directors face more limited access to external finance. Our results survive extensive robustness checks and provide a negative counterpoint to the positive correlation between independent board busyness and corporate performance. Keywords: Business groups, independent boards, external finance, financial debt, India. TÓM TẮT Các nghiên cứu trước đây đã ghi nhận cả tác động tích cực và tiêu cực của thành viên hội đồng quản trị cùng lúc làm tại nhiều công ty đối với kết quả hoạt động công ty. Tuy nhiên, có rất ít nghiên cứu xem xét đến: (1) Tác động của hội đồng quản trị mà ở đó phần lớn thành viên độc lập đều kiêm nhiệm (ở rất nhiều công ty) đến tài trợ bên ngoài của công ty;(2) sự khác nhau (nếu có) của tác động này đối với các công ty thuộc tập đoàn kinh doanh và các công ty độc lập (không thuộc tập đoàn). Trong bài nghiên cứu này, tác giả tập trung giải quyết những vấn đề này, sử dụng dữ liệu ở 445 công ty hàng đầu của Ấn Độ thuộc chỉ số BSE500 và CNX500, trong giai đoạn 2000 - 2014. Áp dụng mô hình GMM, nghiên cứu đã tìm ra mối quan hệ tương quan âm giữa thành viên hội đồng quản trị độc lập này và tài trợ bên ngoài của công ty. Nghiên cứu cũng cho thấy so với các công ty độc lập, các công ty thuộc tập đoàn kinh doanh và có nhiều thành viên hội đồng quản trị độc lập kiêm nhiệm gặp hạn chế hơn trong việc tiếp cận với nguồn tài trợ bên ngoài. Kết quả nghiên cứu này vẫn không thay đổi qua nhiều bước kiểm tra và cung cấp kết quả đối lập với các nghiên cứu cho thấy mối quan hệ tương quan dương giữa thành viên hội đồng quản trị độc lập kiêm nhiệm và hoạt động của công ty. Từ khóa: Tập đoàn kinh doanh, hội đồng quản trị với đa số thành viên độc lập, tài trợ bên ngoài, nợ tài chính, Ấn Độ. 1. Introduction In a lending relationship, through corporate disclosure, companies communicate their performance and governance to outside investors (Healy and Palepu, 2001). However, as borrowers, companies know more about their prospects, profitability, potential risks and the quality of their information disclosure than creditors. Such information asymmetry creates a moral hazard problem when managers and shareholders have incentives to pursue their own interests at the expense of external stakeholders. To restore outside investors „trust in corporate performance and disclosure, further improvement in governance systems, more specifically, the board effectiveness, is hugely important (Bushman et al., 2004). Board of directors are expected to improve the reliability of information flow to investors in the market (Ashbaugh-Skaife et al., 2006; Chuluun et al., 2014). However, board members, especially independent directors, usually concurrently hold a great number of outside directorships. Put it differently, they build up their professional networks across firms. On the one hand, these directors are 332
2. INTERNATIONAL CONFERENCE FOR YOUNG RESEARCHERS IN ECONOMICS & BUSINESS 2019 ICYREB 2019 more visible to outside investors (Merton, 1987; Fang and Peress, 2009), and may provide legitimacy and prestige for the firms they serve (Pfeffer and Salancik, 1978; Certo, 2003). On the other hand, they hardly have enough time to monitor and consult with management teams effectively. Thus, they may let strategic corporate decisions be taken with undue influence of the inside management. This may reduce the confidence of outside capital suppliers in companies‟ performance disclosure, and will possibly make it more difficult for firms to access external finance. In this paper, we examine whether firms with a busy independent board (i.e. a board whose at least half the independent directors serve on three or more boards) face more limited access to external finance, and whether the impact of busy independent board on external finance differs between group and non- group firms. Very few recent papers have addressed these questions. Our paper differs from existing studies in two important aspects: First we pay particular attention to the role of independent directors and address the dynamic relation between busy independent boards and external leverage (i.e. financial debt (including bank and financial institution debt, bonds, commercial paper) over assets). Existing studies focus on either corporate bond or bank loan for US firms, and do not take into account such dynamic relation (Chuluun et al., 2014; Chakravarty and Rutherford, 2017). Second, we conduct the research in an emerging market whose governance mechanisms and institutional frameworks are in sharp contrast to those in developed markets. Prevalence of concentrated family-owned business, opacity of insider control, poor information disclosure measures, weak legal framework, and ineffective investor protection measures make asymmetric information problems more severe in emerging economies compared to the developed economies (Khanna, Kogan and Palepu, 2001; Balasubramanian, Black and Khanna, 2010; Seifert and Gonenc, 2010). Moreover, there is a concern about the conflict of interests between the controlling shareholders and minority shareholders (Type II- Agency Problems) (Morck and Yeung, 2003). The presence of independent directors is expected to reduce such problems and to increase corporate transparency. Thus, the role of these directors really matters to outside investors. Compared to developed markets, the average number of directorships per director in India is much higher (i.e. they are busier). The mean board seats for independent directors of the US companies range from 1.6 to 3 (Ferris et al., 2003; Fich and Shivdasani, 2006). Meanwhile, this estimated number is around five for top firms in India (Jackling and Johl, 2009). Moreover, India has a less developed capital markets, so companies rely more on external finance from banks and financial institutions for investment and performance. Specifically, banks remain the main source of funds even after 25 years of liberalization(Chauhan, 2016). As a result, these features make this emerging market an attractive setting to examine the reaction of Indian capital suppliers to borrowers whose independent boards are busy. To test our hypotheses, unbalanced panel data of 445 top Indian group and non-group firms over the period 2000-2014 was used. Applying alternative measures of director busyness to the fixed effects and the two-step system GMM model, the study shows a negative association between busy independent boards and firms‟ external finance. It also reveals that, compared to non-group firms, group firms whose independent directors are busy face more limited access to external finance. Our research makes several important contributions as follows: First, it contributes to the literature on the impact of busy independent boards on corporate finance. Second, it provides corroborating evidence for the vital role of board capital in firms with higher information asymmetry (Botosan, 1997; Butler, 2008; Mansi et al., 2011) and Type II-Agency problems. Third, it stresses the importance of good corporate governance in lending, and provides insights into one of the governance attributes (i.e. board busyness) that may increase or attenuate the potential conflict between creditors and borrowers. With regard to research methods, the study highlights the important source of endogeneity that arises because 333
3. INTERNATIONAL CONFERENCE FOR YOUNG RESEARCHERS IN ECONOMICS & BUSINESS 2019 ICYREB 2019 the relations among a firm‟s observable characteristics are likely to be dynamic. In the context of corporate governance, current firm external leverage may affect future governance choices, and these may, in turn, affect future firm leverage. The remainder of the paper is organized as follows. Section 2 presents related literature and hypothesis development. Section 3 presents data and summary statistics. Section 4 describes methods. Section 5 reports results and robustness checks, and Section 6 concludes. 2. Literature review and hypothesis development Through the advising and monitoring roles, a more independent board can alleviate information asymmetry on financial reporting and disclosure between companies and outside investors. Specifically, an 18 percentage point increase in the proportion of independent directors translates to roughly a 6% decrease in information asymmetry (Armstrong et al., 2014). For instance, independent directors are found to relate to effective financing and accounting processes (Klein, 2002); less financial statement fraud (Beasley, 1996); lower earnings management (Pathak and Sun, 2013); fewer firm risks (Brick and Chidambaran, 2007); higher accounting quality and earnings informativeness (Petra, 2007); Ferreira et al., 2011); greater timely recognition of losses (Beekes et al., 2004; Ahmed and Duellman, 2007).Al of this helps to improve the credit ratings of borrowers (Ashbaugh-Skaife, Collins and LaFond, 2006) and trust from creditors, which facilitates borrowers‟ access to external finance. 2.1. Busy independent board and external finance Given the importance of independent directors to corporate transparency and firm performance, there are doubts over the effectiveness of directors who serve simultaneously on a number of boards (i.e. well-connected directors). On the one hand, it may be true that firms with well-connected directors are more visible to investors, because media coverage is likely to be greater for these firms, and this coverage facilitates investor recognition (Merton, 1987; Fang and Peress, 2009). Reputed directors also provides legitimacy and prestige for the firms they serve (Pfeffer and Salancik, 1978; Certo, 2003). Hence, such board members may possibly act as a link between firms and the external environment to facilitate access to capital for corporate operations. On the other hand, it is highly possible that well-connected directors are too busy to perform their monitoring and advising role as effectively as expected, which will badly impact corporate transparency due to an increase in agency problems (Ferris et al. 2003).Being a firm‟s directors, they are required to actively participate in board meetings and to carefully prepare before such meetings. According to the National Association of Corporate Directors, the time commitment for board members with one directorship was, on average, 227.5 hours in 2011 (Lublin, 2012). Consequently, when directors serve on multiple boards, they can hardly allocate enough time for each company. There has been growing empirical support for this busyness hypothesis. For instance, Loderer and Peyer (2002) and Arranz-aperte and Berglund (2008) show that directors with multiple directorships do not have enough time to dedicate to multiple mandates. Jiraporn et al. (2009) point out that these directors show an obvious tendency to be absent from board meetings. It is, therefore, clear that well-connected directors face time constraints in performing their tasks. Due to the time constraints of well-connected directors and hence less oversight of management, a firm with such directors may experience a number of adverse issues: lower sensitivity of CEO turnover to corporate performance (Fich and Shivdasani, 2006; Devos et al., 2009); higher compensation for CEO (Renneboog and Zhao, 2011); decline in firm performance and value (Cashman et al., 2012; Jiraporn et al., 2008); higher level of financial risks (Tarkovska, 2012); more likelihood to commit financial statement fraud (Beasley, 1996); and higher earnings management (Sarkar et al., 2008).Thus, it is clear that busy directors are detrimental to the monitoring capability of the board on which they sit (Falato et al., 2014; Mendez et al., 2015). This leads to strategic corporate decisions be taken with undue influence of the inside management. Put if differently, corporate transparency, a requirement to facilitate debt contracts (Armstrong et al., 2010), may be adversely affected. 334
4. INTERNATIONAL CONFERENCE FOR YOUNG RESEARCHERS IN ECONOMICS & BUSINESS 2019 ICYREB 2019 Being aware of the possible negative effects of busy boards on corporate performance and disclosure, outside investors disapprove of inside directors having three or more independent directorship appointments (Masulis and Mobbs, 2011) and support the resignation of such busy directors (Bar-Hava et al., 2013).Organizations also offer guidelines on the number of outside directorships that should be held by corporate officers to help avoid “director over-commitment” (e.g. guidelines of National Association of Corporate Directors 1996; Council of Institutional Investors 2014; Financial Reporting Council 2014). Having witnessed a reduction in value, profitability, and financing reporting transparency in firms whose directors are busy, it is likely that creditors will be more cautious when offering loans to such firms. In other words, creditors will be unwilling to provide loans for these firms to prevent possible adverse situations occuring to their money (e.g. when borrowers are in default on the loans or go bankrupt). We, therefore, argue that it is more difficult for firms with busy boards to access external finance. This leads to the following testable hypothesis: Hypothesis 1: Firms with busy independent directors are associated with less external debt. In other words, firms with greater connectedness of independent directors face more limited access to external finance. Independent directors on Indian boards are fewer in number, but much busier than those in the US or the UK and operate under a weaker corporate governance regime. Understanding how outside investors react to such board features, can provide useful implications for corporate governance practices and policies in emerging economies. 2.2. The moderation role of busy independent boards across group and non-group firms in the context of external finance We hypothesize that firms with busy independent boards face more limited access to external finance. However, it is also worth examining whether there is any difference in the potential impact of busy independent board on external finance for group-affiliated firms and non-group firms in India. There are a number of characteristics that may possibly lead to different effects of a busy independent board on the two firm types. First, family business groups are ubiquitous in India (Khanna and Yafeh, 2007). Promoters (i.e. founding family shareholders) in group firms usually have high share ownership (Chakrabarti, Megginson and Yadav, 2008), and hold key positions in the boardroom(Sarkar and Sarkar, 2012). In detail, their average stakes are more than 48% and nearly 50% in BSE 100 and in BSE 500 respectively (Mathew, 2007). They act as chairman or managing director in 95% of top 500 Indian corporate boards (Sarkar and Sarkar, 2012). Thus, promoters in such groups tend to control the board of directors. This indicates that information asymmetry could be higher in business groups than in non-group firms. Second, family firms are prone to unfair business transactions, such as related-party transactions (Cheung, Rau and Stouraitis, 2006). Promoter managers may act in the interests of the controlling family, sometimes at the expense of minority shareholders and/or other stakeholders (Morck and Yeung, 2003). This implies that independent directors encounter more difficulties when performing their duties in family business groups than in non-group firms. Thus, family control may reduce the monitoring effectiveness of independent directors (Jaggi, Leung and Gul, 2009). Hence, more agency problems may arise in such firms. The effectiveness of independent directors in family business group may reduce further due to time constraints, if they simultaneously serve on multiple corporate boards. All of these may lead to a further decline in firm transparency and the trust of outside investors in corporate performance disclosure. Thus, lenders may be unwilling to offer funds to borrowers who belong to family business groups and have busy independent boards. Therefore, we formulate the following hypothesis: 335
5. INTERNATIONAL CONFERENCE FOR YOUNG RESEARCHERS IN ECONOMICS & BUSINESS 2019 ICYREB 2019 Hypothesis 2: Group-affiliated firms with busy independent boards face more limited access to external finance than non-group firms with busy independent boards. 3. Data description 3.1. Sample design To test our hypotheses, we use unbalanced panel data of 445 top firms sourced from the BSE 500 and the CNX 500 in India from 2000 to 2014. Our sample has 5,616 firm-year observations with 3,937 group firm-year observations and 1,679 stand-alone firm-year observations. In 2000, the Securities and Exchange Board of India (SEBI) incorporated Clause 49 into the listing agreement, which requires all listed firms in India to file a corporate governance report with detailed information on board functions. More importantly, this clause strongly emphasizes the role of independent directors in the boardroom. Data for corporate governance and board characteristics are manually collected from corporate governance (CG) reports in Prowess. We extract all directors‟ names, categories (e.g. executive, non- executive, independent, non-independent) and directorships. For director category not tabulated with director name (i.e. the director category scattered across different sections in the CG report), we read each CG report to obtain this specific information. Data on firm characteristics are also collected from Prowess. Ownership and business-group affiliation were sourced from the Prowess IQ database. This database is the latest online version of CMIE and was launched on the 1st of January 2016. As opposed to the previous versions, Prowess IQ is the first to reflect time-series data on ownership classification (i.e. whether a firm is group-affiliated or non- affiliated on a yearly basis) from 1989 onwards. This renders research results relating to group affiliation more reliable. Our sample includes 445 firms, 302 of which are group affiliated and 143 unaffiliated (i.e. stand-alone firms). 3.2. Descriptive statistics Table 1 reports the summary financials for all group and non-group firms in our sample. On average, group firms are larger, more profitable, and older than stand-alone firms. Also, both the leverage and external leverage are higher for the group firms than non-group firms. Following Buchuk et al. (2014), we define leverage as total debt over book assets, and external leverage as financial debt (bank and financial institution debt, bonds, commercial paper) over book assets. This table reports the summary financials of sample firms. Data are for the period 2000-2014. , , * indicate that differences in mean between group and non-group firms are significant at 1%, 5%, and 10%, respectively. a, b, c indicate differences in median between group and non-group firms at 1%, 5%, and 10%, respectively, using Mann-Whitney-Wilcoxon nonparametric test. Table 1: Summary financials of all firms, group firms, and non-group firms Mean St.dev. Median Total assets (in millions of rupees) All 39,273.69 130,809.50 10,390.00 Group 49,468.87 152,950.10 14,452.50a Non-group 15,367.53 39,608.12 5,462.40 EBIT All 3,940.94 13,631.55 1,039.40 Group 4,854.50 15,660.66 1,314.50 a Non-group 1,798.78 6,321.48 605.80 EBIT/total assets (in percent) All 13.22 9.04 11.84 Group 12.62 8.42 11.36 Non-group 14.63 10.23 13.27 a 336
6. INTERNATIONAL CONFERENCE FOR YOUNG RESEARCHERS IN ECONOMICS & BUSINESS 2019 ICYREB 2019 PPE/total assets (in percent) All 27.93 18.17 25.86 Group 28.70 18.23 27.20 a Non-group 26.14 17.90 22.90 Sales growth (in percent) All 22.37 42.22 15.31 Group 21.69 41.89 14.91 Non-group 23.95* 42.96 16.15b Leverage (in percent) All 25.53 19.70 24.53 Group 26.63 19.23 27.07 a Non-group 21.75 20.38 17.45 External leverage (in percent) All 18.29 17.69 15.05 Group 19.27 17.68 16.84 a Non-group 15.99 17.52 10.49 Age (in years) All 34.85 24.15 27.00 Group 36.41 25.20 28.00 a Non-group 31.18 21.06 23.00 Table 2 presents summary statistics for board busyness and other board characteristics. Consistent with Jackling and Johl (2009), we find that an average director in our sample holds about five directorships, while an average director in developed markets only holds around two directorships (e.g. Fich and Shivdasani, 2006; Jiraporn et al., 2008; Cashman et al., 2012). Around 58% of all boards in our sample are classified as busy, whereas, percentage of busy boards of US firms ranges from 16% to 21% (Chakravarty and Rutherford, 2017; Fich and Shivdasani, 2006). With regard to independent directors, the average ratio of independent directors is approximately 51% of the total number of directors, which is lower than the ratio of around 70% of US boards (Bhojraj and Sengupta, 2003; Ashbaugh-Skaife et al., 2006). 62% of all independent boards in the sample are classified as busy. This ratio is even higher for group firms (i.e. 66%). Overall, compared with the US, directors in India have more directorships (i.e. they are busier), and the ratio of busy boards is extremely higher. However, the average ratio of independent directors in the boardroom is lower. Moreover, directors in group firms are better-connected than those in non- group firms. This table reports board busyness measures and other board characteristics for all firms, groups, and non-group firms. , , * indicate that differences in mean between group and non-group firms are significant at 1%, 5%, and 10%, respectively. a, b, c indicate differences in median between group and non-group firms at 1%, 5%, and 10%, respectively, using Mann-Whitney-Wilcoxon nonparametric test. Table 2: Board busyness measures and other board characteristics Panel A. Board busyness measures Mean St.dev. Median Directorships per director All 4.46 2.91 4.13 Group 4.94 2.91 4.58a Non-group 3.34 2.61 2.80 337
7. INTERNATIONAL CONFERENCE FOR YOUNG RESEARCHERS IN ECONOMICS & BUSINESS 2019 ICYREB 2019 Directorships per independent director All 4.62 3.26 4.25 Group 4.72 2.89 4.50a Non-group 4.39 3.99 3.67 Busy board dummy All 0.58 0.49 1 Group 0.67 0.47 1a Non-group 0.37 0.48 0 Busy independent board dummy All 0.62 0.49 1 Group 0.66 0.47 1a Non-group 0.52 0.50 1 Panel B. Other board characteristics Mean St.dev. Median Independent directors (in percent) All 51.28 14.26 50.00 Group 51.63 14.20 50.00 Non-group 50.45 14.39 50.00 Non-executive directors (in percent) All 73.93 13.45 75.00 Group 75.42 13.01 76.47 Non-group 70.43 13.83 71.43 Board size All 9.75 2.95 10.00 Group 10.22 2.98 10.00 Non-group 8.63 2.52 9.00 Institutional ownership (in percent) All 17.00 13.86 15.05 Group 18.75 14.06 16.98 Non-group 12.89 12.43 10.12 4. Methods We test the relation between director busyness and external leverage for a sample of 445 top firms (groups and non-groups) in India, using unbalanced panel data over the period 2000-2014. The frequency of changes in director busyness over the period of research suggests that there is enough time-series variation in the key variable to effectively use panel-data estimation techniques. In Table 3, on average, over the period 2000-2014, 12.09% of the sample firms experienced a change in the busy independent board. By the end of the sample period, this ratio was 15.12%. Following Fich and Shivdasani (2006) and Field et al. (2013), the main measurement of director networks in this analysis is busy independent board (i.e. a board in which 50% or more of the independent directors hold three or more board seats). Additionally, other alternative busyness measures were computed: directorships per independent director (Ferris et al. 2003); dummy variables for directorships per independent director greater than three (IndDirect1) and greater than four (IndDirect2); busy independent board with 60% or more independent directors holding three or more total directorships (busy_ind1). With regard to external leverage, we focus on the ratio of financial debt (bank, institution debt, bonds, commercial paper) over book assets (Buchuk et al. 2014). 338
8. INTERNATIONAL CONFERENCE FOR YOUNG RESEARCHERS IN ECONOMICS & BUSINESS 2019 ICYREB 2019 Table 3: Changes in busy independent boards Year Change in busy independent board (%) 2001 7.86 2002 13.56 2003 12.54 2004 14.70 2005 16.72 2006 13.99 2007 13.20 2008 12.17 2009 11.75 2010 13.24 2011 13.68 2012 13.69 2013 14.87 2014 15.12 2001-2014 12.09 In the analysis, we control for the following variables that impact the external leverage of a firm: EBIT/total assets (Buchuk et al., 2014; Chuluun et al., 2014; Chakravarty and Rutherford, 2017); sales growth (Gopalan, Nanda and Seru, 2007); PPE/total assets (Buchuk et al., 2014); firm size (Buchuk et al., 2014; Chuluun et al., 2014); firm age (Gopalan, Nanda and Seru, 2007); institutional ownership (i.e. ownership percentage of institutional investors), board size (Chakravarty and Rutherford, 2017); and percentage of non-executive directors (Chuluun et al., 2014).We also include year fixed effects in all regressions to control for potential systematic differences in time. All variables are defined in details in the Appendix. To test the hypotheses, we first start with the static fixed effects model and then extend to the dynamic fixed-effects model (the two-step system GMM). 4.1. Fixed effects model We first carry out the Breusch-Pagan Lagrange multiplier (LM) test, and then the Hausman test (details in Table 4). The null hypothesis in the LM test is that variances across entities are zero. Here we reject the null, thus the simple pooled OLS is not appropriate in this study. We use the Hausman test to distinguish between the fixed and random effects models. The null hypothesis of no individual heterogeneity-regressor correlation in the Hausman test is rejected (p-value = 0.0000), thus the fixed effects model below is chosen: yi,t = α + βXi,t + fi+ εit where y is external leverage (Extlev). X includes director busyness (Busyness), ROA, sales growth (SaleGrow), PPE/total assets (Tangi), firm size (Size), firm age (Age), institutional ownership (Insti), Log board size (LogBsize), and percentage of non-executive directors (Nonex). fi is firm heterogeneity (fixed effects) and εit is the error term. 339
9. INTERNATIONAL CONFERENCE FOR YOUNG RESEARCHERS IN ECONOMICS & BUSINESS 2019 ICYREB 2019 Table 4: Breusch-Pagan and Hausman tests Well-connected Breusch and Pagan Lagrangian Hausman test for individual heterogeneity- directors measured by multiplier test for random effects regressor correlation Busy independent board external_assets[id,t] = Xb + u[id] + Test: Ho: difference in coefficients not systematic e[id,t] chi2(9) = (b-B)'[(V_b-V_B)^(-1)](b-B) = 143.68 Test: Var(u) = 0 Prob>chi2 = 0.0000 chibar2(01) = 7548.84 Prob > chibar2 = 0.0000 Within the fixed effects regression model, all t-statistics are based on robust, firm-clustered standard errors. This results from the fact that our data have both heteroscedasticity and first-order autocorrelation (p-value = 0.0000) based on modified Wald test (Greene, 2008) and Wooldridge test (Wooldridge, 2010), respectively. 4.2. Dynamic fixed effects model The static fixed effects approach is robust to the presence of omitted firm-specific variables that would lead to biased estimates in an ordinary least-squares framework. However, it cannot deal with the important source of endogeneity that arises because the relations among a firm‟s observable characteristics are likely to be dynamic. In the context of corporate governance research, current financial leverage may affect future governance choices (such as the ratio of well-connected independent directors in the boardroom, the upper limit of directorships per board member) and these may, in turn, affect future firm financial leverage. To control for the dynamic aspects of the empirical relationship in this research, we may wish to include lagged external leverage as a further explanatory variable. However, with a lagged dependent variable on the right hand side of the external leverage, the use of the fixed effects model may lead to inconsistent estimates as the lagged dependent variable will be correlated with the error term (Wooldridge, 2002; Cameron and Trivedi, 2005). Meanwhile, the generalized method of moments (GMM) provides a framework for estimating an equation with such endogenous variables. To obtain the appropriate system GMM model, we follow Wintoki et al. (2012) to carry out two sets of tests to determine endogenous/exogenous variables, the number of lags of dependent variables, and the instruments used in the model. The first set of tests involve OLS regression of (1) current levels of director busyness measure, firm-specific variables and (2) changes in these levels on past external leverage and historical values of the firm-specific variables. The second is the test of strict exogeneity as recommended by Wooldridge (2002)1 . The results of the first sets of tests show a negative relationship between director busyness and past external leverage. Additionally, most of the firm-specific variables are also significantly associated with past external leverage. In particular, both the current levels and changes in ROA, sales growth, PPE/total assets, firm size, institutional ownership, and percentage of non- executive directors are all significantly related to past external leverage. This reflects that it is not only the director busyness, but almost all the control variables are likely to be endogenous as well. In the second test of strict exogeneity, we examine whether future realizations of director busyness and control variables are unrelated to current external leverage. The results of these tests indicate that in every specification in which they are included, the coefficient estimates for the future values of almost all control variables (i.e. ROA(t+1), SaleGrow(t+1), Tangi(t+1), Size(t+1), Insti(t+1), Nonex(t+1)) are 1 For brevity, we do not report this procedure. Details of these tests are available from the author upon request. 340
10. INTERNATIONAL CONFERENCE FOR YOUNG RESEARCHERS IN ECONOMICS & BUSINESS 2019 ICYREB 2019 significantly different from zero. The F-test of the joint significance of the coefficient estimates of all the future values is also significant (F=4.16; p-value = 0.0000). Overall, our tests suggests that neither the busyness variable nor firm-specific control variables (except Firm Age) are strictly exogenous. To determine the number of lags needed to ensure dynamic completeness, we estimate a regression of current leverage on up to six lags of past external leverage, controlling for other firm-specific characteristics. The results suggest that including two lags is sufficient to capture the dynamic aspect of the network/external leverage relation. Thus, two lags of external leverage are included in the GMM model. The two-step system GMM model After determining endogenous variables, exogenous variables, and the number of lags of the dependent variable, we arrive at the following system GMM model to examine the relationship between external leverage and director busyness: yit = α1 + k1yit-1 + k2yit-2 + βXit +λZit + θDit + ηi +εit Where yit is external leverage (Extlev). Xit includes busy independent board (busy_ind). Zit includes ROA, sales growth (SaleGrow), PPE/total assets (Tangi), firm size (Size), institutional ownership (Insti), Log board size (LogBsize), and percentage of non-executive directors (Nonex). Dit includes firm age (Age) and year dummies. ηi is firm heterogeneity (fixed effects) and εit is the error term. In this GMM model, we apply the collapse option in xtabond2, and limit the number of the instruments used to mitigate the instrument proliferation problem (Roodman, 2009b). Accordingly, the two lags of the external leverage are included. This makes historical external leverage and historical firm- specific characteristics, lagged three periods or more, available for use as instruments. Specifically, variables lagged three and four periods (t-3 and t-4, respectively) are applied as the instruments for all the endogenous variables in the GMM estimates. The choice of instruments from these two periods is based on our empirical analysis that suggests two lags are needed to make the model dynamically complete. Potential endogeneity There is a concern that the busyness of directors and the choice to belong to a group-affiliation may be jointly determined. In India, multiple directorships are quite pervasive in both business groups and non-group firms due to the shortage of industrial leadership with adequate experience to serve on corporate boards. Thus, independent directors serve on different groups and non-group firms simultaneously. Put differently, they are “overboarded” and too busy. Moreover, the corporate sector in this country is dominated by business. The majority of listed firms on the stock exchanges and in the Prowess database are group-affiliated firms. Previous studies on the impact of the busyness of directors on different aspects of corporate performance in India (e.g. Sarkar and Sarkar, 2009; Jackling and Johl, 2009; Sarkar et al., 2008, among others) all focus on a sample including both group and non-group firms. Above three-quarters of which are group-affiliated firms. The issue that the busyness of directors and the choice to belong to a group-affiliation may be jointly determined has not been discussed and addressed in their research. This study includes 445 firms, 302 of which are group affiliated and 143 unaffiliated (i.e. non-group firms). On average, in group firms, each independent director has around 5 directorships. In non-group firms, an independent director also serves on around 5 other boards. Similarly, the ratio of busy independent boards in group and non-group firms is above 50% each (Table 2). Thus, independent directors in the sample are busy regardless of whether they serve on boards of groups or of non-group firms. In a sub-sample that includes only non-group firms, we also obtain the same result as reported for the whole sample, when examining the impact of director busyness on external finance. 341
11. INTERNATIONAL CONFERENCE FOR YOUNG RESEARCHERS IN ECONOMICS & BUSINESS 2019 ICYREB 2019 5. Results This section reports the results of the reaction of outside creditors to the independent directors‟ busyness (Table 5), the moderation role of busy independent board across group and non-group firms in the context of external finance (Table 6), and further robustness checks. 5.1. Independent director busyness and external leverage In Table 5, both the fixed effects and GMM estimates report a negative relation between director busyness and external leverage. However, there is an increase in both the magnitude and the level of significance of the estimated coefficient on the busyness variable when moving from the fixed effects model to the system GMM model. In particular, the coefficient on busy independent board is an insignificantly negative -0.3886 in the fixed effects model (Column 1), but is significant in the system GMM model (β= -3.1872, p-value = 0.05), (Column 2). The rise in the magnitude and the level of significance of the estimated coefficient on this variable in the GMM model may arise from controlling for the dynamic relation between director busyness and past external leverage. Since director busyness is negatively related to past external leverage. Failing to control for this dynamic relation, the fixed effects model is unable to fully reflect the impact of director busyness on external leverage. Overall, busy independent directors appear to have an unfavorable impact on the firm‟s external finance. Hence, we provide evidence to support hypothesis 1. Firms with greater connectedness of independent directors face more limited access to external finance. Our finding is different from that of Chuluun et al. (2014), who document that firms with greater connectedness of directors leads to more external debt for US firms. In column 2, Table 5, we also report the results of the specification tests (i.e. the AR(2) second- order serial correlation tests, the Hansen J test of over-identifying restrictions, and the Difference in Hansen test of exogeneity). In detail, the AR(2) test has a p-value of 0.26 which means that the null hypothesis of no second-order serial correlation cannot be rejected. The Hansen test of over-identification yields a p-value of 0.36, thus we cannot reject the hypothesis that our instruments are valid. The Difference in Hansen test of exogeneity has a p-value of 0.42, which means that the null that instruments used for the equations in levels are exogenous cannot be rejected. Overall, the tests reflect that the instruments are appropriate and well identified in each model. In this table, we report the results from the estimation of the model: yit = α1 + k1yit-1 + k2yit-2 + βXit + λZit + θDit + ηi +εit Where yit is external leverage (Extlev). Xit includes busy independent board (busy_ind). Zit includes ROA, sales growth (SalGrow), PPE/total assets (Tangi), firm size (Size), institutional ownership (Insti), Log board size (LogBsize), percentage of non-executive directors (Nonex). Dit includes firm age (Age) and year dummies. ηi is firm heterogeneity (fixed effects) and εit is the error term. For the fixed effect model, it is assumed that k1=k2=0. All t-statistics are based on robust, firm-clustered standard errors. , , * represent significance at the 1%, 5%, 10% level, respectively. AR(2) are tests for second-order serial correlation in the first-differenced residuals, under the null of no serial correlation, The Hansen test of over-identification is under the null that all instruments are valid. The Diff-in-Hansen test of exogeneity is under the null that instruments used for the equations in levels are exogenous. The instruments used in the GMM estimation are: differenced equations: yit-3, yit-4, Xit-3, Xit-4, Zit-3, Zit-4, ∆Dit; level equations: ∆yit-2, ∆Xit-2, ∆Zit-2, Dit. 342
12. INTERNATIONAL CONFERENCE FOR YOUNG RESEARCHERS IN ECONOMICS & BUSINESS 2019 ICYREB 2019 Table 5: The effect of director busyness (denoted by busy_ind) on external leverage Fixed effects model GMM model (1) (2) Busy_ind -0.3886 -3.1872 (0.5792) (1.7763) ROA -0.3065 -0.0558 (0.0359) (0.0903) SalGrow 0.0041 -0.0184 (0.0045) (0.0286) Tangi 0.1990 0.0098 (0.0344) (0.0434) Size 4.0833 2.3220 (0.6668) (0.8275) Age -0.1703 -0.0194 (0.8653) (0.0159) Insti -0.1306 -0.1235 (0.0359) (0.0548) LogBsize -0.1508 4.7391 (1.6207) (3.1281) Nonex 0.0180 -0.1079 (0.0324) (0.0798) Extlev (t-1) 0.5501 (0.2367) Extlev (t-2) 0.2165 (0.2087) R-square 0.2033 AR (2) test p (value) 0.26 Number of observations 5616 4724 Hansen test of over-identification (p-value) 0.36 Diff-in Hansen tests of exogeneity (p-value) 0.42 Source: Output from STATA 5.2. The moderation role of busy independent board across the group and non-group firms in the context of external finance We hypothesize that group firms with busy independent board will probably face more limited access to external finance than non-group firms with busy boards. Table 6 presents the regression results of the analysis. 343
13. INTERNATIONAL CONFERENCE FOR YOUNG RESEARCHERS IN ECONOMICS & BUSINESS 2019 ICYREB 2019 Model 4 includes interaction between busy independent board and group dummy, enabling analysis of the moderating effect of busy board on the relationship between group-affiliated firms and external finance (Hypothesis 2). The coefficient on this interaction is negative and significant (β=-7.347, t=-2.16, p-value =0.031). This lends support to Hypothesis 2. Group-affiliated firms with busy independent boards face more limited access to external finance than non-group firms with busy independent boards. In this table, we report the results from the estimation of the model: yit = α1 + k1yit-1 + k2yit-2 + βXit + λZit + θDit + ηi +εit Where yit is external leverage (Extlev). Xit includes busy independent board (busy_ind). Zit includes Group, the interaction term busy_ind x Group, ROA, sales growth (SalGrow), PPE/total assets (Tangi), firm size (Size), institutional ownership (Insti), Log board size (LogBsize), percentage of non-executive directors (Nonex). Dit includes firm age (Age) and year dummies. ηi is firm heterogeneity (fixed effects) and εit is the error term. All t-statistics are based on robust, firm-clustered standard errors. , , * represent significance at the 1%, 5%, 10% level, respectively. AR(2) are tests for second-order serial correlation in the first-differenced residuals, under the null of no serial correlation, The Hansen test of over-identification is under the null that all instruments are valid. The Diff-in-Hansen test of exogeneity is under the null that instruments used for the equations in levels are exogenous. The instruments used in GMM estimation are: differenced equations: yit-3, yit-4, xit-3, Xit-4, Zit-3, Zit-4, ∆Dit; level equations: ∆yit-2, ∆Xit-2, ∆Zit-2, Dit. Table 6: The moderation role of busy independent board and external leverage (1) (2) (3) (4) Busy_ind -3.1872* -2.9967* -1.6567 (1.7763) (1.7291) (2.7508) Group -1.1904 -0.0863 6.7851 (6.5956) (6.6402) (6.3825) Busy_ind x Group -7.3470 (3.3966) ROA -0.0558 -0.0059 -0.0394 -0.0504 (0.0903) (0.1027) (0.0971) (0.1020) SalGrow -0.0184 -0.0357 -0.0278 -0.0199 (0.0286) (0.0330) (0.0308) (0.0297) Tangi 0.0098 0.0127 0.0109 0.0183 (0.0434) (0.0466) (0.0437) (0.0454) Size 2.3220 2.2982 2.0334 1.3511 (0.8275) (0.7861) (0.7872) (0.8410) Age -0.0194 -0.0306 -0.0205 -0.0188 (0.0159) (0.0145) (0.0153) (0.0166) Insti -0.1235 -0.1380 -0.1102 -0.0867 (0.0548) (0.0536) (0.0558) (0.0579) LogBsize 4.7391 6.3686* 4.3100 3.5422 (3.1281) (3.3938) (3.5775) (3.5920) 344
14. INTERNATIONAL CONFERENCE FOR YOUNG RESEARCHERS IN ECONOMICS & BUSINESS 2019 ICYREB 2019 Nonex -0.1079 -0.0850 -0.0861 -0.1162 (0.0798) (0.0784) (0.0807) (0.0824) Extlev (t-1) 0.5501 0.7611 0.6974 0.7265 (0.2367) (0.2307) (0.2220) (0.2360) Extlev (t-2) 0.2165 0.0272 0.0842 0.0637 (0.2087) (0.2073) (0.1994) (0.2093) Number of observations 4724 4724 4724 4724 AR (2) test p (value) 0.174 0.714 0.489 0.56 Hansen test of over-identification (p-value) 0.361 0.204 0.280 0.281 Diff-in Hansen tests of exogeneity (p-value) 0.423 0.307 0.263 0.202 Source: Output from STATA The results reported in Tables 5-6 survive extensive robustness checks. First, a number of alternative measures of busy independent board are used including directorships per independent director (IndDirec) (Ferris, Jagannathan and Pritchard, 2003); dummy variables for directorships per independent director greater than three (IndDirect1) and greater than four (IndDirect2); busy independent board with 60% or more independent directors hold three or more total directorships (busy_ind1). Second, one lag of the dependent variable is used in the GMM model instead of the current two lags. 2 6. Discussion and conclusions In this study, we examine the relation between independent director busyness and corporate external leverage in a panel of 445 top Indian firms from 2000 to 2014. Using alternative measures of director busyness and the two-step system GMM model, the study shows a negative association between busy independent boards and firms‟ external finance. The study also reveals that, compared to non-group firms with busy independent boards, group firms with such boards face more limited access to external finance. The findings in our study have both theoretical and practical implications. With regard to theoretical implications, our study emphasizes the importance of good corporate governance in corporate financing in emerging markets where exist a high level of information asymmetry and Type II- Agency problems. Accordingly, for firms with higher information asymmetry, the marginal impact of board capital (such as board independence, board network) on external finance is likely to be greater (Botosan, 1997; Butler, 2008; Mansi et al., 2011). Not limited to the lending relationship, these findings also indicate that improved governance of business groups may be needed to ensure that management is doing what is best for shareholders and that minority shareholders‟ rights are protected. With regard to methods of research, our study takes into account an important source of endogeneity that arises because the relations among a firm‟s observable characteristics are likely to be dynamic. Specifically, in the context of corporate governance, current firm external leverage will affect future governance choices and these may, in turn, affect future firm leverage. Regarding practical implications, through the negative association between a busy independent board and external finance, it seems that outside investors do pay attention to independent directors and put their trust in this type of director when evaluating the likelihood of default of a borrower. Therefore, further enhancement in the roles of independent directors in corporate strategic activities should be considered. To do this, Indian firms, first, should follow appropriate procedures in the nomination process for this type of director. Second, they should create more room for independent 2 Details of these tests are available from the author upon request. 345
15. INTERNATIONAL CONFERENCE FOR YOUNG RESEARCHERS IN ECONOMICS & BUSINESS 2019 ICYREB 2019 directors to actively participate in firm strategic activities. According to the review of corporate governance practices by FICCI and Thornton (2009), the most reputed accountancy firm in this country, 59% of the respondent companies think that the involvement of independent directors in the annual planning and strategy development was moderate, while 13% agreed that the involvement was minimal. In addition, Indian firms should limit the number of busy independent directors in the boardroom, because under the lens of outside investors in this study, it seems that the costs of a „too-busy‟ independent board far outweigh its benefits. Policymakers should re-examine the appropriate upper limit of directorships per independent director so that this type of director can devote enough time and effort to corporate performance and transparency as expected. The abovementioned implications regarding independent directors in Indian firms may also be applied to firms in other emerging markets. Given their weak shareholder rights, and low corporate transparency (Sarkar and Sarkar, 2012), independent directors in such markets may become a powerful internal mechanism that outside investors can rely on to protect their rights. Like Indian firms, companies in other emerging markets should re-examine whether they have paid proper attention to this type of director. Appendix: Variable definitions Variable names Description Source Extlev (External leverage) Financial debt over book assets Prowess, calculations Busy_ind Boards coded with a one if 50% or more independent Prowess, calculations directors hold three or more total directorships Busy_ind1 Boards coded with a one if 60% or more independent Prowess, calculations directors hold three or more total directorships IndDirec Average number of directorships per independent Prowess, calculations director IndDirec1 Dummy variable that takes a value of 1 if directorships Prowess, calculations per independent director greater than three IndDirec2 Dummy variable that takes a value of 1 if directorships Prowess, calculations per independent director greater than four ROA (EBITDA/total assets ) Earnings before interest, taxes, depreciation and Prowess, calculations amortization divided by the book value of total assets Tangi (PPE/total assets) Ratio of book value of net property plant and equipment Prowess, calculations to the book value of total assets Size (Firm size) Natural logarithm of total assets. Prowess, calculation Age (Firm age) Number of years since incorporation Prowess IQ, calculation Insti (Institutional ownership) Ownership percentage of institutional investors Prowess LogBsize (Log board size) Number of directors on a board. Prowess, Capital IQ, calculation Nonex Percentage of non-executive directors on a board Prowess, Capital IQ, calculation REFERENCES [1] Ahmed, A. S. and Duellman, S. (2007) "Accounting conservatism and board of director characteristics: An empirical analysis", Journal of Accounting and Economics, 43(2–3), pp. 411–437. [2] Armstrong, C. S., Core, J. E. and Guay, W. R. (2014) "Do independent directors cause improvements in firm transparency?", Journal of Financial Economics, 113(3), pp. 383–403. 346
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