Abstract
CHINA JOURNAL OF ACCOUNTING STUDIES 2020, VOL. 8, NO. 4, 495–527 https://doi.org/10.1080/21697213.2021.1966175 ARTICLE The globalised board of directors and corporate environmental performance: evidence from China a b a c Xingqiang Du , Jingwei Yin , Ying Zhang and Yingjie Du Center for Accounting Studies and Accounting Department, Xiamen University, Xiamen, Fujian, China; b c Business School, Central South University, Changsha, Hunan, China; School of Management, Shanghai University, Shanghai, China ABSTRACT KEYWORDS The globalised board of This study examines the association between the globalised board directors; regional green of directors and corporate environmental performance, and then development; board investigates the moderating effect of regional green development governance; the supervisory on the above association. Using a sample from the Chinese stock and advisory functions; market during the period of 2008–2016, the findings reveal that the corporate environmental globalised board of directors is significantly positively associated performance with corporate environmental performance, suggesting that the globalised board of directors can play an important role in strength- ening the moral and strategic motivations of corporate environ- mental responsibility, and enhance corporate environmental performance. Further, regional green development attenuates the positive relation between the globalised board of directors and corporate environmental performance. Above findings are robust to a variety of sensitivity tests and our main conclusions are still valid after controlling for the potential endogeneity between the globalised board of directors and corporate environmental perfor- mance. Interestingly, additional tests reveal that the positive effect of foreign directors on corporate environmental performance is more pronounced for those from the countries (regions) with shorter time zone difference, stronger investor protection and bet- ter performance in environmental responsibilities. 1. Introduction In the last four decades, it has been gradually recognised that contemporary enterprises should actively undertake environmental responsibilities and should not pursue eco- nomic benefits at the cost of environmental deterioration (Campbell, 2007; Maignan & Ralston, 2002; Mallin et al., 2013; Vidaver-Cohen & Simcic Brønn, 2008; Walls et al., 2012). In China, the second-largest economy in the world, environmental problems have become more and more prominent along with its rapid economic growth. In response to worsening environment, the Chinese government had promulgated a set of environmen- tal laws (regulations) to severely punish environmental violations and strengthening CONTACT Jingwei Yin 1327861655@qq.com, yinjw@csu.edu.cn Business School, Central South University, No. 932, Lushan South Road, Changsha, Hunan 410083, China; Xingqiang Du xqdu@xmu.edu.cn Center for Accounting Studies and Accounting Department, Xiamen University, No. 422, Siming South Road, Xiamen, Fujian 361005, China Paper accepted by Kangtao Ye. See the website: https://www.nytimes.com/2007/08/26/world/asia/26china.html. © 2021 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/ licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 496 X. DU ET AL. environmental protection. However, it seems that laws (regulations) had not achieved the desired effects (Du et al., 2014). For example, Yunnan Luoping Zinc & Electricity Co., Ltd. (002114.SZ) – a firm whose stock was listed in the Shenzhen stock exchange – was detected that its heavy metal-containing waste residue seriously contaminated the Zhujiang River as early as 2016, but it just treated the rectification requirements from the Ministry of Ecology and Environment in a passive and perfunctory way. As a result, the heavy metal-containing waste residue had not been cleaned up by the end of 2018. In this regard, board monitoring as a micro-level mechanism is also expected to urge enterprises to improve their environmental performance (Du et al., 2014). In recent years, along with the economic globalisation, multi-national firms have led the trend of establishing the globalised board of directors (Staples, 2007). In China, due to both the deficiency of governance mechanisms and the shortage of superior manage- ment practices, more and more Chinese listed firms have an increasing demand for foreign directors (Du et al., 2017; Youssef, 2003). Given that environmental responsibility embodies business ethics (the moral motivation) and strategic choice (the strategic motivation) of decision-makers (Jose & Lee, 2007), it is suggested that corporate boards can exert influence on corporate environmental performance through its supervisory and advisory roles (Kassinis & Vafeas, 2002; Mallin et al., 2013; Post et al., 2011; Shaukat et al., 2016; Walls et al., 2012). However, specific to environmental issues, not all directors are of equal importance for improving environmental performance. Prior literature has validated that, compared to their counterparts, women directors (Post et al., 2011), outside directors (Kassinis & Vafeas, 2002), and financial experts serving on audit committee (Shaukat et al., 2016) are more likely to concern about corporate environmental responsibility. Regarding foreign directors on the globalised board, Du (2018) finds that they can effectively monitor corporate financial decisions. Nevertheless, it is still a pending problem about whether the globalised board of directors (foreign directors) can improve board effec - tiveness about environmental issues and motivate Chinese listed firms to carry out environmental responsibilities better. In response, this study examines whether the globalised board of directors can enhance corporate environmental performance. In addition, we further investigate the moderating effect of regional green develop- ment on the relation between the globalised board of directors and corporate environ- mental performance. Regional green development reflects macro-level social atmosphere towards environmental conservation, and thus environmental performance for firms located in provinces with higher level of green development is predicted to be better. Furthermore, drawing on Williamson (2000)’s institutional analysis framework, regional green development as a social atmosphere (an informal institution), is predicted to moderate (weaken or reinforce) the positive effect of the globalised board of directors as a formal (internal governance mechanism) on corporate environmental performance. Using a sample from the Chinese stock market during the period of 2008–2016, we examine the influence of the globalised board of directors on corporate environmental performance, and further investigate the moderating effect of regional green develop- ment on the above effect. In brief, the findings reveal several aspects: First, the globalised board of directors is significantly positively related with corporate environmental perfor- mance, suggesting that the globalised board of directors can play an important role in See the website: http://finance.sina.com.cn/chanjing/gsnews/2018-06-21/doc-ihefphqk8116553.shtml . CHINA JOURNAL OF ACCOUNTING STUDIES 497 strengthening the moral and strategic motivations of environmental responsibility, and thus enhance corporate environmental performance. Second, regional green develop- ment weakens the positive relation between the globalised board of directors and environmental performance. Third, above findings are robust to a variety of sensitivity tests and still stand after controlling for the potential endogeneity. Lastly, the positive effect of foreign directors on corporate environmental performance only holds for those from the countries (regions) with shorter time zone difference, stronger investor protec- tion and better performance in environmental responsibilities. This study makes several contributions as below. First, to our knowledge and literature in hand, this study is the first to examine whether the globalised board of directors (board nationality diversity, foreign directors) affects corporate environmental performance. Prior literature has validated the effects of (internal and external) governance mechanisms on corporate environmental responsibility (Mallin et al., 2013; Post et al., 2011; Shaukat et al., 2016; Walls et al., 2012). However, previous studies have provided little evidence about how the globalised board of directors affects corporate environmental performance. In this regard, our study adds to prior literature by documenting the positive role of the globalised board of directors in upgrading environmental performance. More importantly, corporate social responsibility (CSR) can be divided into CSR- strength (e.g. philanthropy) and CSR-weakness (e.g. environmental wrongdoings). Contemporary enterprises have inconsistent attitudes towards different CSR dimensions (Chen et al., 2008; Du, 2015; Zyglidopoulos et al., 2012). Chen et al. (2008) find that firms are more likely to engage in philanthropy along with pollution, low-quality products or employee discrimination. Du (2015) reveals that, compared to their counterparts, envir- onmentally unfriendly firms usually exhibit higher level of corporate philanthropy. As such, it is still necessary for researchers to identify the influence of the globalised board of directors on different CSR dimensions. Second, prior literature has validated that the globalised board of directors can facil- itate cross-border acquisitions, promote operational efficiency, and add to firm value (Masulis et al., 2012; Oxelheim & Randøy, 2003). As for the supervisory function, Masulis et al. (2012) find that the globalised board of directors is less effective in supervising managers. Du et al. (2017) argue that the U.S. context limits the generalisation of Masulis et al. (2012)’s findings, and further report a positive relation between the globalised board of directors and earnings quality in the Chinese context. Specifically, the globalised board of directors not only transfers superior environmental practices to managers (i.e. to advise), but also mitigates managers from unethical environmental wrongdoings (i.e. to supervise). Therefore, echoing Du et al. (2017), our study lends supplement to prior literature about the supervising benefits of the globalised board of directors. Third, we firstly address whether the influence of the globalised board of directors on corporate behaviour is asymmetric across different regions in China. Specifically, the level of green development at the province level attenuates the positive relation between the globalised board of directors and environmental performance. Thus, this study contri- butes to previous literature about how the globalised board of directors affects corporate behaviours. Lastly but not least, this study identifies three important channels for the globalised board of directors to affect corporate environmental performance. First, time zone differ - ence between foreign directors’ original countries (regions) and China hinders them from 498 X. DU ET AL. improving corporate environmental performance, implying that geographic distance results in extra costs for foreign directors to fulfill their duties. Second, foreign directors from countries (regions) with relatively weak investor protection weaken the positive effect of the globalised board of directors on corporate environmental performance. Third, foreign directors from countries (regions) with better performance exert a greater effect. Above findings can help researchers, managers and regulators to understand how foreign directors from different countries (regions) asymmetrically affect corporate behaviours. The second section develops hypotheses. The third section illustrates variables, model, the sample and data source. The fourth section reports the results of our main tests and robustness checks. The fifth section addresses the endogeneity issue and conducts additional analyses. The final section summarises conclusions, develops managerial impli- cations, and discusses limitations and future research. 2. Literature review, theory and research hypotheses 2.1. Motivations for undertaking environmental responsibilities Prior literature has documented the moral and strategic motivations of corporate envir- onmental responsibility (Babiak & Trendafilova, 2011; Campbell, 2007; Jose & Lee, 2007; Maignan & Ralston, 2002; Vidaver-Cohen & Simcic Brønn, 2008). As Jose and Lee (2007) argue, a firm’s main objective of engaging in environmental protection is related to competitive advantages, the long-term survival and stakeholder responsiveness, rather than laws (regulations). 2/3 of respondents (managers/executives from 113 countries/ regions) consider CSR as a critical mean to gain competitive advantages and achieve sustainable development (Kiron et al., 2012). Beyond maximising profit and shareholder value, corporate social responsibility (CSR) further requires large firms to take care of their stakeholders’ benefits. In this regard, firms (managers) with higher level of business ethics are more likely to be concerned about their stakeholders and thus fulfill environmental responsibilities (Du et al., 2014). Maignan and Ralston (2002) conduct a cross-country study, finding that CSR is mainly driven by the moral motivation and CSR can be considered as the expression of organisational culture and value. Similarly, as an important CSR component, corporate environmental respon- sibility is altruistic or a virtue behaviour in essence. Corporate environmental responsibility is originally for the sake of stakeholders, but it can ultimately benefit shareholders (Babiak & Trendafilova, 2011; Maignan & Ralston, 2002). Given that a considerable part of customers value environmentally responsible activities, better environmental performance is associated with the enhanced reputation, higher level of customer loyalty, and more customers (McWilliams & Siegel, 2000; Porter & Kramer, 2011). Prior literature finds that socially responsible and environment-friendly firms are much easier to get access to financing (Benlemlih, 2017; Goss & Roberts, 2011), have higher credit ranking (Attig et al., 2013), and are less likely to be issued modified audit opinions (Du et al., 2018). Thus, firms should attach special importance to corporate environmental responsibility. Given that environmental performance embodies business ethics and strategic choice, governance mechanisms have considerable impacts on corporate environmental perfor- mance (Mallin et al., 2013; Post et al., 2011; Shaukat et al., 2016; Walls et al., 2012). The CHINA JOURNAL OF ACCOUNTING STUDIES 499 board of directors is a key component of governance mechanisms (Jensen & Meckling, 1976). Kassinis and Vafeas (2002) find that board size and the fraction of directors in industrial firms are positively related to environmental litigation, while the number of directorships held by outside directors is significantly negatively related with environ- mental litigation. In addition, Post et al. (2011) reveal that firms with at least three women directors exhibit better environmental performance. Shaukat et al. (2016) validate that financial experts on audit committee have a positive effect on environmental perfor- mance. In a nutshell, prior literature has suggested that board attributes could exert influence on environmental performance. 2.2. The globalised board of directors and corporate environmental performance The globalised board of directors (i.e. board nationality diversity) has attracted a great deal of attention of scholars in the field of accounting and finance. In emerging markets such as China, due to the incomplete governance mechanism and the lack of superior management practices, domestic firms applaud experts from developed countries (regions) (Du et al., 2017; Youssef, 2003). The globalised board of directors, which consists of experts with different cultural and institutional backgrounds, can lead to the brain gains, benefit local firms’ strategically decision-making, and contribute to competitive advantages (Giannetti et al., 2015). Masulis et al. (2012) find that foreign directors are familiar with international markets and the globalised board of directors improves cross- border acquisition performance. In addition to the advisory role, Du et al. (2017) find that the globalised board of directors also mitigates financial misconducts. In general, foreign directors are both valuable advisors and relatively good monitors for domestic firms, especially in emerging markets such as China (Oxelheim & Randøy, 2003). As such, the influence of the globalised board of directors on corporate environmental performance mainly relies on its advisory and supervisory functions. 2.3. The supervisory function of the globalised board of directors Given that immature business ethics are problematic in emerging markets like China (Du et al., 2014), in most cases, domestic directors have weaker environmental consciousness and moral motivation to supervise environmental wrongdoers. Besides, environmental laws and regulations are somewhat on paper, which hinders enterprises from fulfiling environmental responsibilities (Du et al., 2016; Zhang et al., 2018). As a result, as Du et al. (2016) note, it is quite prevalent for firms to pursue economic benefits at the cost of environmental pollution. The supervisory function of the globalised board of directors is particularly important in such a situation. The supervisory effectiveness of corporate boards depends on the willingness and the ability to do so (Du et al., 2017; Masulis et al., 2012). Specific to environmental issues, the globalised board of directors can enhance the supervisory function for two reasons: First, foreign directors are more independent from managers. Unlike domestic directors, for- eign directors are less socially connected to managers, and thus have higher level of independence (Wong & Chan, 1999). Moreover, the relatively mature labour markets in developed countries (regions) motivate foreign directors to hold more concerns about their reputation and career prospect (Du et al., 2017). As such, the globalised board of 500 X. DU ET AL. directors advocates corporate responsiveness to environmental issues from stakeholders (Ibrahim et al., 2003). To sum up, both being out of managers’ social network and reputation concerns make foreign directors less likely to be captured by managers, which guarantees higher extent of independence of the globalised board of directors to a considerable extent. Second, the globalised board of directors has the moral motivation (higher level of business ethics and environmental consciousness) to diligently supervise managers over environmental conservation (Khanna, 2008; Zhang et al., 2018). The attitude towards environmental protection is rooted in cultural and institutional backgrounds (Campbell, 2007; Waldman et al., 2006). Driven by the government, non-government organisations and the public, firms in developed countries (regions) have recognised environmental protection as a social norm or macro-level social culture, and further these firms have incorporated environmental conservation into micro-level corporate culture (Berry & Rondinelli, 1998). As a result, foreign directors from developed countries (regions) are more likely to identify with the value of environmental responsibility (performance), and further have a stronger incentive to curb managers from environmental wrongdoings. 2.4. The advisory function of the globalised board of directors Environmental responsibility can be used as a strategy to increase firm value (the strategic motivation; Jose & Lee, 2007; Kiron et al., 2012). Since 2008, the Shenzhen and Shanghai Stock Exchanges have required listed firms to issue CSR report, in which environmental responsibility is a key component. Moreover, since 2011, the South Weekend, an influential newspaper in China, has turned its eye on corporate environmental responsibility and announced a yearly list of environmental wrongdoers. Along with corporate internatio- nalisation (globalisation), it is increasingly important for firms to obtain legitimacy by fulfiling environmental responsibilities. In this regard, Chinese listed firms have a long way to go. Thus, the globalised board of directors can play its advisory role to urge Chinese listed firms to establish the linkage between environmental responsibilities and the long- term value and be familiar with environmental management practices (Du et al., 2014). With regard to the advisory function, the globalised board of directors is beneficial to promote the strategic motivation of corporate environmental performance: First, most foreign directors have well recognised that corporate environmental responsibility is crucial for firms to accumulate competitive advantages and ensure long-term survival (Johnson & Greening, 1999). Zhang et al. (2018) find that the percentage of directors with overseas experience is significantly positively related with CSR engagement, suggesting that the globalised board of directors is more likely to urge firms to behave in socially responsible ways. Consequently, the globalised board of directors can advise Chinese firms (managers) to strategically engage in environmental protection. Second, as foreign directors have extensive work experience in the international market, they have accumulated the knowledge about how to strategically deal with environmental issues and properly handle the equilibrium between risks and benefits. To engage in environmental-friendly activities requires great investment, accompanies with high risks, and needs a comparatively long return cycle (Hart & Ahuja, 1996). In this regard, foreign directors on the globalised board of directors, who have superior environ- mental practices, can provide Chinese enterprises with important suggestions on the CHINA JOURNAL OF ACCOUNTING STUDIES 501 adoption and implementation of environmental strategies. According to Giannetti et al. (2015), Iliev and Roth (2018), and Zhang et al. (2018), the globalised board of directors plays a crucial role in the cross-country transfer of superior environmental practices. Based on the aforementioned discussions, domestic firms (managers) can benefit from the globalised board of directors on environmental strategies, and further exhibit better environmental performance. To sum up, based on the supervisory and advisory functions, the globalised board of directors is expected to enhance both the moral and strategic motivations for enterprises (managers) to improve environmental performance. Thus, Hypothesis 1 (H1) is formulated in an alternative as below: H1: Ceteris paribus, the globalised board of directors is positively associated with corporate environmental performance. 2.5. The moderating effect of regional green development In China, environmental conservation consciousness across different provinces varies greatly (The China National Bureau of Statistics, 2015). Regional green development as a multi-dimensional concept, proxied by green development index at the province level, embodies sustainable development and consists of resource utilisation index, environ- mental governance index, environmental quality index, ecological protection index, growth quality index and green life index. To obtain political promotion, local officials pay close attention to environmental policies. Against this context, regional green development has cultivated macro-level social atmosphere towards environmental friendliness and sustainable development, which motivate enterprises within different jurisdictions to undertake environmental responsibilities. Thus, regional green development positively affects environmental per- formance. Next, we further investigate the moderating effect of regional green develop- ment. Referring to Williamson (2000), regional green development – which embodies macro-level social atmosphere towards environmental conservation – should be posi- tioned at the first level in the social institutions. However, the globalised board of directors can be classified as an element at the third level in the social institutions. Different social institutions interactively affect corporate decisions and moderate (attenu- ate or reinforce each other (e.g. Du et al., 2014). On the one hand, social atmosphere about green development means the value identity towards environmental responsibility (Campbell, 2007; Waldman et al., 2006), and thus higher level of provincial green development provides enterprises in the province with stronger moral incentives to fulfill environmental responsibilities and have better environmental performance. Against this context, the positive effect of the Green development index at the province level can be obtained from the ‘Green Development Index System’ issued by the National Development and Reform Commission, the National Bureau of Statistics, the Ministry of Ecology and Environment and the Organization Department of Central Committee of the CPC. Williamson (2000)’s institution analysis framework includes four levels: (1) informal institutions (e.g. customs, traditions, norms, religions); (2) institutional environment (e.g. polity, judiciary, bureaucracy); (3) governance mechanisms; and (4) resource allocation and employment. 502 X. DU ET AL. globalised board of directors on corporate environmental performance (the supervisory function) will be weakened. On the other hand, along with the green development at the province level, the demand for superior environmental practices increases accordingly. In this regard, the globalised board of directors can play the advisory role in the cross- country transfer of superior environmental practices (Giannetti et al., 2015; Iliev & Roth, 2018). As a result, the globalised board of directors is prone to exert greater influence on corporate environmental performance by its advisory function. That is, regional green development reinforces the positive relation between the globalised board of directors and corporate environmental performance. Thus, we formulate two competitive hypotheses – Hypothesis 2a (H2a) and Hypothesis 2b (H2b): H2a (H2b): Ceteris paribus, regional green development weakens (reinforces) the positive effect of the globalised board of directors on corporate environmental performance. 3. Research design 3.1. Model specification for hypothesis 1 (H1) To test H1, we use the Tobit regression Model (1) to link environmental performance index (EPI) to the globalised board of directors (GBD), and other control variables: EPI ¼ α þ α GBDþ α Controlsþ Industry Indicatorsþ Year Indicatorsþ ε Model(1) 0 1 2 20 In Model (1), the dependent variable is EPI (environmental performance index). Extending extant studies (Al-Tuwaijri et al., 2004; King & Lenox, 2001; Patten, 1992; Wiseman, 1982), Clarkson et al. (2008) focus on purely discretionary environmental dis- closure and develop a content analysis index on the basis of the Global Reporting Initiative (GRI) sustainability reporting guidelines. Compared to prior literature, Clarkson et al. (2008) provide an optimised index for environmental performance, which has highly positive correlation with the actual environmental performance. Up to now, Clarkson et al. (2008)’s method has been widely accepted (e.g. Du et al., 2014; Rahman & Post, 2012), and thus we refer to Clarkson et al. (2008) to measure corporate environmental performance. Specifically, environmental inforamtion disclosure is divided into ten com- ponents (GRI, 2006). Based on the scoring method advocated by Clarkson et al. (2008), the scoring scale of each component is from 0 to 6. Accordingly, we score each component separately, and then aggregate the scores to get environmental performance index (EPI). In Model (1), the independent variable is the globalised board of directors with a label of GBD. Specifically, GBD is an indicator variable, which equals 1 if at least one foreigner serves in the boardroom and 0 otherwise (Du et al., 2017). In Model (1), if the coefficient on GBD (i.e. α ) is significantly positive, then Hypothesis 1 (H1) is supported. It is difficult to measure corporate environmental performance (Clarkson et al., 2008; Ilinitch et al., 1998). Based on Environmental Protection Agency’s TRI database, some scholars use total toxic waste released by each firm to capture environmental performance (King & Lenox, 2001). Please note that, due to the absence of firm-level pollution discharge data in most contexts, corporate environmental information disclosure has been viewed as an alternative proxy for environmental performance (Al-Tuwaijri et al., 2004; Patten, 1992; Wiseman, 1982). CHINA JOURNAL OF ACCOUNTING STUDIES 503 To isolate the incremental effect of the globalised board of directors on corporate environmental performance, a set of control variables are included into Model (1). First, to address the effect of internal governance mechanisms on environmental performance (Nie et al., 2018; Walls et al., 2012), we include BLOCK, MAN_SHR, QFII_SHR, DUAL, BOARD and INDR into Model (1). BLOCK is the ratio of shares owned by the largest shareholder to the total shares. MAN_SHR is the ratio of shares owned by managers to the total common shares. QFII_SHR is the ratio of shares owned by qualified foreign institutional investors to the total shares. DUAL is an indicator, equalling 1 if CEO chairs the board of directors and 0 otherwise. BOARD is the natural logarithm of the total number of directors. INDR is the proportion of independent directors. Second, we also incorporate two variables of external governance mechanisms into Model (1). ANALYST is the natural logarithm of 1 plus the number of analysts that follow the firm. BIG10 is an indicator variable that equals 1 if the firm is audited by a Big 10 auditor and 0 otherwise. Third, based on prior literature (Clarkson et al., 2008; Walls et al., 2012), several firm- specific characteristics are included in Model (1). SIZE is the natural logarithm of market value at the end of the year. LEV is the amount of interest-bearing liabilities (i.e. long-term and short-term loans, bonds, and notes payable) divided by total assets. ROA is calculated as the net income divided by average assets. TOBIN’Q denotes a firm’s growth opportunity. Fourth, referring to Clarkson et al. (2008) and Du et al. (2014), we consider other factors of FIN, VOLAT, and CAP_INV. FIN is the ratio of equity and debt re-financed in the year to total assets at the beginning of the year. VOLAT stands for information asymmetry, calculated as the standard deviation of market adjusted weekly stock return. CAP_INV is the investment on fixed assets, intangible assets and other long-term assets divided by sales revenues. Fifth, the length of time as public firms may lead to the difference in environmental strategies (Du et al., 2014). Thus, LISTAGE, measured as the number of years since IPO, is included in Model (1). In addition, we include an indicator of SOE in Model (1). SOE is an indicator variable that equals 1 if the firm is a state-owned enterprise and 0 otherwise. Furthermore, GDP_PC and MKT are included in Model (1). GDP_PC is the GDP per capita at the province level (in ten thousand RMB). MKT is marketisation index at the province level (Wang et al., 2018). Finally, to control for industry and time fixed effects, we include a set of dummy variables about industry and year dummies in Model (1). 3.2. Model specification for hypothesis 2a (H2a) and hypothesis 2b (H2b) To test H2a (H2b), we employ Model (2) to link environmental performance index (EPI) with the globalised board of directors (GBD), regional green development (RGD), the interactive item of GBD×RGD and other control variables: EPI ¼ β þ β GBDþ β RGDþ β GBD� RGDþ β Controlsþ Industry Indicators 0 1 2 3 4 22 þ Year Indicatorsþ ε Model(2) 504 X. DU ET AL. In Model (2), EPI (environmental performance index) is the dependent variable and GBD (an indicator for the globalised board of directors) is the independent variable. Moreover, the moderating variable is regional green development at the province level (RGD). In Model (2), a significantly negative (positive) coefficient on GBD×RGD (β ) is consistent with H2a (H2b). 3.3. Identification of sample The sample for our empirical analyses is based on all Chinese listed firms between 2008 and 2016. We start from 2008 for the reason that most Chinese listed firms had not disclosed their environmental information until 2008. This initial sample consists of 21,348 firm-year observations. Then, we conduct the following selection procedures: (1) we drop 364 observations in the financial industry; (2) we delete 302 observations with negative net assets; (3) we drop 3,969 observations with missing data needed in our empirical analyses. Above procedures leave us with a final research sample of 16,713 firm-year observations, representing 2,770 unique firms. For sample distribution by year and industry, the cluster- ing phenomenon just exists in a few industries and is not very serious in our sample. 3.4. Data source Data sources are reported as below: (1) We hand-collect data on environmental perfor- mance index from annual reports, social responsibility reports and corporate websites. Specifically, we analyse the original contents, conduct the scoring procedure based on the GRI sustainability reporting guidelines, and then calculate environmental performance index (Clarkson et al., 2008; Du et al., 2014). (2) We identify the original country (region) of each director and hand-collect data on the globalised board of directors by directors’ curriculum vitae in annual reports. (3) The data on regional green development are obtained from the ‘China National Bureau of Statistics’ (www.stats.gov.cn/tjsj/zxfb). (4) The data on BIG10 are obtained from the CICPA’s official website (www.cicpa.org.cn). (5) The data on GDP_PC are obtained from the China Statistical Yearbook. (6) The data on MKT are obtained from Wang et al. (2018); (7) Other control variables are obtained from CSMAR database. 4. Empirical results 4.1. Descriptive statistics and t-/z-tests Section A of Table 1 reports descriptive statistics of all variables used in our main tests. The mean value of EPI is 0.730, revealing the average value of environmental performance index for sample firms. GBD has a mean value of 0.078, revealing that 7.8% of sample firms have established the globalised board of directors. The mean value of RGD is 80.282, indicating the average value of regional green development at the province level. Results for descrip- tive statistics of control variables are qualitatively similar to extant studies (e.g. Du, 2018). In Section B of Table 1, the full sample is split into two subsamples: firms with the globalised board of directors (GBD = 1; the GBD subsample) and firms without the globalised board of directors (GBD = 0; the non-GBD subsample). And then, t-tests CHINA JOURNAL OF ACCOUNTING STUDIES 505 Table 1. Descriptive statistics and t-/z-tests. Section A: Descriptive statistics Section B: t-/z-tests about the differences between firms with GBD and firms without GBD GBD = 1 (N = 1,303) GBD = 0 (N = 15,410) Variables N Mean S. D. Min Q1 Median Q3 Max Mean Median S. D. Mean Median S. D. t-tests z-tests EPI 16,713 0.730 2.161 0.000 0.000 0.000 0.000 24.000 1.622 0.000 3.978 0.654 0.000 1.912 15.64*** 7.09*** GBD 16,713 0.078 0.268 0.000 0.000 0.000 0.000 1.000 RGD 16,713 80.282 2.061 75.200 79.110 79.600 81.830 83.710 80.371 79.600 2.016 80.274 79.600 2.065 1.63 1.92* BLOCK 16,713 0.356 0.151 0.085 0.235 0.336 0.461 0.757 0.383 0.366 0.155 0.354 0.335 0.150 6.64*** 6.29*** MAN_SHR 16,713 0.055 0.126 0.000 0.000 0.000 0.022 0.611 0.051 0.000 0.129 0.056 0.000 0.126 −1.38 −1.55 QFII_SHR 16,713 0.001 0.003 0.000 0.000 0.000 0.000 0.022 0.001 0.000 0.004 0.001 0.000 0.003 5.80*** 6.23*** DUAL 16,713 0.232 0.422 0.000 0.000 0.000 0.000 1.000 0.274 0.000 0.446 0.229 0.000 0.420 3.72*** 3.72*** BOARD 16,713 2.156 0.197 1.609 2.079 2.197 2.197 2.708 2.182 2.197 0.196 2.153 2.197 0.197 5.12*** 4.24*** INDR 16,713 0.371 0.053 0.300 0.333 0.333 0.400 0.571 0.373 0.333 0.057 0.371 0.333 0.052 1.51 1.28 ANALYST 16,713 1.567 1.123 0.000 0.693 1.609 2.485 3.689 1.839 1.946 1.082 1.544 1.609 1.124 9.13*** 9.07*** BIG10 16,713 0.523 0.499 0.000 0.000 1.000 1.000 1.000 0.614 1.000 0.487 0.516 1.000 0.500 6.83*** 6.82*** SIZE 16,713 22.603 1.100 20.437 21.840 22.487 23.231 27.067 22.974 22.739 1.373 22.572 22.468 1.068 12.72*** 9.30*** LEV 16,713 0.170 0.145 0.000 0.044 0.143 0.263 0.613 0.159 0.132 0.137 0.170 0.144 0.146 −2.68*** −2.28** ROA 16,713 0.037 0.054 −0.224 0.013 0.034 0.064 0.211 0.046 0.042 0.056 0.037 0.034 0.054 6.18*** 7.15*** TOBIN’Q 16,713 2.716 2.049 0.918 1.443 2.061 3.209 13.994 2.917 2.208 2.262 2.699 2.047 2.029 3.67*** 3.23*** FIN 16,713 0.305 0.338 0.000 0.059 0.226 0.432 2.101 0.296 0.193 0.347 0.306 0.228 0.337 −1.02 −2.40** VOLAT 16,713 0.053 0.022 0.021 0.038 0.048 0.062 0.147 0.054 0.049 0.023 0.053 0.048 0.022 1.32 0.77 CAP_INV 16,713 0.127 0.172 0.000 0.026 0.069 0.155 1.049 0.121 0.075 0.144 0.128 0.068 0.174 −1.26 3.05*** LISTAGE 16,713 10.394 6.256 0.000 5.000 10.000 16.000 26.000 9.286 7.000 6.372 10.487 10.500 6.238 −6.66*** −6.76*** SOE 16,713 0.445 0.497 0.000 0.000 0.000 1.000 1.000 0.355 0.000 0.479 0.453 0.000 0.498 −6.81*** −6.80*** GDP_PC 16,713 5.716 2.506 0.985 3.707 5.410 7.402 11.820 6.429 6.345 2.565 5.656 5.410 2.492 10.72*** 10.23*** MKT 16,713 7.633 1.804 2.940 6.360 7.810 9.296 10.863 8.156 8.370 1.615 7.589 7.780 1.812 10.93*** 10.97*** 506 X. DU ET AL. and z-tests are conducted to analyse whether significant differences between two subsamples exist. As reported, the mean value of environmental performance index (EPI) is 1.622 for GBD firms and 0.654 for non-GBD firms, and the difference is significant at the 1% level (t = 15.64). Similarly, the median value of EPI is also significantly different between two subsamples at the 1% level (z = 7.09). Overall, the GBD subsample has better environmental performance than the non-GBD subsample, consistent with H1. 4.2. Pearson correlation analyses Table 2 presents the correlation coefficients among variables. EPI holds a significantly positive correlation with GBD (0.120 with p < 0.01), indicating that the globalised board of directors enhances corporate environmental performance, lending preliminary support to H1. Moreover, the correlation between EPI and RGD is positive and significant, which motivates our study to address the interactive effect between the globalised board of directors and regional green development on EPI. Specific to control variables, EPI is significantly positively (negatively) correlated with BLOCK, QFII_SHR, BOARD, ANALYST, BIG10, SIZE, LEV, FIN, CAP_INV, LISTAGE, and SOE (MAN_SHR, DUAL, TOBIN’Q, VOLAT, and MKT). Moreover, most correlation coefficients are below 0.30, suggesting that multicollinearity is not very serious in our regression analyses. 4.3. Multivariate tests of hypotheses 1, 2a, and 2b Table 3 tabulates the step-by-step regression results of corporate environmental perfor- mance (EPI) on the globalised board of directors, regional green development and other determinants. All models are significant at the 1% level. Furthermore, from column (1) to 2 2 column (4), Pseudo_R gradually increases and the differences in ‘Pseudo_R ’ between nearby columns are all significant (see Chi -tests in the next-to-last row), implying that the explanatory power increases when GBD, RGD and GBD×RGD are added into the multi- variate regression models one by one. All reported t-statistics are calculated using the Huber-white procedure (White, 1980). Column (1) of Table 3 addresses the effects of all control variables on EPI. As shown in Column (1), the coefficients on blockholder ownership (BLOCK), board size (BOARD), the number of analysts coverage (ANALYST), firm size (SIZE; market value), the percentage of interest–bearing liabilities (LEV), and the likelihood of being state-owned enterprises (SOE) are significantly positive, while the coefficients on the growth opportunity (TOBIN’Q), the percentage of equity and debt re-financing (FIN), information asymmetry (VOLAT) and a firm’s listing age (LISTAGE) are significantly negative, similar to prior literature (e.g. Du et al., 2014). Column (2) of Table 3 displays the regression results of H1. The coefficient on GBD is positive and significant at the 1% level (1.610 with t = 5.65), consistent with H1. Specifically, the significantly positive coefficient on GBD suggests that firms with the globalised board of directors are more environmentally responsible and have better environmental performance than their counterparts. Then, the value of environmen- tal performance index (EPI) for firms with the globalised board of directors is 0.431 CHINA JOURNAL OF ACCOUNTING STUDIES 507 Table 2. Pearson correlation analyses. Variables (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) (15) (16) (17) (18) (19) (20) (21) (22) EPI (1) 1.000 GBD (2) 0.120*** 1.000 RGD (3) 0.020*** 0.013 1.000 BLOCK (4) 0.144*** 0.051*** 0.028*** 1.000 MAN_SHR (5) −0.075*** −0.011 0.091*** −0.047*** 1.000 QFII_SHR (6) 0.046*** 0.045*** 0.022*** 0.016** −0.028*** 1.000 DUAL (7) −0.066*** 0.029*** 0.046*** −0.057*** 0.462*** −0.006 1.000 BOARD (8) 0.135*** 0.040*** −0.035*** 0.020*** −0.157*** 0.033*** −0.175*** 1.000 INDR (9) −0.008 0.012 0.002 0.049*** 0.099*** −0.002 0.099*** −0.463*** 1.000 ANALYST (10) 0.158*** 0.070*** 0.083*** 0.121*** 0.129*** 0.184*** 0.040*** 0.114*** 0.008 1.000 BIG10 (11) 0.059*** 0.053*** 0.074*** 0.061*** 0.037*** −0.009 0.034*** 0.006 0.024*** 0.065*** 1.000 SIZE (12) 0.298*** 0.098*** 0.024*** 0.210*** −0.222*** 0.119*** −0.137*** 0.195*** 0.054*** 0.396*** 0.155*** 1.000 LEV (13) 0.083*** −0.021*** −0.092*** 0.001 −0.137*** −0.029*** −0.049*** 0.110*** −0.022*** −0.097*** 0.001 0.210*** 1.000 ROA (14) 0.009 0.048*** 0.094*** 0.104*** 0.139*** 0.112*** 0.048*** 0.001 −0.014* 0.417*** 0.021*** 0.073*** −0.351*** 1.000 TOBIN’Q (15) −0.119*** 0.028*** 0.049*** −0.114*** 0.180*** −0.006 0.122*** −0.187*** 0.076*** −0.001 0.003 −0.135*** −0.294*** 0.184*** 1.000 FIN (16) 0.029*** −0.008 −0.002 0.018** −0.025*** −0.025*** 0.013 0.035*** −0.001 0.056*** 0.001 0.139*** 0.434*** −0.109*** −0.137*** 1.000 VOLAT (17) −0.081*** 0.010 0.022*** −0.035*** 0.075*** −0.034*** 0.058*** −0.113*** 0.040*** −0.056*** 0.005 0.023*** 0.009 −0.041*** 0.408*** 0.083*** 1.000 CAP_INV (18) 0.013* −0.010 −0.046*** −0.028*** 0.086*** −0.005 0.057*** 0.033*** −0.005 0.091*** 0.005 −0.045*** −0.049*** −0.016** −0.002 0.099*** −0.043*** 1.000 LISTAGE (19) 0.029*** −0.051*** −0.076*** −0.070*** −0.444*** 0.037*** −0.221*** 0.100*** −0.039*** −0.246*** −0.033*** 0.293*** 0.147*** −0.175*** −0.134*** 0.022*** −0.054*** −0.147*** 1.000 SOE (20) 0.155*** −0.053*** −0.090*** 0.197*** −0.372*** 0.049*** −0.283*** 0.268*** −0.068*** −0.052*** −0.022*** 0.281*** 0.121*** −0.133*** −0.258*** −0.015** −0.121*** −0.056*** 0.424*** 1.000 GDP_PC (21) 0.005 0.083*** 0.486*** 0.028*** 0.146*** −0.002 0.085*** −0.112*** 0.040*** 0.058*** 0.166*** 0.196*** −0.094*** 0.067*** 0.106*** −0.030*** 0.072*** −0.083*** −0.031*** −0.131*** 1.000 MKT (22) −0.025*** 0.084*** 0.523*** 0.011 0.187*** 0.009 0.134*** −0.122*** 0.020*** 0.070*** 0.151*** 0.081*** −0.068*** 0.098*** 0.092*** −0.015** 0.077*** −0.089*** −0.127*** −0.232*** 0.809*** 1.000 *: p < 0.10; **: p < 0.05; ***: p < 0.01. 508 X. DU ET AL. higher than that for firms without the globalised board of directors, which accounts for 59.1% of the mean value of EPI. Above results suggest that the influence of the globalised board of directors on environmental performance is economically signifi - cant, in addition to its statistical significance. In Column (3) of Table 3, we link environmental performance index with the globalised board of directors, regional green development and all control variables. The coefficient on GBD is positive and significant at the 1% level (1.677 with t = 5.87), lending additional support to H1. Then, as expected, the moderating variable of RGD has a significantly positive coefficient (0.209 with t = 4.69). Column (4) of Table 3 tabulates the regression results of H2a (H2b) – whether regional green development weakens (reinforces) the positive effect of the globalised board of directors on corporate environmental performance. In Column (4), GBD has a significantly positive coefficient (1.815 with t = 6.31), supporting H1 again; RGD has a significantly positive coefficient (0.247 with t = 5.39), echoing the finding in Column (3). More importantly, the coefficient on GBD×RGD is negative and significant at the 5% level (−0.328 with t = −2.48), and the coefficient difference test between (GBD +GBD×RGD) and GBD is significant at the 5% level (F-value = 6.16). Above results lend Table 3. Results of corporate environmental performance on the globalised board of directors, regional green development, and other determinants. Dependent variable: The raw value of environmental performance index (EPI) (1) (2) (3) (4) Variables Coefficient t-value Coefficient t-value Coefficient t-value Coefficient t-value GBD 1.610*** 5.65 1.677*** 5.87 1.815*** 6.31 RGD 0.209*** 4.69 0.247*** 5.39 GBD×RGD −0.328** −2.48 BLOCK 2.901*** 5.50 2.789*** 5.35 2.746*** 5.29 2.765*** 5.33 MAN_SHR −0.206 −0.26 0.159 0.20 0.184 0.24 0.209 0.27 QFII_SHR 1.778 0.09 −2.937 −0.14 −3.788 −0.18 −2.842 −0.14 DUAL −0.256 −1.20 −0.322 −1.52 −0.304 −1.44 −0.317 −1.51 BOARD 2.146*** 4.90 1.954*** 4.52 1.861*** 4.31 1.849*** 4.30 INDR 1.015 0.68 0.674 0.45 0.650 0.44 0.853 0.57 ANALYST 0.529*** 6.04 0.543*** 6.21 0.538*** 6.17 0.535*** 6.15 BIG10 0.085 0.56 0.062 0.41 0.062 0.42 0.060 0.40 SIZE 2.123*** 22.42 2.056*** 21.93 2.049*** 21.83 2.056*** 21.95 LEV 1.382** 2.15 1.516** 2.37 1.635** 2.55 1.631** 2.55 ROA −1.326 −0.76 −1.334 −0.77 −1.346 −0.78 −1.469 −0.86 TOBIN’Q −0.304*** −5.02 −0.305*** −5.07 −0.309*** −5.14 −0.304*** −5.07 FIN −0.920*** −3.30 −0.900*** −3.26 −0.929*** −3.36 −0.918*** −3.32 VOLAT −17.216*** −3.60 −16.852*** −3.54 −16.731*** −3.52 −16.562*** −3.48 CAP_INV −0.165 −0.36 −0.122 −0.27 −0.140 −0.31 −0.142 −0.31 LISTAGE −0.129*** −8.01 −0.123*** −7.71 −0.122*** −7.64 −0.122*** −7.63 SOE 1.462*** 7.44 1.532*** 7.87 1.525*** 7.86 1.510*** 7.78 GDP_PC 0.060 1.12 0.048 0.91 −0.013 −0.24 −0.012 −0.22 MKT 0.114 1.59 0.103 1.44 0.024 0.31 0.013 0.17 INTERCEPT −61.664*** −26.10 −59.600*** −25.94 −74.920*** −18.77 −78.071*** −18.98 Industry and Year Yes Yes Yes Yes Observations 16,713 16,713 16,713 16,713 Pseudo_R 9.87% 10.01% 10.10% 10.12% Log Likelihood −13,590.02 −13,568.95 −13,556.62 −13,552.48 LR Chi value 2,977.87***(0.000) 3,020.01***(0.000) 3,044.67***(0.000) 3,052.96***(0.000) Δ Pseudo_R 42.14***(0.000) 24.66***(0.000) 8.28***(0.004) (GBD + GBD×RGD) V.S. GBD 6.16**(0.013) *: p < 0.10; **: p < 0.05; ***: p < 0.01. All reported t-statistics are based on standard errors adjusted following White (1980). CHINA JOURNAL OF ACCOUNTING STUDIES 509 support to H2a, implying that regional green development weakens the positive rela- tion between the globalised board of directors and corporate environmental performance. 4.4. Robustness checks using other proxies for corporate environmental performance In Table 5, three additional variables are employed to re-test H1 and H2a (H2b). LN(1+ EPI) is the natural logarithm of (1+ the raw value of environmental performance index). EPI_STD is calculated as ‘(EPI −EPI )/ (EPI −EPI )’. EPI is the raw value j, t min, t max, t min, t j, t of environmental performance index for firm j in year t; and EPI (EPI ) is the min, t max, t minimum (maximum) of environmental performance index for all firms in year t. ENV is a proxy for all environmental items of GRI sustainability reporting guidelines, rather than environmental performance indicators. Panel A of Table 4 reports the OLS regression results using LN(1+ EPI) as the dependent variable. In Column (2) of Panel A, the coefficient on GBD is significantly positive (0.114 with t = 5.50). Then, in Column (4) of Panel A, the coefficient on GBD×RGD is significantly negative (−0.026 with t = −2.42). Above results additionally affirm H1 and H2a. Panel B of Table 4 reports the OLS regression results using EPI_STD as the dependent variable. In Column (2) of Panel B, GBD is significantly positively related with EPI_STD (0.029 with t = 6.55), consistent with H1. Then, in Column (4) of Panel B, GBD×RGD has a significantly negative coefficient (−0.005 with t = −2.13), lending additional support to H2a. Using ENV as the dependent variable, the Tobit regression results are listed in Panel C of Table 4. In Column (2) of Panel C, GBD is significantly positively associated with ENV (1.265 with t = 5.72). Then, in Column (4) of Panel C, the coefficient on GBD×RGD is negative and significant (−0.488 with t = −4.54). Results in Panel C of Table 4 verify H1 and H2a again. 4.5. The influence of the globalised board of directors on greenwashing Corporate environmental performance based on environmental disclosure may be biased if some firms ‘talk much but do little’ or ‘do much but talk little’. To alleviate this bias, we investigate the effect of the globalised board of directors on corporate greenwashing (GW), which means that a firm does not undertake environmental responsibilities but claims that it acts environment-friendly. GW is defined as ‘|ENV- ENV_EXP|’ if ENV<ENV_EXP and 0 otherwise (Du et al., 2018). ENV (ENV_EXP) is the actual (expected) value of environmental performance. If the actual value is greater than the expected value, the firm has already fulfilled its environmental responsibilities and is less likely to conduct greenwashing. On the contrary, if the actual value is less than the expected value, the firm has not fulfilled its environ- mental responsibility or does not meet the expectation from the public, implying that the firm may establish its reputation on environmental protection by greenwashing. In Column (2) of Table 5, the coefficient on GBD is negative and significant (−0.290 with t = −3.74), implying that the globalised board of directors mitigates corporate greenwashing. Then, in Column (4) of Table 5, the coefficient on GBD×RGD is positive 510 X. DU ET AL. Table 4. Robustness checks using other measures of corporate environmental performance. Panel A Robustness checks using the natural logarithm of (1+ the raw value of environmental performance index) Variables Dependent variable: The natural logarithm of (1+ the raw value of environmental performance index) – LN(1+EPI) (1) (2) (3) (4) Coefficient t-value Coefficient t-value Coefficient t-value Coefficient t-value GBD 0.114*** 5.50 0.117*** 5.67 0.126*** 6.02 RGD 0.014*** 5.19 0.017*** 5.99 GBD×RGD −0.026** −2.42 Control Variables Yes Yes Yes Yes INTERCEPT −4.253*** −26.90 −4.155*** −26.46 −5.245*** −20.17 −5.432*** −20.71 Industry and Year Yes Yes Yes Yes Observations 16,713 16,713 16,713 16,713 Adjusted_R 19.08% 19.32% 19.47% 19.52% F-value 84.86***(0.000) 84.38***(0.000) 83.47***(0.000) 82.08***(0.000) Δ Adjusted_R 49.57***(0.000) 31.04***(0.000) 10.35***(0.001) (GBD + GBD×RGD) V.S. GBD 5.84**(0.016) Panel B Robustness checks using the standardised environmental performance index Variables The dependent variable: The standardised environmental performance index (EPI_STD) (1) (2) (3) (4) Coefficient t-value Coefficient t-value Coefficient t-value Coefficient t-value GBD 0.029*** 6.55 0.030*** 6.69 0.032*** 7.06 RGD 0.002*** 4.95 0.003*** 6.05 GBD×RGD −0.005** −2.13 Control Variables Yes Yes Yes Yes INTERCEPT −0.648*** −22.53 −0.623*** −22.26 −0.807*** −17.26 −0.843*** −18.42 Industry and Year Yes Yes Yes Yes Observations 16,713 16,713 16,713 16,713 Adjusted_R 15.58% 16.19% 16.35% 16.42% F-value 66.62***(0.000) 68.25***(0.000) 67.67***(0.000) 66.68***(0.000) Δ Adjusted_R 121.29***(0.000) 31.87***(0.000) 13.96***(0.000) (GBD + GBD×RGD) V.S. GBD 4.53**(0.033) (Continued) CHINA JOURNAL OF ACCOUNTING STUDIES 511 Table 4. (Continued). Panel C Robustness checks using environmental performance on the basis of all environmental items of GRI sustainability reporting guidelines Variables Dependent variable: Environmental performance on the basis of all environmental items of GRI sustainability reporting guidelines (ENV) (1) (2) (3) (4) Coefficient t-value Coefficient t-value Coefficient t-value Coefficient t-value GBD 1.265*** 5.72 1.326*** 5.98 1.494*** 6.72 RGD 0.224*** 8.00 0.267*** 9.56 GBD×RGD −0.488*** −4.54 Control Variables Yes Yes Yes Yes INTERCEPT −46.734*** −29.04 −45.505*** −28.62 −61.962*** −24.11 −65.656*** −25.29 Industry and Year Yes Yes Yes Yes Observations 16,713 16,713 16,713 16,713 Pseudo_R 5.90% 5.97% 6.06% 6.10% Log Likelihood −38,658.34 −38,629.87 −38,595.13 −38,576.85 LR Chi value 4,849.06***(0.000) 4,905.99***(0.000) 4,975.47***(0.000) 5,012.03***(0.000) Δ Pseudo_R 56.94***(0.000) 69.48***(0.000) 36.56***(0.000) (GBD + GBD×RGD) V.S. GBD 20.64***(0.000) *: p < 0.10; **: p < 0.05; ***: p < 0.01. All reported t-statistics are based on standard errors adjusted following White (1980). 512 X. DU ET AL. Table 5. Robustness checks about the influence of the globalised board of directors on greenwashing. Dependent variable: Greenwashing (GW) Variables (1) (2) (3) (4) Coefficient t-value Coefficient t-value Coefficient t-value Coefficient t-value GBD −0.290*** −3.74 −0.312*** −4.01 −0.364*** −4.68 RGD −0.095*** −8.29 −0.107*** −9.26 GBD×RGD 0.150*** 3.81 BLOCK 0.527*** 3.77 0.544*** 3.90 0.552*** 3.96 0.544*** 3.91 MAN_SHR 0.617*** 3.51 0.579*** 3.29 0.584*** 3.32 0.584*** 3.32 QFII_SHR −7.356 −1.06 −6.628 −0.96 −5.917 −0.85 −6.565 −0.95 DUAL 0.019 0.40 0.025 0.52 0.018 0.37 0.021 0.43 BOARD −0.544*** −4.43 −0.520*** −4.24 −0.498*** −4.07 −0.498*** −4.07 INDR −1.337*** −3.05 −1.299*** −2.97 −1.277*** −2.93 −1.337*** −3.06 ANALYST −0.081*** −3.53 −0.082*** −3.59 −0.078*** −3.42 −0.076*** −3.32 BIG10 −0.036 −0.94 −0.033 −0.85 −0.022 −0.57 −0.020 −0.53 SIZE 0.477*** 14.96 0.486*** 15.22 0.489*** 15.34 0.486*** 15.22 LEV −1.383*** −8.16 −1.402*** −8.28 −1.442*** −8.55 −1.444*** −8.56 ROA 1.334*** 3.23 1.341*** 3.25 1.354*** 3.30 1.381*** 3.37 TOBIN’Q −0.064*** −5.77 −0.063*** −5.70 −0.061*** −5.56 −0.062*** −5.64 FIN 0.217*** 3.50 0.215*** 3.47 0.226*** 3.66 0.224*** 3.63 VOLAT −3.022*** −2.83 −3.089*** −2.90 −3.087*** −2.91 −3.110*** −2.93 CAP_INV 0.229* 1.95 0.225* 1.91 0.219* 1.87 0.220* 1.87 LISTAGE 0.038*** 8.98 0.037*** 8.82 0.037*** 8.83 0.038*** 8.88 SOE −0.070 −1.46 −0.081* −1.69 −0.087* −1.81 −0.083* −1.74 GDP_PC 0.001 0.06 0.002 0.14 0.025* 1.70 0.024 1.61 MKT −0.027 −1.41 −0.025 −1.32 0.016 0.79 0.020 1.00 INTERCEPT −8.602*** −11.32 −8.854*** −11.64 −1.888* −1.67 −0.808 −0.70 Industry and Year Yes Yes Yes Yes Observations 16,713 16,713 16,713 16,713 Pseudo_R 2.11% 2.14% 2.26% 2.29% Log Likelihood −28,264.75 −28,256.60 −28,221.77 −28,212.52 LR Chi value 1,217.95***(0.000) 1,234.27***(0.000) 1,303.91***(0.000) 1,322.43***(0.000) Δ Pseudo_R 16.30***(0.000) 69.66***(0.000) 18.50***(0.000) (GBD + GBD×RGD) V.S. GBD 14.55***(0.000) *: p < 0.10; **: p < 0.05; ***: p < 0.01. All reported t-statistics are based on standard errors adjusted following White (1980). and significant (0.150 with t = 3.81), implying that regional green development attenuates the negative relation between the globalised board of directors and corporate greenwashing. Above results lend supportive evidence to H1 and H2a, respectively. 4.6. Robustness checks using other proxies for the globalised board of directors In Table 6, we replace GBD with two other proxies for the globalised board of directors. One is the proportion of foreign directors on corporate board (GBD_RATIO), the other is an indicator variable for the globalised board of directors including oversea Chinese that equals 1 if at least one foreigner or oversea Chinese serves in the boardroom and 0 otherwise (GBD_BROAD). In Panel A of Table 6, the independent variable is GBD_RATIO. In Column (1), GBD_RATIO has a positive and significant coefficient (7.445 with t = 5.64), consistent with H1. In Column (3), GBD_RATIO×RGD has a significantly negative coefficient (−1.504 with t = −2.04), verifying H2a. CHINA JOURNAL OF ACCOUNTING STUDIES 513 Table 6. Robustness checks using other measures of the globalised board of directors. Panel A Robustness checks using a ratio variable for the globalised board of directors Variables Dependent variable: The raw value of environmental performance index (EPI) (1) (2) (3) Coefficient t-value Coefficient t-value Coefficient t-value GBD_RATIO 7.445*** 5.64 7.620*** 5.78 8.937*** 6.20 RGD 0.204*** 4.56 0.230*** 5.09 GBD_RATIO×RGD −1.504** −2.04 Control Variables Yes Yes Yes INTERCEPT −60.454*** −26.07 −75.424*** −18.88 −77.528*** −19.02 Industry and Year Yes Yes Yes Observations 16,713 16,713 16,713 Pseudo_R 10.03% 10.11% 10.13% Log Likelihood −13,566.87 −13,555.16 −13,551.88 LR Chi value 3,024.17***(0.000) 3,047.60***(0.000) 3,054.16***(0.000) Δ Pseudo_R 46.30***(0.000) 23.42***(0.000) 6.56**(0.010) (GBD_RATIO + GBD_RATIO×RGD) V.S. GBD_RATIO 4.18**(0.041) Panel B Robustness checks using the globalised board of directors in a broad sense Variables Dependent variable: The raw value of environmental performance index (EPI) (1) (2) (3) Coefficient t-value Coefficient t-value Coefficient t-value GBD_BROAD 1.075*** 4.75 1.116*** 4.92 1.344*** 5.85 RGD 0.203*** 4.55 0.278*** 5.96 GBD_BROAD×RGD −0.482*** −4.44 Control Variables Yes Yes Yes INTERCEPT −60.218*** −26.00 −75.134*** −18.76 −81.365*** −19.39 Industry and Year Yes Yes Yes Observations 16,713 16,713 16,713 Pseudo_R 9.96% 10.04% 10.12% Log Likelihood −13,576.85 −13,565.25 −13,553.33 LR Chi value 3,004.22***(0.000) 3,027.41***(0.000) 3,051.26***(0.000) Δ Pseudo_R 26.34***(0.000) 23.20***(0.000) 23.84***(0.000) (GBD_BROAD+ GBD_BROAD×RGD) V.S. GBD_BROAD 19.72***(0.000) *: p < 0.10; **: p < 0.05; ***: p < 0.01. All reported t-statistics are based on standard errors adjusted following White (1980). In Panel B of Table 6, the independent variable is GBD_BROAD. Column (1) shows that GBD_BROAD is significantly positively related with EPI (1.075 with t = 4.75), verifying H1 again. Further, in Column (3) of Panel B, the coefficient on GBD_BROAD×RGD is negative and significant (−0.482 with t = −4.44), providing additional support to H2a. 5. Endogeneity and additional tests 5.1. Endogeneity tests using firm fixed effect The firm-level fixed effect is employed to control for firm-level factors that do not change over time, and the results are reported in Table 7. In Column (1) of Table 7, the coefficient on GBD is positive and significant (0.393 with t = 2.45). Furthermore, in Column (2) of Table 7, the coefficient on GBD×RGD is negative and significant (−0.222 with t = −2.33). In 514 X. DU ET AL. Table 7. Endogeneity tests using firm fixed effect. Dependent variable: The raw value of environmental performance index (EPI) (1) (2) Variables Coefficient t-value Coefficient t-value GBD 0.393** 2.45 0.483*** 2.90 RGD 0.230** 2.28 GBD×RGD −0.222** −2.33 BLOCK 0.302 1.14 0.306 1.15 MAN_SHR 0.185 0.83 0.169 0.76 QFII_SHR −0.471 −0.09 0.145 0.03 DUAL 0.027 0.52 0.030 0.57 BOARD 0.165 0.74 0.144 0.65 INDR −0.151 −0.24 −0.210 −0.34 ANALYST −0.001 −0.05 −0.001 −0.04 BIG10 −0.063 −1.10 −0.058 −1.02 SIZE 0.086* 1.72 0.089* 1.77 LEV −0.133 −0.68 −0.142 −0.74 ROA −0.221 −0.64 −0.191 −0.56 TOBIN’Q 0.001 0.15 −0.001 −0.02 FIN −0.041 −0.93 −0.040 −0.92 VOLAT −1.288* −1.68 −1.310* −1.71 CAP_INV −0.034 −0.30 −0.051 −0.46 LISTAGE −0.283 −1.50 −0.282 −1.50 SOE 0.022 0.30 0.031 0.45 GDP_PC 0.003 0.07 −0.018 −0.40 MKT −0.045 −0.81 −0.070 −1.28 INTERCEPT 2.515 0.92 −15.562* −1.84 Firm and Year Yes Yes Observations 16,713 16,713 Adjusted_R 0.78% 1.53% F-value 3.19***(0.000) 3.33***(0.000) (GBD + GBD×RGD) V.S. GBD 5.45**(0.020) *: p < 0.10; **: p < 0.05; ***: p < 0.01. All reported t-statistics are based on standard errors adjusted following White (1980). general, empirical results in Table 7 are qualitatively similar to those in Table 3, which indicates that the main findings remain unchanged after employing the firm-level fixed effect to address the endogeneity issue. 5.2. Endogeneity tests using IV estimation approach To effectively conduct the IV estimation approach, it is critical to select the instru- mental variable for the globalised board of directors. In this study, we choose AIRPORT as the instrumental variable. Specifically, AIRPORT denotes the number of international airports within 100 kilometres around a firm’s registered address. Referring to Wooldridge (2001), a valid instrumental variable ought to meet two criteria: (1) It is strongly correlated with the potential endogeneity regressor (i.e. the globalised board of directors in this study); (2) It only affects the dependent variable (i.e. corporate environmental performance) through the potential endogeneity inde- pendent variable. The willingness of candidates to work abroad is a key factor that determines whether enterprises can successfully establish the globalised board of directors. In this regard, enterprises close to international airports are easily reached and are more attractive for candidates. Du et al. (2017) and Masulis et al. (2012) have validated that enterprises located near international airports are more likely to have CHINA JOURNAL OF ACCOUNTING STUDIES 515 foreign experts serving in the boardroom. Thus, AIRPORT meets the first criterion as it is theoretically predicted to be strongly correlated with the globalised board of directors. In China, the establishment of an international airport must be approved by the State Council, so it is less likely that the geographic distribution of interna- tional airports can directly affect corporate decision towards environmental respon- sibility. Accordingly, AIRPORT may fit in well with the second criterion to some extent. Panel A of Table 8 reports the results of the IV estimation approach for H1. At the first stage, we use OLS regression to link the globalised board of directors (GBD) to international airports (AIRPORT) and other control variables. In Column (1) of Panel A, AIRPORT is significantly positively related with GBD (0.029 with t = 10.85), consistent with our theoretical expectation. Then, at the second stage, we use the fitted value of GBD (i.e. GBD*) as the independent variable to re-test H1. In Column (2) of Panel A, the coefficient on GBD* is positive and significant (8.447 with t = 2.99), verifying H1. Furthermore, in the next-to-last (last) row, Chi value of AR (Wald) tests for weak IV is 8.83 (8.56) and is significant at the 1% level, indicating that AIRPORT is a valid instrument for GBD. Panel B of Table 8 tabulates the results of IV estimation approach for H2a and H2b. Referring to Wooldridge (2001), at the first stage, we employ the OLS regression to link the globalised board of directors (GBD) to international airports (AIRPORT), the inter- active term of AIRPORT×RGD and other control variables. Next, we also link the interactive term of GBD×RGD to international airports (AIRPORT), the interactive term of AIRPORT×RGD, and other control variables. In doing so, we obtain the fitted value of GBD (i.e. GBD*) and GBD×RGD [i.e. (GBD×RGD)*], respectively. Then, at the second stage, we regress EPI on GBD*, (GBD×RGD)* and other control variables to re-test H2a (H2b). In Column (3) of Panel B, GBD* is significantly positively related with EPI (11.747 with t = 3.94), verifying H1 again. In addition, the coefficient on (GBD×RGD)* is negative and significant (−3.197 with t = −2.10), lending supportive evidence to H2a. Meanwhile, in the next-to-last (last) row, Chi value of AR (Wald) test for weak IV is 20.47 (18.91) and is significant at the 1% level, indicating that AIRPORT is still valid for the model with interaction term. 5.3. Endogeneity tests using Heckman’s (1979) approach In addition to the fixed-effects estimate and IV regression, we further employ Heckman’s (1979) two-stage regression approach to alleviate the self-selection pro- blem. First, using AIRPORT and all control variables in Model (1), we conduct the first- stage regression of Heckman’s (1979) approach, and then calculate the inverse Mills Ratio (IMR). As expected, in Column (1) of Table 9, AIRPORT is significantly positively related with GBD (0.189 with t = 12.39). Second, in the second stage of Heckman’s (1979) approach, we include IMR to re-test Hypotheses 1, 2a, and 2b. As shown in Column (2) of Table 9, GBD has a significantly positive coefficient (4.736 with t = 2.80), supporting H1 again. In addition, results in Column (3) lend important support to H2a, along with a significantly negative coefficient on GBD×RGD (−0.390 with t = −2.57). 516 X. DU ET AL. Table 8. Endogeneity tests using IV estimation approach. Panel A The results of IV estimation approach for H1 Variables The first stage The second stage Dependent variable: Dependent variable: The globalised board of directors (GBD) The raw value of environmental performance index (EPI) (1) (2) Coefficient t-value Coefficient t-value AIRPORT 0.029*** 10.85 GBD* 8.447*** 2.99 INTERCEPT −0.853*** −11.22 −54.084*** −16.09 Industry and Year Yes Yes Observations 16,713 16,713 2 2 Pseudo_R /Adjusted_R 5.51% 9.91% Log Likelihood −13,585.13 LR Chi value/F-value 31.30***(0.000) 2,987.66***(0.000) AR test for weak identification 8.83***(0.003) Wald test for weak identification 8.56***(0.003) Panel B The results of IV estimation approach for H2a and H2b Variables The first stage The second stage Dependent variable: Dependent variable: Dependent variable: The globalised board The interactive term of The raw value of environmental of directors (GBD) GBD×RGD performance index (EPI) (1) (2) (3) Coefficient t-value Coefficient t-value Coefficient t-value AIRPORT 0.028*** 10.35 0.008* 1.89 GBD* 11.747*** 3.94 RGD −0.004*** −3.40 0.081*** 19.40 0.519*** 3.82 AIRPORT×RGD −0.002 −1.03 0.039*** 7.65 (GBD×RGD)* −3.197** −2.10 INTERCEPT −0.529*** −4.29 −7.326*** −19.27 −93.731*** −7.92 Industry and Year Yes Yes Yes Observations 16,713 16,713 16,713 2 2 Pseudo_R /Adjusted_R 5.58% 9.90% 10.02% Log Likelihood −13,568.47 LR Chi value/F-value 20.74***(0.000) 37.72***(0.000) 3,020.98***(0.000) [GBD* +(GBD×RGD)*] V.S. GBD* 4.39**(0.036) AR test for weak identification 20.47***(0.000) Wald test for weak identification 18.91***(0.000) *: p < 0.10; **: p < 0.05; ***: p < 0.01. All reported t-/z-statistics are based on standard errors adjusted following White (1980). 5.4. Endogeneity tests using PSM-DID method Some sample firms have not foreign directors in the boardroom in early years, but they hired foreign directors in later years. Above case provides us with a unique setting to conduct endogeneity test using PSM-DID method on the basis of the arrival of foreign directors. First, we identify two groups of sample firms: the group with the arrival of foreign directors (i.e. the treated group), the group without the arrival of foreign directors (i.e. the controlling group). Next, we employ the propensity score matching (PSM) process, CHINA JOURNAL OF ACCOUNTING STUDIES 517 Table 9. Endogeneity tests using Heckman’s (1979) two-stage regression approach. The first stage The second stage Dependent variable: Dependent variable: The globalised board of directors The raw value of environmental performance index (GBD) (EPI) (1) (2) (3) Variables Coefficient z-value Coefficient t-value Coefficient t-value AIRPORT 0.189*** 12.39 GBD 4.736*** 2.80 6.159*** 3.60 RGD 0.261*** 5.67 GBD×RGD −0.390*** −2.89 IMR −1.661* −1.88 −2.292** −2.57 BLOCK 0.434*** 4.10 2.570*** 4.89 2.464*** 4.71 MAN_SHR −0.984*** −6.10 0.631 0.77 0.864 1.06 QFII_SHR 10.400** 2.45 −11.153 −0.53 −14.038 −0.67 DUAL 0.159*** 4.04 −0.399* −1.83 −0.425** −1.96 BOARD 0.705*** 7.33 1.637*** 3.52 1.408*** 3.04 INDR 0.777** 2.39 0.227 0.15 0.267 0.18 ANALYST −0.022 −1.22 0.562*** 6.35 0.561*** 6.37 BIG10 0.058* 1.87 0.022 0.14 0.004 0.03 SIZE 0.201*** 9.99 1.949*** 17.90 1.909*** 17.54 LEV −0.442*** −3.32 1.754*** 2.73 1.963*** 3.05 ROA 0.266 0.76 −1.394 −0.81 −1.576 −0.92 TOBIN’Q 0.020** 2.14 −0.313*** −5.20 −0.315*** −5.24 FIN −0.054 −1.02 −0.884*** −3.21 −0.895*** −3.24 VOLAT −1.354 −1.47 −16.114*** −3.38 −15.509*** −3.26 CAP_INV −0.112 −1.19 −0.054 −0.12 −0.049 −0.11 LISTAGE −0.014*** −4.26 −0.116*** −7.06 −0.112*** −6.82 SOE −0.311*** −7.63 1.678*** 8.05 1.709*** 8.23 GDP_PC 0.035*** 3.18 0.034 0.64 −0.033 −0.61 MKT −0.008 −0.49 0.082 1.12 −0.022 −0.29 INTERCEPT −8.113*** −16.05 −56.392*** −19.81 −74.742*** −17.39 Industry Yes Yes Yes Year Yes Yes Yes Observations 16,713 16,713 16,713 Pseudo_R 10.40% 10.03% 10.16% Log Likelihood −4,099.55 −13,566.37 −13,547.68 LR Chi value 951.82***(0.000) 3,025.18***(0.000) 3,062.56***(0.000) (GBD + GBD×RGD) V.S. GBD 8.38*(0.004) *: p < 0.10; **: p < 0.05; ***: p < 0.01. All reported t-/z-statistics are based on standard errors adjusted following White (1980). abiding by the one-to-one principle and adopting ‘±0.001ʹ as the threshold to match each observation in the treated group to the controlling group. In doing so, governance mechanisms (BLOCK, MAN_SHR, QFII_SHR, DUAL, BOARD and INDR), firm-specific char- acteristics (SIZE, LEV, ROA, and TOBIN’Q) and a dummy variable for state-owned enter- prises (SOE) are chosen to conduct the PSM process. Then, we get a sample of 2,554 observations, including 1,277 in the treated group and 1,277 in the controlling group. As shown in Panel A of Table 10, after conducting the PSM process, the differences in all chosen variables become insignificant between the treated group and the controlling group, suggesting that we have done a relatively good matching work. Lastly, we define a set of variables as below: TREAT is an indicator variable for the treated group, equalling 1 if the firm experienced the arrival of foreign directors during the sample period and 0 otherwise. POST is an indicator variable for the post-period, equalling 1 for the post- period and 0 otherwise. TREAT×POST is the interactive term of TREAT and POST. In difference-in-difference (DID) regressions, TREAT×POST is included to estimate the effect 518 X. DU ET AL. of the arrival of foreign directors on corporate environment performance. In the mean- time, TREAT and year dummies are used to control for the treatment effect and the time effect, respectively. As shown in Column (1) of Panel B of Table 10, we find a significantly positive coefficient on TREAT×POST (1.274 with t = 2.03), consistent with H1. It suggests that the difference in corporate environmental performance between the treated group and the controlling group becomes significantly greater after the arrival of foreign directors. Then, in Column (2), we find a significantly negative coefficient on TREAT×POST×RGD (−0.616 with t = −2.94), consistent with H2a. 5.5. Additional tests considering the original countries (regions) of foreign directors Referring to Du et al. (2017) and Masulis et al. (2012), we investigate the influence of time zone difference between original countries (regions) of foreign directors and corporate headquarters – which captures the geographic distance and monitoring costs – on corporate environmental performance. GBD_TZ (GBD_NTZ) is an indicator that equals 1 if the work time period of at least one foreign director’s original country or region has a (no) overlap with the trading hours of China’s stock market and 0 otherwise. In Column (1) of Panel A in Table 11, GBD_TZ is significantly positively related with EPI (2.041, with t = 6.49), but the coefficient on GBD_NTZ is insignificant. Above results reveal that the difference in time zone suppresses the positive effect of foreign directors on environmental performance, echoing Du et al. (2017) and Masulis et al. (2012). Foreign directors on corporate boards are expected to hold stronger stakeholder perspective when investor protection mechanisms are of high quality and being effec - tively implemented in their original countries (regions). In response, GBD_H_IP (GBD_L_IP) is an indicator variable that equals 1 if the investor protection index of at least one foreign director’ original country or region is higher (lower) than that of China and 0 otherwise. As reported in Column (2) of Panel A in Table 11, GBD_H_IP is signifi - cantly positively related with EPI (1.903, with t = 6.22), but the coefficient on GBD_L_IP is insignificant, suggesting that foreign directors from countries (regions) with better inves- tor protection have done a relatively good job in enhancing corporate environmental performance. We further examine whether foreign directors from countries (regions) with better performance in environmental responsibilities exert greater effect on corporate environ- mental performance. Based on the Environmental Performance Index developed by Yale University, Columbia University and World Economic Forum, we define GBD_H_ER (GBD_L_ER) as an indicator variable, equalling 1 if at least one foreign director’ original country (region) performs better (worse) in environmental responsibilities compared with China and 0 otherwise. In Column (3) of Panel C in Table 11, GBD_H_ER is significantly positively related with EPI (1.560, with t = 5.40), but the coefficient on GBD_L_ER is insignificant, suggesting that the positive effect of foreign directors on environmental performance only holds for foreign directors from environmentally friendly countries (regions). CHINA JOURNAL OF ACCOUNTING STUDIES 519 Table 10. Endogeneity tests using PSM-DID method. Panel A T-tests about the differences between the treated group and the controlling group Full sample Matched sample TREAT = 1 TREAT = 0 TREAT = 1 TREAT = 0 [N = 1,303] [N = 14,083] [N = 1,277] [N = 1,277] Variables Mean S. D. Mean S. D. t-test Mean S. D. Mean S. D. t-test BLOCK 0.375 0.150 0.353 0.150 5.16*** 0.373 0.150 0.372 0.158 0.21 MAN_SHR 0.041 0.115 0.057 0.128 −4.26*** 0.042 0.116 0.045 0.113 −0.58 QFII_SHR 0.001 0.004 0.001 0.003 4.28*** 0.001 0.004 0.001 0.004 0.77 DUAL 0.203 0.403 0.231 0.421 −2.27** 0.208 0.406 0.221 0.415 −0.82 BOARD 2.177 0.204 2.152 0.197 4.34*** 2.175 0.204 2.182 0.201 −0.87 INDR 0.372 0.057 0.371 0.052 0.69*** 0.371 0.057 0.372 0.055 −0.35 SIZE 23.049 1.335 22.545 1.046 16.23*** 22.998 1.291 23.009 1.199 −0.22 LEV 0.162 0.135 0.172 0.147 −2.17** 0.162 0.135 0.167 0.143 −0.84 ROA 0.045 0.057 0.036 0.054 5.68*** 0.045 0.057 0.044 0.056 0.30 TOBIN’Q 2.612 2.064 2.701 2.026 −1.52 2.631 2.074 2.623 2.096 0.11 SOE 0.496 0.500 0.452 0.498 3.02*** 0.490 0.500 0.475 0.500 0.80 Panel B The results of difference-in-difference (DID) regressions Variables Dependent variable: The raw value of environmental performance index (EPI) (1) (2) Coefficient t-value Coefficient t-value TREAT −0.174 −0.46 −0.203 −0.54 TREAT×POST 1.274** 2.03 1.395** 2.26 RGD 0.138 1.35 TREAT×POST×RGD −0.616*** −2.94 Control Variables Yes Yes INTERCEPT −57.963*** −11.15 −68.765*** −7.88 Industry and Year Yes Yes Observations 2,554 2,554 Pseudo_R 11.69% 11.83% Log Likelihood −2,600.17 −2,595.92 LR Chi value 688.42***(0.000) 696.91***(0.000) (TREAT×POST + TREAT×POST×RGD) V.S. TREAT×POST 8.678***(0.003) *: p < 0.10; **: p < 0.05; ***: p < 0.01. All reported t-statistics are based on standard errors adjusted following White (1980). 5.6. Cross-sectional analyses considering external monitoring mechanisms In Panel A of Table 11, for both the subsample with high analyst coverage and the subsample with low analyst coverage, GBD has a positive and significant coefficient. However, the coefficient test reveals that the coefficient on GBD for the subsample with low analyst coverage (2.735 with t = 5.25) is significantly larger than that for the sub- sample with high analyst coverage (0.992 with t = 3.05). Next, DIS_REGU is defined as the distance between the firm’s registered address and the nearest securities regulator (the China Securities Regulatory Commission, the Shanghai Stock Exchange and the Shenzhen Stock Exchange), which captures regulatory intensity (El Ghoul et al., 2013). In Panel B, the coefficients on GBD are both significantly positive for two subsamples, but the coefficient on GBD is significantly larger for the subsample with weak regulatory intensity (2.072 with t = 5.52) than that for the subsample with strong regulatory intensity (1.120 with t = 2.57). 520 X. DU ET AL. Table 11. Cross-sectional analyses considering external monitoring mechanisms. Panel A Cross-sectional analyses considering analyst coverage Variables Dependent variable: The raw value of environmental performance index (EPI) High analyst coverage Low analyst coverage (1) (2) Coefficient t-value Coefficient t-value GBD 0.992*** 3.05 2.735*** 5.25 Control Variables Yes Yes INTERCEPT −60.801*** −22.29 −63.653*** −14.31 Industry and Year Yes Yes Observations 7,980 8,733 Pseudo_R 9.79% 8.59% Log Likelihood −8,133.31 −5,370.56 LR Chi value 1,765.24***(0.000) 1,009.97***(0.000) Chow test for two subsamples 142.25***(0.000) Coefficient test on GBD −8.05***(0.004) Panel B Cross-sectional analyses considering regulatory intensity Variables Dependent variable: The raw value of environmental performance index (EPI) High regulatory intensity Low regulatory intensity (1) (2) Coefficient t-value Coefficient t-value GBD 1.120** 2.57 2.072*** 5.52 Control Variables Yes Yes INTERCEPT −63.945*** −19.03 −52.164*** −14.91 Industry and Year Yes Yes Observations 8,355 8,358 Pseudo_R 10.14% 10.91% Log Likelihood −6,969.58 −6,519.87 LR Chi value 1,573.08***(0.000) 1,596.38***(0.000) Chow test for two subsamples 171.09***(0.000) Coefficient test on GBD −2.74*(0.098) Panel C Cross-sectional analyses considering the nature of the ultimate owner Variables Dependent variable: The raw value of environmental performance index (EPI) SOE subsample Non-SOE subsample (1) (2) Coefficient t-value Coefficient t-value GBD 1.026*** 3.04 2.091*** 4.47 Control Variables Yes Yes INTERCEPT −55.555*** −20.42 −56.852*** −11.34 Industry and Year Yes Yes Observations 7,442 9,271 Pseudo_R 11.77% 5.48% Log Likelihood −7,771.32 −5,677.32 LR Chi value 2,073.56***(0.000) 658.62***(0.000) Chow test for two subsamples 555.48***(0.000) Coefficient test on GBD −3.41*(0.065) *: p < 0.10; **: p < 0.05; ***: p < 0.01. All reported t-statistics are based on standard errors adjusted following White (1980). CHINA JOURNAL OF ACCOUNTING STUDIES 521 In China, state-owned enterprises are not only regulated by securities regulators, but also under the supervision of SASAC and local governments, which leads to the relatively high level of external monitoring. As reported in Panel C of Table 12, GBD has significantly positive coefficients for both the SOE and non-SOE subsamples, but the coefficient on GBD is significantly larger for the non-SOE subsample (2.091 with t = 4.47) than that for the SOE subsample (1.026 with t = 3.04). Overall, the positive relation between foreign directors and corporate environmental performance is more pronounced for firms with weak external monitoring mechanisms – low analyst coverage, weak regulatory intensity and non-SOE. 5.7. Additional tests about economic consequences of better environmental performance To address economic consequences of better environmental performance, additional variables of COC, COD, ROT and SUBSIDY are defined. COC (the cost of capital) is defined 1/2 as ‘[(EPS −EPS )/P ] ’ (EPS is the mean value of analysts’ forecast on earnings per t+2 t+1 t share; P is stock price at the end of the year). COD is the cost of debt, measured as the total interest expenses divided by the amount of interest-bearing liabilities. ROT is the natural logarithm of (1+ the amount of refund of taxes). SUBSIDY is the natural logarithm of (1+ the amount of government subsidies). In Columns (1) and (2) of Panel B in Table 12, EPI is significantly negatively related with both COC (−0.001 with t = −4.15) and COD (−0.001 with t = −2.26). Meanwhile, in Columns (3) and (4), EPI is significantly positively related with both ROT (0.071 with t = 2.84) and SUBSIDY (0.032 with t = 4.44). Above result suggest that environmentally responsible enterprises have lower costs of capital and debt, more tax benefits and more government subsidies, consistent with theoretical expectation. 6. Conclusions, managerial implications, limitations and future research In this study, we address the relation between the globalised board of directors and environmental performance, and further investigate the moderating effect of regional green development on above relation. Our findings reveal a positive and significant relation between the globalised board of directors and corporate environmental performance, suggesting that the globalised board of directors can strengthen the moral and strategic incentives for firms to undertake environmental responsibility and enhance environmental performance. Moreover, regional green development attenu- ates the positive effect of the globalised board of directors on corporate environmen- tal performance. This study has several managerial implications as below: First, our findings imply that board nationality diversity can enhance board independence and board super- visory capability, which can help to shift superior environmental practices to managers and result in better environmental performance. Thus, our finding can inspire regula- tory bodies to attach the importance to the positive role of board nationality diversity in corporate behaviour (e.g. environmental performance in our study). Moreover, Chinese listed firms should incorporate foreign directors from advanced countries 522 X. DU ET AL. Table 12. Additional tests. Panel A Additional tests considering the characteristics of foreign directors’ original countries (regions) Variables Dependent variable: The raw value of environmental performance index (EPI) Time zone difference Investor protection Environmental responsibilities (1) (2) (3) Coefficient t-value Coefficient t-value Coefficient t-value GBD_TZ 2.041*** 6.49 GBD_NTZ −0.280 −0.46 GBD_H_IP 1.903*** 6.22 GBD_L_IP −0.580 −0.81 GBD_H_ER 1.560*** 5.40 GBD_L_ER 1.501 1.48 Control Variables Yes Yes Yes INTERCEPT −59.441*** −25.99 −59.359*** −25.87 −59.585*** −25.89 Industry and Year Yes Yes Yes Observations 16,713 16,713 16,713 Pseudo_R 10.07% 10.05% 10.01% Log Likelihood −13,561.16 −13,563.04 −13,569.46 LR Chi value 3,035.59***(0.000) 3,031.83***(0.000) 3,019.00***(0.000) (Continued) CHINA JOURNAL OF ACCOUNTING STUDIES 523 Table 12. (Continued). Panel B Additional tests about economic consequences of better corporate environmental performance Variables Dependent variable: Cost of capital Dependent variable: Cost of debt Dependent variable: Refund of taxes Dependent variable: Government Subsidy (COC) (COD) (ROT) (SUBSIDY) (1) (2) (3) (4) Coefficient t-value Coefficient t-value Coefficient t-value Coefficient t-value EPI −0.001*** −4.15 −0.001** −2.26 0.071*** 2.87 0.032*** 4.44 BLOCK −0.015*** −6.00 −0.021*** −4.33 0.284 0.76 −0.054 −0.40 MAN_SHR 0.012*** 3.87 −0.048*** −8.56 3.266*** 6.59 1.407*** 10.19 QFII_SHR 0.288*** 3.41 −0.495*** −2.69 −6.520 −0.40 11.494** 2.37 DUAL −0.002* −1.95 −0.001 −0.57 −0.261* −1.91 −0.048 −1.02 BOARD −0.004** −1.97 0.005 1.36 −0.483 −1.49 0.245** 2.22 INDR 0.007 0.94 0.005 0.40 −1.415 −1.26 0.476 1.24 ANALYST 0.007*** 16.17 0.002*** 3.15 1.628*** 25.48 0.955*** 43.83 BIG10 0.015*** 4.82 −0.172*** −29.46 3.378*** 7.74 1.256*** 7.78 SIZE 0.035*** 3.82 −0.200*** −12.36 1.167 1.07 4.746*** 9.37 LEV −0.004*** −17.43 0.002*** 3.14 −0.463*** −14.91 −0.228*** −13.66 ROA −0.009*** −10.14 0.004** 2.34 0.186 1.47 0.039 0.83 TOBIN’Q −0.042*** −3.90 0.068*** 3.80 −24.960*** −16.07 −6.135*** −11.61 SOE −0.001*** −4.15 −0.001** −2.26 0.071*** 2.87 0.032*** 4.44 INTERCEPT −0.015*** −6.00 −0.021*** −4.33 0.284 0.76 −0.054 −0.40 Industry and Year Yes Yes Yes Yes Observations 11,518 13,579 16,092 16,024 Adjusted_R 27.38% 15.41% 24.72% 26.43% F-value 109.53***(0.000) 62.83***(0.000) 133.11***(0.000) 144.92***(0.000) *: p < 0.10; **: p < 0.05; ***: p < 0.01. All reported t-statistics are based on standard errors adjusted following White (1980). 524 X. DU ET AL. (regions) to actively establish the globalised board of directors, which can cultivate environmental consciousness and facilitate them to improve environmental performance. Second, given the positive impact of green development as a social atmosphere on environmental performance, it is suggested that the government should pay close attention to the bright side of adding environmental requirements into the official’s evaluation system. As such, regional green development can inspire local officials to show the solicitude for the increasingly deteriorated natural environ- ment in China, which is expected to constrain enterprises in the province from destroying the natural environment, urge enterprises to fulfill environmental responsibilities. Third, our findings suggest a doable strategy of hiring foreign directors from different countries (regions) for listed firms located in provinces with lower level of green devel- opment to enhance environmental performance. By introducing foreign directors into the boardroom, firms in provinces with lower green development can ensure board nation- ality diversity, establish the globalised board of directors, and are inclined to behave in an environment-friendly way. Finally, our findings can further refine the scope of Chinese listed firms to choose foreign directors to establish the globalised board of directors, motivating Chinese enterprises to pay close attention to the negative impact of time zone difference on the role of the globalised board of directors in enhancing corporate environmental perfor- mance. Furthermore, our findings can inspire Chinese enterprises to import foreign directors from environment-friendly countries (regions). This study also has its limitations. First, environmental performance is measured based on environmental information disclosure. Although the index has been highly acknowledged by scholars (e.g. Du et al., 2014; Rahman & Post, 2012), it may be biased if some firms ‘talk much but do little’ or ‘do much but talk little’. Second, our study focuses on environmental performance (a specific CSR dimension), and it remains unknown about whether the globalised board of directors can play its advising and monitoring roles in other CSR dimensions (e.g. philanthropy, product quality, staff health). Third, due to data limitation, we cannot obtain the data on environmental consciousness of foreign directors. As a result, we do not examine whether the effect of foreign directors with different levels of environmental consciousness on environ- mental performance is similar or asymmetric. Finally, our study is conducted based on the Chinese context, so our findings may not fit in well with other contexts. 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Journal
China Journal of Accounting Studies
– Taylor & Francis
Published: Oct 1, 2020
Keywords: The globalised board of directors; regional green development; board governance; the supervisory and advisory functions; corporate environmental performance
