China Journal of Accounting Studies, 2014 Vol. 2, No. 4, 323–344, http://dx.doi.org/10.1080/21697213.2014.984265 a b c Zhi Jin *, Shunlin Song and Xue Yang a b School of Accounting, Southwestern University of Finance and Economics, China; School of Accountancy, Central University of Finance and Economics, China; Business School, Sun Yat-Sen University, China This paper investigates the effects of regional market environment and organisational- power environment on the relationship between female directors and corporate- investment efﬁciency in the Chinese institutional context. Our results show that although a higher proportion of female directors is, in general, associated with a lower level of investment efﬁciency, both a stronger market environment and a lower power concentration may attenuate the negative effect of female directors on investment efﬁ- ciency. The association between female directors and investment efﬁciency is negative and signiﬁcant in regions with a weaker market environment and in ﬁrms with a higher power concentration, but insigniﬁcant in regions with a stronger market environment and in ﬁrms with a lower power concentration. These ﬁndings indicate the importance of considering a regional environment and organisational environment when examin- ing the role of female directors in board governance. Keywords: board governance; corporate investment; female directors; regional and organisational environment 1． Introduction In recent years, more and more women are joining ‘men’s clubs’ such as boards of directors, and thereby eroding corporate male dominance. This phenomenon has received a great deal of attention from academics and practitioners alike. Carter, Simkins, and Simpson (2003) and Erhardt, Werbel, and Shrader (2003) identify a positive relationship between the number of female directors at a ﬁrm and the ﬁrm’s performance in the US. Campbell and Minguez-Vera (2008) support this result using ﬁrms in Spain. However, using US data, Adams and Ferreira (2009) ﬁnd that an increase in the number of female directors decreases the value of a ﬁrm, and Miller and Triana (2009) claim that the number of female directors has no signiﬁcant inﬂuence on ﬁrm value. There are two possible reasons for the inconsistency of these results. First, the presence of female directors may affect ﬁrm value by inﬂuencing the efﬁciency of board governance. Whether this effect is positive or negative depends on the nature of the female powerbase on the board, which is greatly inﬂuenced by local female culture. Female culture differs across countries and regions. In some areas, cultural gender norms encourage women to play an active role in overseeing ﬁrms’ affairs. However, cultural norms in other areas depict women as passive and subordinate, cre- ating an unfavourable environment for them to engage actively in governance (Wang, 2005;Wu, 2009). As a result, company value in such regions is unlikely to be *Corresponding author. E-mail: email@example.com Paper accepted by Tong Yu. © 2014 Accounting Society of China 324 Jin et al. improved by the presence of female directors. However, the aforementioned studies ignore the effects of market environment and organisational environment on female directors’ governance, which makes it difﬁcult to draw reliable inferences regarding the role of female directors. Second, many factors may affect ﬁrm value, of which capital investment efﬁciency and operation management efﬁciency are the most important. Although the introduction of female directors may improve the efﬁciency of investment by enhancing board governance, the ﬁrm’s management costs may increase simultaneously for other reasons. The joint effect of these phenomena on ﬁrm value is difﬁcult to ascertain. As investment is the most important factor affect- ing ﬁrm value, exploring the effects of female directors on companies’ investment efﬁciency offers the most direct insights into the inﬂuence of female directors on ﬁrm value (Zhu, Ye, & Yan, 2012). In this paper, we use data on Chinese listed ﬁrms from 2005 to 2010 to investigate the effects of market environment and organisational environment on the relationship between female directors and investment efﬁciency. Our results show that although a higher proportion of female directors is in general associated with a lower level of investment efﬁciency, both a stronger market environment and a lower power concen- tration may weaken the negative association of female directors with investment efﬁ- ciency. The relationship between female directors and investment efﬁciency is negative and signiﬁcant in regions with a weaker market environment and in ﬁrms with a higher power concentration, but insigniﬁcant in regions with a stronger market environment and in ﬁrms with a lower power concentration. These ﬁndings highlight the importance of considering regional environment and organisational environment when examining the role of female directors in board governance. Our paper contributes to the literature in three ways. First, our insights into women’s governance roles in the largest emerging market in the world complement the ﬁndings of existing studies of female directors in Europe and America. Second, we explore the role of female directors in board governance by investigating the effects of regional environment and organisational environment on the relationship between female directors and investment efﬁciency. This exploration supplements the existing literature on the role of female directors in board governance. And it also reminds the regulators to consider improving the institutional environment before copying the gen- der-diverse boards of developed markets; otherwise, board governance and ﬁrm value may not improve. The remainder of this paper is structured as follows. In Section 2, we discuss the relevant existing literature. Section 3 brieﬂy introduces China’s institutional back- ground. Section 4 presents the theoretical analysis and hypotheses. In Section 5,we detail our methodology and sample selection, and provide descriptive statistics. In Sec- tion 6, we report on the empirical results of our regression analyses. Section 7 provides the results of a robustness check. Section 8 concludes the paper. 2. Related literature In recent years, a series of important studies have been conducted in this ﬁeld, follow- ing two main lines of logic. Carter et al. (2003), Erhardt et al. (2003), Campbell and Minguez-Vera (2008) argue that women have certain characteristics that facilitate board governance and thus improve ﬁrm performance. Using a sample of US Fortune- 1,000 ﬁrms, Carter et al. (2003) ﬁnd the relationship between board diversity and ﬁrm value to be signiﬁcantly positive. They argue that diversity enhances the supervisory China Journal of Accounting Studies 325 role of a board by providing reputational incentives for directors, decreasing managers’ agency costs and increasing ﬁrm value. Using a sample of 127 large US ﬁrms, Erhardt et al. (2003) identify a positive relationship between board diversity (the proportion of female directors) and ﬁrm ﬁnancial performance. They argue that female directors can improve the supervisory function and decision-making efﬁciency of a board. Unlike most researchers, who use US samples, Campbell and Minguez-Vera (2008) examine Spanish listed ﬁrms. Similarly, however, they ﬁnd that gender diversity improves ﬁrm performance. In addition, Miller and Triana (2009), testing a sample of Fortune 500 ﬁrms, use behavioural theory to argue that a gender-diverse board of directors increases a ﬁrm’s creativity by multiplying its sources of information, which may in turn increase ﬁrm value. However, the claims made by Miller and Triana (2009) are only partly sup- ported by their empirical results. They show that the presence of female directors improves a ﬁrm’s innovation capacity, but ﬁnd no evidence that female directors improve ﬁrm value. In contrast, some researchers argue that the presence of females on boards exacer- bates board disagreements, results in excessive monitoring and harms investment efﬁ- ciency and ﬁrm performance (Kravitz, 2003; Richard, Kochan, & McMillan-Capehart 2002). Using data on US listed ﬁrms from 1996 to 2003, Adams and Ferreira (2009) ﬁnd that female directors are generally more diligent than their male counterparts and thus have a positive effect on board governance. However, the authors ﬁnd no evidence that a gender-diverse board improves ﬁrm value. On the contrary, they claim that in ﬁrms with good governance, gender diversity may result in excessive supervision and decrease ﬁrm value. Using a sample of US listed ﬁrms from 2000 to 2006, Hussein and Kiwia (2009) also argue that gender diversity on a board does not improve ﬁrm performance. With an increasing number of studies of female directors in Western countries, some scholars have investigated the role in governance of female directors in China. Ye, Zhang, and Rezaee (2010) argue that although China’s long-held social traditions make it more difﬁcult for women in China than their Western counter- parts to achieve professional success, gender equality has gradually been realised in the Chinese business environment since the foundation of the People’s Republic of China, due to the government’s efforts to foster gender equality. In support of this argument, Ye et al. (2010) show that in their sample of ﬁrms, the gender of a board chairman has no effect on earnings quality. In addition, Zhu et al. (2012) argue that women are more likely than men to constrain corporate investment in Chinese ﬁrms, because they are more risk averse. Zhu et al. (2012) use a natural economic experiment to show that during the 2008 ﬁnancial crisis, ﬁrms with lar- ger proportions of female directors experienced sharper declines in corporate invest- ment and that this effect was most conspicuous in ﬁrms that over-invested. Although Zhu et al. (2012) examine the relationship between female directors and corporate investment during ﬁnancial crises, we consider that they and other schol- ars pay insufﬁcient attention to the effects of market environment and organisa- tional environment on the role of female directors. In this paper, we propose that the role played by female directors in board governance depends on ﬁrms’ local market environment and on the organisational environment in which their directors work. Drawing on the ﬁndings of existing studies, we seek to open the ‘black box’ that links female directors with ﬁrm value by investigating the effect of mar- ket environment and organisational environment on the role of female directors in corporate investment. 326 Jin et al. 3. Institutional background Gender roles reﬂect power relationships that are inﬂuenced by cultural and social back- grounds (Scott, 1988; Zhou, Fu, & Wu, 2010). We suggest that the balance of discur- sive power between men and women is affected in the same way. We posit that China is distinguished by its traditional culture and economic system. We further posit that although the discursive power of Chinese women has been inﬂuenced profoundly by Chinese traditional culture, it has also been shaped by modern marketisation reforms. Together, the ‘Three Obediences and Four Virtues’ underpinning Confucianism and the ‘Three Cardinal Guides’ proposed by Confucian Zhongshu Dong constitute the ideol- ogy of China’s traditional patriarchal society, which mandates male dominance and female subordination (Wang, 2005). Under the long inﬂuence of this ideology, unequal gender relations such as female subordination and perceptions of female inferiority have developed in Chinese society. We suggest that these cultural and ideological traditions continue to have a profound effect on gender relations in modern China. Before China’s economic reform and opening-up policy, various women’s liberation movements were spearheaded by the government during three historical periods, seemingly manifesting a general trend toward gender equality. However, further investigation reveals that the gov- ernment’s calls for gender equality were intended primarily to boost domestic industrial production rather than to eliminate gender discrimination (Wu, 2009). According to Wu (2009), the government’s attitude towards gender equality has remained constant since China’s reform and opening up, although ofﬁcial wordings per- taining to this issue have been modiﬁed in both form and content. Nevertheless, each time employment fell, the government began to vacillate in its attitude towards female employment, advocating policies such as ‘women return home’ and ‘employing women by steps’ (Wu, 2009). Mou (2008) shows that, so far, gender-discriminating actions against women, such as ‘man-only’ or ‘man-preferred’ requirements on job advertise- ments, have been quite common in the job market; and employers sometimes still hold concealed bias towards male applicants although without speciﬁc written gender requirements. Consequently, men enjoy priority over women in the labour market, no matter how such gender division changes with the ﬂuctuating economy (Jin, 2000). Moreover, although gender bias against women emerges in various areas of Chinese society such as education and employment, state policies do not embody the idea of gender equality in law and regulation (Wu, 2009). However, on the whole, the marketisation reform since 1978 has greatly enhanced the employment opportunities of Chinese women at different levels, has strengthened their economic independence and improved their social status (Cooke, 2001). Further, it is worth mentioning that although the marketisation reforms over the past three dec- ades have greatly promoted China’s economic development and gender equality, they have also led to the unbalanced development of marketisation across regions (Fan & Wang, 2010). We conjecture that there is also a large amount of gender inequality across regions in modern China. 4. Development of hypotheses Psychological research (mainly from the US) suggests that women surpass men in terms of work attitudes, ethical codes, decision making and risk aversion. First, women on corporate boards have been shown to be more diligent and independent than their male counterparts (Adams & Ferreira, 2009; Carter et al., 2003). Second, women are found to adhere more strictly to ethical codes than men and to be less tolerant of China Journal of Accounting Studies 327 opportunistic behaviour, which makes their monitoring activities more rigorous (Ambrose & Schminke, 1999; Krishnan & Parsons, 2008; Thorne, Massey, & Magnan, 2003), and, in our opinion, makes it more difﬁcult to pass a decision on inefﬁcient investment. Third, female directors have been shown to enrich the diversity of opinions and information available to a board and to improve the quality of its decision making (Gul, Srinidhi, & Ng, 2011; Rose, 2007). We speculate that the enriched information can improve investment efﬁciency, and provide a timely prohibition on inefﬁcient investment projects. Fourth, women are claimed to be less likely than men to exhibit overconﬁdence, especially in male-dominated areas (Barber & Odean, 2001; Beyer & Bowden, 1997), which can reduce the ﬁrm’s over-investment (Malmendier & Tate, 2005). We may argue that the prior evidence in the literature on these four ‘female’ personality traits suggests that female directors can help to improve investment efﬁ- ciency. However, we also suggest that women possess certain gender-related traits that may negatively inﬂuence investment efﬁciency. Under the inﬂuence of Confucian culture in the long run, women are more passive, obedient and conservative than men (Wang, 2005). We suggest that such traits may turn women into ‘rubber stamps’ rather than corporate board activists and, as a result, female directors of Chinese boards may weaken board governance, exacerbate the opportunistic behaviour and thus contribute to more inefﬁcient investment. The foregoing analysis, based on our reasoning by analogy from prior research to the conditions in China, indicates that the presence of female directors may affect board governance either positively or negatively. When their ‘positive’ traits outweigh their ‘negative’ traits, an increase in the proportion of female directors may improve board governance and thus increase investment efﬁciency, or vice versa. However, whether female directors facilitate board governance or become ‘rubber stamps’ may depend on a ﬁrm’s speciﬁc organisational and institutional environments. We think that regional environment can inﬂuence female directors’ role in board governance by promoting gender equality or gender discrimination. Compared with regions with a lower level of market development, it is likely that regions with more developed markets accept the imperative of gender equality more rapidly and more pro- foundly. This would in turn undermine the Chinese tradition of ‘male dominance’ more fully in these regions. One of the reasons is that, according to Friedman (1962), market competition mechanisms have a greater resource allocation capability in regions with a higher level of market development, prompting the market to replace the contractual arrangements related to gender identity, thereby decreasing gender discrimination (or increasing gender equality) in the workplace. This is also because, we argue, enhanced gender equality in more marketised regions may help alleviate women’s aforementioned passive and obedient traits and enhance their positive qualities. In summary, we suggest that a stronger regional market environment can enhance gender equality, and the improved gender equality can enhance the ability of female directors to monitor inefﬁcient investment. Based on the above analysis, we put for- ward the following hypothesis. H1: Ceteris paribus, the association between female directors and investment inefﬁciency is lower in ﬁrms of stronger regional market environment. We next suggest that, as well as the regional environment, the organisational environ- ment (dictatorial or democratic) may have an important effect on female directors’ role in governance. According to Bebchuk and Fried (2003, 2004), the power concentration 328 Jin et al. of a corporate board may be inclined to make a submissive board. We argue that a dic- tatorial board environment is more likely to suppress women’s ‘positive’ personality traits and elicits more ‘negative’ traits, making it more difﬁcult for female directors to play a positive role in governance. In contrast, we suggest that as a democratic board emphasises equality and freedom, women’s ‘negative’ personality traits are more likely to be suppressed and their ‘positive’ traits foregrounded, helping female directors to play a positive role in governance. A ﬁrm’s capital investment decisions are inﬂuenced by information and agency problems (Stein, 2003). A democratic board is more recep- tive to a variety of opinions, which improves the monitoring role of female directors and reduces agency problems, thereby enhancing investment efﬁciency. At the same time, a democratic board’s openness also encourages female directors to provide more information, which helps improve board decision making and thus reduce inefﬁcient investment. Based on the above analysis, we put forward the following hypothesis. H2: Ceteris paribus, the association between female directors and investment inefﬁciency is lower in ﬁrms of lower power concentration. 5. Methodology 5.1. Model speciﬁcation and variable deﬁnition To test our hypotheses, we construct Model (1) to investigate the effects of market development and power concentration on the association between female directors and investment inefﬁciency. Investment inefficiency ¼ a þ b1 Female director þ b2 Marketisation þ b3 Power concentration þ b4 Marketisation Female director þ b5 Power concentration Female director þ Control Varibles þ e (1) In Model (1), the dependent variable Investment_inefﬁciency refers to investment inefﬁ- ciency. The main independent variables are Female_director, Marketisation and Power_concentration. Female_director is the percentage of female directors (Female_director_ratio) or the number of female directors (Female_director_no) on the board. Marketisation is the market development level of the region in which the ﬁrm is located, which is a dummy variable equal to 1 if the market development index is higher than the median, and 0 otherwise. Power_concentration is the power concentra- tion of the corporate board, which is a dummy variable equal to 0 if the CEO and chairman are the same person, the largest shareholder holds more than 50% of the shares or the board size is less than seven people. Otherwise, Power_concentration equals 1. We also use several important control variables, as documented in prior stud- ies. The variables used in Model (1) are deﬁned in Table 1. Based on our theoretical analysis and hypotheses, we predict that the coefﬁcients of and will be signiﬁcantly negative. The measurement of investment efﬁciency and the selection of the control variables are described in detail as follows. 5.1.1. Measurement of investment efﬁciency We use Richardson’s(2006) approach to estimate corporate capital investment efﬁ- ciency. We run equation (2) to obtain the regression residuals (the unexplained portion). Residuals with positive and negative values refer to under- and over-investment, China Journal of Accounting Studies 329 Table 1. Variable deﬁnitions. Variables Deﬁnition Dependent variables Investment_inefﬁciency_1 Capital investment efﬁciency, equal to the absolute value of the residuals from Model (1), in which Growth is t–1 equal to Tobin’s Q. A higher Investment_inefﬁciency_1 means a lower investment efﬁciency. Investment_inefﬁciency_2 Capital investment efﬁciency, equal to the absolute value of the residuals from Model (1), in which Growth is t–1 equal to sales growth. A higher Investment_inefﬁciency_2 means a lower investment efﬁciency. Main independent variables Female_director_ratio The percentage of female directors = the number of female directors/the number of directors on the board. Female_director_no The number of female directors on the board. Marketisation Market development level, a dummy variable that equals 1 if the marketisation index is higher than the median, which means the good market environment, and 0 otherwise. Power_concentration Power concentration level, a dummy variable that equals 0 if the CEO and chairman are the same person, the largest shareholder holds more than 50% of the shares or the board size is less than seven people, which means a dictatorial board. Otherwise, it equals 1. Control variables Education The variable is deﬁned as 1 (high educational background) if the mean degree-ranking score of the ﬁrm’s female directors is higher than that of its male directors, and 0 (low educational background) otherwise. We rank the degree of each director as follows: 1=high school or below; 2=junior college; 3=Bachelor’s degree; 4= Master’s degree; 5= PhD; and 0=no clear disclosure of degree. Qualiﬁcation_experience The variable is deﬁned in two dimensions: age and position. It equals 1 (high seniority) if the female directors’ mean age is higher than that of the male directors and the female directors’ positions are not lower than those of the vice-chairman or deputy CEO. Otherwise, it equals 0(low seniority). Board_size Board size, equal to ln(the number of directors on the board). Firm_size Firm size, the natural log of the ﬁrm’s total assets. Leverage Leverage, equal to total liabilities/total assets. ROA Proﬁtability, i.e. the return on assets, equal to (income before tax+ﬁnancial expense)/total assets. State_ownership The nature of the ﬁrm’s ownership, a dummy variable equal to 1 if the ﬁrm is state-owned, and 0 otherwise. Ownership_centralisation Ownership centralization, i.e. the percentage of shares held by the largest shareholders. Ownership_balance Checks and balances of ownership, equal to the percentage of shares held by the second to the ﬁfth largest shareholders/the percentage of shares held by the largest shareholders. Board_independence Board independence, i.e. the percentage of independent directors. (Continued) 330 Jin et al. Table 1. (Continued). Variables Deﬁnition Duality CEO duality, a dummy variable equal to 1 if the CEO and board chairman are the same person, and 0 otherwise. Growth Growth, equal to sales growth. Free_cashﬂow Free cash ﬂow, equal to net income + interest expense + non-cash expenditure - change in working capital - capital expenditure. Firm_age Firm age, i.e., the number of years since the ﬁrm’s listing. ROA_1 One period lagged ROA. Growth_1 One period lagged Growth. Free_cashﬂow_1 One period lagged Free_cashﬂow. Whether Tobin’s Q can proxy for growth opportunity depends on market efﬁciency. Therefore, we also use sales growth to represent growth opportunity. Fan and Wang (2010) calculate the marketisation index. However, they only provide data up to 2007. As no signiﬁcant difference exists between the indexes of adjacent years, we take the average marketisation index from 2006 and 2007 as the estimated marketisation index of the years after 2007. In addition, we use a dummy variable to measure the marketisation. The reason is as follows: during the period of Chinese marketised reform, the degree of marketisation is only greatly different between the coastal and inland regions. For example, the coastal regions such as Guangdong, Zhejiang, Jiangsu, Shanghai, Fujian, Tianjin have a far higher marketisation index than inland regions. The marketi- sation indexes of the inland regions are similar. Therefore, we use a dummy variable to measure the marketisation of each region. China Journal of Accounting Studies 331 respectively. Both under-investment and over-investment are forms of inefﬁcient corporate investment behaviour. Therefore, we use the absolute value of the residuals to measure investment efﬁciency. Investment ¼ a þ b1 Growth þ b2 Leverage þ b3 Cash balance t t1 t1 t1 þb4 Firm age þ b5 Firm size þ b6 Stock return (2) t1 t1 t1 þb7 Investment þ RIndustry þ RYear þ e t1 t In Model (2), the dependent variable Investment denotes the ﬂow of capital investment in year t. Growth measures the growth opportunity using Tobin’s Q at the end of t–1 year t–1 or the sales growth in year t–1. Leverage , Cash_balance , Firm_age , t–1 t–1 t–1 Firm_size , Stock_return and Investment denote leverage, cash balance, ﬁrm age, t–1 t–1 t–1 ﬁrm size, stock return and capital investment in year t–1, respectively. We also use industry and year dummies in Model (2) to control for industry and year effects. 5.1.2. Selection of control variables As female directors’ educational background and qualiﬁcations and experiences may correlate with the percentage of female directors and investment efﬁciency, indicators of these characteristics (Education and Qualiﬁcation_experience, respectively) are added to Model (1) as control variables. We also use indicators of board characteristics, such as board size (Board_size) and the percentage of independent directors (Board_independence), as control variables. Board size is negatively related to the efﬁciency of decision-making because of coordi- nation problems and director free-riding (Jensen, 1993; Lipton & Lorsch, 1992), which will inﬂuence the ﬁrm’s investment efﬁciency. The independent director mechanism is designed to improve the monitoring capability of corporate boards and its effectiveness is documented in prior studies (Wang, Zhao, & Wei, 2006; Wu, Liu, & Fan, 2001). Therefore, we control for these variables in Model (1). Indicators of ﬁrm fundamentals, such as ﬁrm size (Firm_size), leverage (Leverage), proﬁtability (ROA) and age (Firm_age), are also used as control variables. First, larger ﬁrms that possess more resources are more likely to invest inefﬁciently. However, lar- ger ﬁrms also face stricter monitoring as a result of greater market attention. Second, highly leveraged ﬁrms are more strictly supervised by ﬁnancial institutions and thus less likely to invest inefﬁciently. However, such supervision may be effective in a developed market but ineffective in the Chinese market, which is characterised by a defective legal system, a government-led bank and government-oriented companies. Third, a ﬁrm’s proﬁtability may affect its capital investment efﬁciency, because capital investment is related to cash ﬂow (Richardson, 2006), which is in turn related to ﬁrm proﬁtability. Finally, in our opinion, ﬁrms with longer listing histories may attract more attention from market participants and stakeholders and thus are under more monitor- ing, which can reduce their inefﬁcient investment. Therefore, to reduce the problem of omitted variables, we control for ﬁrm size, leverage, proﬁtability and age in our model. Indicators of corporate governance, such as the nature of ownership (State_owner- ship), ownership centralisation (Ownership_centralisation), checks and balances of ownership (Ownership_balance) and CEO duality (Duality), are also used as control variables. First, state-owned enterprises are more likely than private ﬁrms to invest inef- ﬁciently, due to the former’s ‘absence of owners’ and pursuit of social objectives (e.g., Xin, Lin, & Yang, 2007). Second, the agency problem of the controlling shareholder is more pronounced in ﬁrms characterised by strong ownership centralisation, which 332 Jin et al. Table 2. Sample distribution. Panel A:Year composition 2005 2006 2007 2008 2009 2010 Total N 1,022 1,077 1,073 1,082 1,251 1,352 6,857 Percent (%) 14.90 15.71 15.65 15.78 18.24 19.72 100 Panel B: Industry composition N Percent (%) Agriculture, forestry, livestock farming, ﬁshery 135 1.97 Mining 164 2.39 Manufacturing – electronics 298 4.35 Manufacturing – textiles and clothing 263 3.84 Manufacturing – machinery and apparel 1,050 15.31 Manufacturing – metals and non-metals 562 8.20 Manufacturing – timber and furnishings 19 0.28 Manufacturing – other manufacturing 54 0.79 Manufacturing – petrochemicals and plastomers 694 10.12 Manufacturing – food and beverages 307 4.48 Manufacturing – medical and pharmaceuticals 488 7.12 Manufacturing – paper-making and printing 105 1.53 Electric power, steam and hot water production 331 4.83 and supply Construction 134 1.95 Transportation and storage 271 3.95 Information technology industry 342 4.99 Wholesale and retail trade 538 7.85 Real estate 559 8.15 Social services 205 2.99 Communication and cultural industry 79 1.15 Comprehensive 259 3.78 Total 6,857 100.00 diminishes corporate investment efﬁciency. In contrast, greater checks and balances of ownership ensure that the controlling shareholder is more closely monitored, which improves investment efﬁciency. Third, CEO duality means that the CEO has greater power over corporate decisions and thus ﬁnds it easier to exhibit opportunistic invest- ment behaviour. Therefore, we also control for these variables in Model (1). Finally, we control for free cash ﬂow (Free_cashﬂow) and growth (Growth). Free cash ﬂow can increase agency costs by triggering inefﬁcient investment (Jensen, 1986). Furthermore, strong growth may encourage over-investment and weak growth may lead to under-investment. Therefore, we add these control variables to Model (1). 5.2. Sample selection Our initial sample comprises all of the non-ﬁnancial A-share listed companies in China from 2005 to 2010. After excluding ﬁrms with leverage greater than 1 and ﬁrms with omitted data, we obtain 6,857 observations, with 1,022, 1,077, 1,073, 1,082, 1,251 and 1,352 annual observations for 2005 to 2010, respectively. The distribution of the sam- ple by year and industry is described in detail in Table 2. Panel A of Table 2 presents the yearly distribution of the sample during 2005–2010. Panel B of Table 2 summarises China Journal of Accounting Studies 333 the industry distribution and shows that more than half of the ﬁrms in our sample are in the manufacturing industry, followed by the real estate and information technology industries. This ranking is fairly representative of listed ﬁrms in China. We winsorise some of the continuous variables in their bottom and top 1% to miti- gate the problem of extreme values. The data relating to female directors are down- loaded from the China Stock Market and Accounting Research database and processed manually. The data concerning individual ﬁrms’ ﬁnancial conditions and corporate gov- ernance are obtained from the same database. 5.3. Descriptive statistics and correlation analysis Table 3 presents the descriptive statistics for the whole sample and sub-samples. Panel A shows that the mean and median of Investment_inefﬁciency_1 in the full sample are 0.069 and 0.044, respectively. The percentage of female directors (Female_direc- tor_ratio) in our sample is about 10%, which is slightly higher than the 8.87% documented by Adams and Ferreira (2009). The values of Firm_size, Leverage, ROA, State_ownership, Ownership_centralisation, Ownership_balance, Board_size, Board_independence, Duality, Free_cashﬂow, Growth and Firm_age are also reasonable. We ﬁnd that 37% of the companies in the sample have no female director, while 38% of the companies in the sample have only one female director. To distinguish between the high Female_director_ratio and low Female_director_ratio, we split the sample by thirds. We further divide the whole sample into two sub-samples according to whether Female_director_ratio (the percentage of female directors) is in the top third (Panel B) or the bottom two thirds (Panel C). In Panel D, we compare the differences in the mean and median between the variables from the two groups. Panel B and Panel C present the descriptive statistics for the sub-samples with a higher Female_direc- tor_ratio value (22.3%) and a lower Female_director_ratio value (4.55%), respectively. Panels B, C and D show that Investment_inefﬁciency_1 is signiﬁcantly higher in the group with lower Female_director_ratio, which means that investment efﬁciency is sig- niﬁcantly lower in ﬁrms with a higher percentage of female directors. In addition, the means of Firm_size, Ownership_centralisation, Board_size, Free_cashﬂow and Growth are signiﬁcantly lower in ﬁrms with a higher percentage of female directors, suggesting that these ﬁrms have a smaller size, a lower ownership concentration, a smaller board, a smaller free cash ﬂow and less sales growth. In ﬁrms with a higher percentage of female directors, the means of State_ownership, Ownership_balance, Board_indepen- dence, Duality and Firm_age are also signiﬁcantly higher, suggesting that these ﬁrms are more likely to be older and state-owned, with greater checks and balances of own- ership and a larger ratio of independent directors. In these ﬁrms, the CEO and board chairman are also likely to be the same person. The signiﬁcant differences in the ﬁrm characteristic variables between the two groups highlight the importance of controlling for these variables when regressing investment efﬁciency on the proportion of female directors. Table 4 presents a correlation matrix for the main variables. Female_director_ratio is positively correlated with Investment_inefﬁciency_1, preliminarily showing that a higher proportion of female directors is associated with a higher capital investment inefﬁciency in our whole sample. In addition, the results show that Female_direc- tor_ratio is signiﬁcantly correlated with other ﬁrm characteristic variables, which is consistent with the descriptive statistics displayed in Table 3. Lastly, the correlation coefﬁcients between the ﬁrm characteristic variables are reasonable. 334 Jin et al. Table 3. Descriptive statistics. Mean Variance Minimum Median Maximum Panel A: Full sample Investment_inefﬁciency_1 0.069 0.082 0.000 0.044 0.615 Female_director_ratio 0.104 0.105 0.000 0.111 0.667 Firm_size 21.603 1.144 17.495 21.496 27.301 Leverage 0.514 0.187 0.002 0.526 1.000 ROA 0.058 0.069 –0.177 0.053 0.292 State_ownership 0.352 0.478 0.000 0.000 1.000 Ownership_centralisation 0.364 0.153 0.035 0.343 0.852 Ownership_balance 0.537 0.522 0.013 0.359 2.435 Board_size 2.231 0.214 1.386 2.197 3.045 Board-independence 0.359 0.049 0.083 0.333 0.667 Duality 0.135 0.342 0.000 0.000 1.000 Free_cashﬂow 0.051 0.137 -0.677 0.062 0.389 Growth 0.217 0.589 -0.847 0.133 4.740 Firm_age 9.688 3.960 1.181 9.715 20.071 Panel B: Sub-sample for high Female_director_ratio Investment_inefﬁciency_1 0.073 0.085 0.000 0.046 0.615 Female_director_ratio 0.223 0.084 0.118 0.222 0.667 Firm_size 21.421 1.085 17.908 21.357 26.099 Leverage 0.511 0.187 0.002 0.523 1.000 ROA 0.057 0.068 –0.177 0.051 0.292 State_ownership 0.437 0.496 0.000 0.000 1.000 Ownership_centralisation 0.346 0.150 0.035 0.316 0.852 Ownership_balance 0.567 0.542 0.013 0.390 2.435 Board_size 2.194 0.242 1.386 2.197 3.045 Board-independence 0.364 0.053 0.083 0.333 0.625 Duality 0.176 0.381 0.000 0.000 1.000 Free_cashﬂow 0.045 0.141 –0.677 0.058 0.389 Growth 0.187 0.572 –0.847 0.118 4.740 Firm_age 9.968 4.093 2.016 10.125 20.071 Panel C: Sub-sample for low Female_director_ratio Investment_inefﬁciency_1 0.068 0.080 0.000 0.044 0.588 FD_ratio 0.046 0.051 0.000 0.000 0.111 Firm_size 21.691 1.162 17.495 21.572 27.301 Leverage 0.515 0.187 0.009 0.528 1.000 ROA 0.059 0.069 –0.177 0.054 0.292 State_ownership 0.311 0.463 0.000 0.000 1.000 Ownership_centralisation 0.373 0.154 0.045 0.358 0.852 Ownership_balance 0.522 0.512 0.013 0.339 2.435 Board_size 2.249 0.196 1.386 2.197 3.045 Board-independence 0.356 0.047 0.111 0.333 0.667 Duality 0.116 0.320 0.000 0.000 1.000 Free_cashﬂow 0.054 0.135 –0.677 0.064 0.389 Growth 0.232 0.597 –0.847 0.141 4.740 Firm_age 9.552 3.887 1.181 9.575 20.047 Panel D: Difference comparison of variables (mean and median) ΔMean=high-low T-value ΔMedian=high-low Z-value Investment_inefﬁciency_1 0.005 2.485** 0.002 1.986** Firm_size –0.271 –9.241*** –0.215 –8.479*** (Continued) China Journal of Accounting Studies 335 Table 3. (Continued). Leverage –0.005 –0.960 –0.005 –0.965 ROA –0.002 –1.245 –0.002 –1.468 State_ownership 0.125 10.256*** 0.000 10.179*** Ownership_centralisation –0.028 –6.994*** –0.042 –7.083*** Ownership_balance 0.046 3.409*** 0.051 3.513*** Board_size –0.055 –10.139*** 0.000 –12.195*** Board-independence 0.008 6.253*** 0.000 7.891*** Duality 0.060 6.807*** 0.000 6.784*** Free_cashﬂow –0.009 –3.865*** –0.006 –4.086*** Growth –0.045 –2.973*** –0.023 –3.956*** Firm_age 0.417 4.089*** 0.549 4.221*** Notes: (1) Refer to Table 1 for the deﬁnition of variables. (2) ***, ** and * represent signiﬁcance at the 1%, 5% and 10% levels, respectively. 6. Empirical results: regression analyses We conduct two types of hypothesis test. First, we investigate the effect of market envi- ronment (or power concentration) on the relationship between female directors and investment efﬁciency by adding two interaction terms, Female_director_ratio×Marketi- sation and Female_director_ratio×Power_concentration, to our main model. Second, we divide the whole sample into two groups according to regional market development or ﬁrm power concentration and examine the relationship between female directors and investment efﬁciency in each of these two groups. To increase the reliability of our results, we construct two measures of investment efﬁciency and two measures of the proportion of female directors in our regressions. The regression results are reported in Tables 5–8. In Table 5, the dependent variable is corporate investment efﬁciency, measured by Investment_inefﬁciency_1, and the independent variables of interest are Female_direc- tor_ratio, Female_director_ratio × Marketisation and Female_director_ratio × Power_concentration. The results displayed in column (1) show that the coefﬁcient of Female_director_ratio is positive and signiﬁcant at the 1% level, suggesting that a higher proportion of female directors is associated with a lower level of investment efﬁ- ciency in regions with less developed markets, and in ﬁrms whose corporate boards have a higher power concentration. The coefﬁcient of Female_director_ratio×Marketi- sation is negative and signiﬁcant at the 5% level, indicating that a higher level of mar- ket development is capable of weakening the negative effect of female directors on investment efﬁciency. The coefﬁcient of Female_director_ratio×Power_concentration is negative and signiﬁcant at the 10% level, indicating that a lower power concentration can weaken the negative effect of female directors on investment efﬁciency. The coefﬁ- cient Female_director_ratio is positive in both columns (2) and (3), but this result is only signiﬁcant in column (3), suggesting that the effect of female directors on invest- ment efﬁciency is dependent on the market environment and that the negative effect of female directors on investment efﬁciency only exists in ﬁrms located in regions with less developed markets. The coefﬁcient Female_director_ratio is positive in both col- umns (4) and (5), but is only signiﬁcant in column (5), suggesting that the effect of female directors on investment efﬁciency is also dependent on the organisational envi- ronment and that the negative effect of female directors on investment efﬁciency only exists in corporate boards with a higher power concentration. With regard to the control variables, the coefﬁcients for State_ownership, Ownership_centralisation, Owner- ship_balance and Firm_age are positive and signiﬁcant in almost all of the columns, which suggests that state-owned ﬁrms, ﬁrms with more concentrated ownership, ﬁrms 336 Jin et al. Table 4. Correlation analysis. Variables 1 2 34567 89 10 11 12 13 1. Investment_inefﬁciency_1 1.000 2. Female_director_ratio 0.019 1.000 3. Board_size –0.003 –0.061*** 1.000 4. Firm_size 0.013 –0.123*** 0.234*** 1.000 5. Leverage –0.004 –0.012 0.073*** 0.259*** 1.000 6. Roa 0.028** 0.003 0.037*** 0.191*** –0.272*** 1.000 7. State_ownership –0.008 0.133*** –0.194*** –0.250*** –0.060*** 0.046*** 1.000 8. Ownership_centralisation 0.048*** –0.099*** 0.016 0.272*** –0.004 0.116*** –0.237*** 1.000 9. Ownership_balance 0.003 0.039*** 0.071*** –0.166*** –0.033*** –0.007 0.206*** –0.648*** 1.000 10. Board-independence –0.010 –0.018 –0.265*** 0.037*** –0.006 –0.017 0.074*** –0.013 0.003 1.000 11. Duality –0.026 0.066*** –0.101*** –0.102*** –0.054*** 0.002 0.147*** –0.095*** 0.063*** 0.048*** 1.000 12. Growth_1 –0.000 –0.028 0.013 0.100*** 0.066*** 0.120*** 0.000 0.096*** –0.011 0.002 –0.013 1.000 13. Free_cashﬂow_1 0.034*** –0.045*** 0.062*** 0.037*** –0.028** 0.106*** –0.045*** 0.076*** –0.022* –0.047*** –0.016 –0.042*** 14. Firm_age 0.011 0.054*** –0.073*** 0.084*** 0.132*** –0.091*** –0.110*** –0.158*** –0.104*** 0.034*** –0.049*** –0.035*** –0.015*** Notes: (1) Refer to Table 1 for the deﬁnition of variables. (2) ***, ** and * represent signiﬁcance at the 1%, 5% and 10% levels, respectively. China Journal of Accounting Studies 337 Table 5. Female directors and investment efﬁciency: The effects of market development and power concentration. Dependent variable: Investment_inefﬁciency_1 Variables （1）（2）（3）（4）（5） INTERCEPT 0.077*** 0.116*** –0.110 0.087** 0.076* (2.69) (3.67) (–1.59) (2.21) (1.85) Female_director_ratio 0.097*** 0.015 0.073*** 0.016 0.041** (3.34) (1.06) (2.75) (0.98) (2.36) Marketisation –0.000 –0.010*** –0.002 (–0.08) (–2.69) (–0.39) Power_concentration –0.001 –0.006 0.002 (–0.23) (–1.60) (0.26) Female_director_ratio× –0.062** Marketisation (–2.19) Female_director_ratio× –0.037* Power_concentration (–1.67) Qualiﬁcation_experience –0.003 –0.005 0.003 –0.005 0.002 (–0.65) (–1.00) (0.37) (–1.11) (0.31) Education –0.001 0.000 –0.002 –0.002 0.002 (–0.22) (0.01) (–0.24) (–0.64) (0.39) Board_size –0.008 –0.007 –0.014 –0.015* –0.003 (–1.44) (–1.09) (–1.07) (–1.65) (–0.42) Firm_size –0.002 –0.004** 0.008** –0.000 –0.003 (–1.22) (–2.22) (2.23) (–0.16) (–1.52) Leverage 0.001 –0.001 0.002 –0.011 0.017 (0.17) (–0.12) (0.14) (–1.00) (1.50) ROA 0.020 0.019 0.010 0.005 0.033 (0.85) (0.63) (0.24) (0.15) (0.92) State_ownership 0.006*** 0.005* 0.009* 0.004 0.009** (2.58) (1.86) (1.77) (1.39) (2.25) Ownership_centralisation 0.048*** 0.044*** 0.063* 0.045** 0.048** (3.45) (2.99) (1.78) (2.19) (2.42) Board-independence –0.018 –0.008 –0.042 –0.057* 0.028 (–0.73) (–0.26) (–1.05) (–1.80) (0.81) Ownership_balance 0.012*** 0.011*** 0.014* 0.011*** 0.012** (3.45) (2.96) (1.85) (2.72) (2.10) Duality –0.008** –0.007 –0.005 0.000 –0.007* (–2.09) (–1.65) (–0.60) (0.000) (–1.93) Growth_1 –0.000 –0.001 0.002 0.000 –0.001 (–0.17) (–0.57) (0.49) (0.16) (–0.60) ROA_1 –0.035 –0.017 –0.109** –0.047 –0.027 (–1.37) (–0.54) (–2.40) (–1.41) (–0.67) Free_cashﬂow_1 –0.000 –0.004 0.013 0.003 –0.004 (–0.04) (–0.38) (0.90) (0.33) (–0.29) Firm_age 0.001*** 0.001*** –0.000 0.001** 0.001*** (3.09) (3.26) (–0.02) (2.38) (2.59) Industry dummy Yes Yes Yes Yes Yes Year dummy Yes Yes Yes Yes Yes Adj. R 0.059 0.062 0.053 0.055 0.069 N 6,857 5,172 1,685 3,996 2,861 Notes: (1) The data used in column (1) represent the full sample. The sub-samples in columns (2) and (3) are ‘Marketisation =1’and ‘Marketisation =0’, respectively. The sub-samples in columns (4) and (5) are respec- tively ‘Power_concentration=1’ and ‘Power_concentration=0’. (2) Refer to Table 1 for the deﬁnition of variables. (3) All of the t-statistics, reported in brackets, are based on standard errors adjusted for heteroscedasticity and ﬁrm-level clustering. ***, ** and * represent signiﬁcance at the 1%, 5% and 10% levels, respectively. (4) The R-square of model is low. Zhu et al. (2012) study the relationship between female directors and cor- porate investment, their R-square is also about 0.05. 338 Jin et al. Table 6. Female directors and investment efﬁciency: The effects of market development and power concentration. Dependent variable: Investment_inefﬁciency_2 Variables （1）（2）（3）（4）（5） INTERCEPT 0.076*** 0.115*** –0.109 0.086** 0.077* (2.68) (3.66) (–1.57) (2.19) (1.88) Female_director_ratio 0.098*** 0.015 0.075*** 0.016 0.042** (3.37) (1.06) (2.83) (0.97) (2.40) Marketisation –0.000 –0.010*** –0.002 (–0.12) (–2.68) (–0.56) Power_concentration –0.001 –0.006 0.002 (–0.22) (–1.57) (0.22) Female_director_ratio× –0.063** Marketisation (–2.20) Female_director_ratio× –0.038* Power_concentration (–1.69) Qualiﬁcation_experience –0.003 –0.005 0.002 –0.005 0.002 (–0.66) (–0.97) (0.25) (–1.07) (0.24) Education –0.001 –0.000 –0.002 –0.003 0.002 (–0.31) (–0.01) (–0.36) (–0.72) (0.35) Board_size –0.009 –0.007 –0.014 –0.015 –0.004 (–1.48) (–1.14) (–1.11) (–1.62) (–0.54) Firm_size –0.002 –0.003** 0.008** –0.000 –0.003 (–1.17) (–2.16) (2.22) (–0.13) (–1.47) Leverage 0.000 –0.003 0.002 –0.013 0.015 (0.00) (–0.30) (0.12) (–1.12) (1.33) ROA 0.025 0.023 0.016 0.009 0.038 (1.07) (0.80) (0.40) (0.27) (1.09) State_ownership 0.007*** 0.005* 0.010* 0.005 0.009** (2.64) (1.90) (1.81) (1.48) (2.22) Ownership_centralisation 0.048*** 0.043*** 0.063* 0.045** 0.048** (3.45) (2.98) (1.77) (2.17) (2.49) Board-independence –0.017 –0.007 –0.041 –0.056* 0.028 (–0.70) (–0.24) (–1.02) (–1.78) (0.81) Ownership_balance 0.011*** 0.011*** 0.013* 0.011*** 0.013** (3.42) (3.00) (1.75) (2.65) (2.23) Duality –0.008** –0.007* –0.005 0.000 –0.008** (–2.14) (–1.70) (–0.62) . (–1.98) Growth_1 –0.001 –0.002 0.001 –0.000 –0.002 (–0.58) (–1.00) (0.36) (–0.07) (–0.93) ROA_1 –0.035 –0.018 –0.102** –0.049 –0.025 (–1.35) (–0.60) (–2.22) (–1.44) (–0.61) Free_cashﬂow_1 0.000 –0.004 0.013 0.002 –0.002 (0.00) (–0.37) (0.91) (0.21) (–0.13) Firm_age 0.001*** 0.001*** 0.000 0.001** 0.001** (3.11) (3.22) (0.09) (2.42) (2.56) Industry dummy Yes Yes Yes Yes Yes Year dummy Yes Yes Yes Yes Yes Adj. R 0.061 0.051 0.054 0.068 0.061 N 6,857 5,172 1,685 3,996 2,861 Notes: (1) The data provided in column (1) represent the full sample. The sub-samples in columns (2) and (3) are ‘Marketisation =1’ and ‘Marketisation =0’, respectively. The sub-samples in columns (4) and (5) are respectively ‘Power_concentration=1, and ‘Power_concentration=0’. (2) Refer to Table 1 for the deﬁnition of variables. (3) All of the t-statistics, reported in brackets, are based on standard errors adjusted for heteroscedasticity and ﬁrm-level clustering. ***, ** and * represent signiﬁcance at the 1%, 5% and 10% levels, respectively. China Journal of Accounting Studies 339 Table 7. Female directors and investment efﬁciency: The effects of market development and power concentration. Dependent variable: Investment_inefﬁciency_1 Variables （1）（2）（3）（4）（5） INTERCEPT 0.083*** 0.119*** –0.097 0.091** 0.085** (2.94) (3.83) (–1.40) (2.31) (2.09) Female_director_no 0.011*** 0.002 0.007*** 0.001 0.005*** (3.63) (1.14) (2.65) (0.92) (2.65) Marketisation –0.000 –0.010*** –0.002 (–0.13) (–2.69) (–0.40) Power_concentration 0.000 –0.006 0.002 (0.05) (–1.58) (0.27) Female_director_ no×Marketisation –0.006** (–2.18) Female_director_ –0.005** no×Power_concentration (–2.23) Qualiﬁcation_experience –0.003 –0.005 0.004 –0.005 0.002 (–0.69) (–1.02) (0.38) (–1.08) (0.24) Education –0.001 0.000 –0.001 –0.002 0.002 (–0.22) (0.00) (–0.17) (–0.61) (0.34) Board_size –0.012** –0.009 –0.021 –0.017* –0.008 (–2.04) (–1.33) (–1.57) (–1.80) (–1.04) Firm_size –0.002 –0.004** 0.008** –0.000 –0.003 (–1.18) (–2.21) (2.26) (–0.16) (–1.48) Leverage 0.001 –0.001 0.002 –0.011 0.017 (0.15) (–0.12) (0.13) (–1.00) (1.46) ROA 0.020 0.019 0.011 0.005 0.033 (0.84) (0.64) (0.26) (0.15) (0.92) State_ownership 0.006*** 0.005* 0.009* 0.004 0.009** (2.59) (1.86) (1.78) (1.40) (2.22) Ownership_centralisation 0.047*** 0.044*** 0.062* 0.045** 0.048** (3.37) (3.00) (1.75) (2.18) (2.44) Board-independence –0.016 –0.008 –0.042 –0.057* 0.028 (–0.65) (–0.26) (–1.04) (–1.80) (0.81) Ownership_balance 0.011*** 0.011*** 0.013* 0.011*** 0.012** (3.40) (2.96) (1.80) (2.71) (2.12) Duality –0.008** –0.007 –0.005 0.000 –0.008** (–2.22) (–1.64) (–0.59) . (–1.97) Growth_1 –0.000 –0.001 0.002 0.000 –0.001 (–0.15) (–0.57) (0.46) (0.16) (–0.59) ROA_1 –0.036 –0.017 –0.109** –0.047 –0.027 (–1.38) (–0.54) (–2.38) (–1.41) (–0.67) Free_cashﬂow_1 –0.000 –0.004 0.013 0.003 –0.004 (–0.03) (–0.38) (0.92) (0.33) (–0.29) Firm_age 0.001*** 0.001*** –0.000 0.001** 0.001** (3.09) (3.24) (–0.04) (2.38) (2.57) Industry dummy Yes Yes Yes Yes Yes Year dummy Yes Yes Yes Yes Yes Adj. R 0.059 0.062 0.052 0.055 0.070 N 6,857 5,172 1,685 3,996 2,861 Notes: (1) Column (1) provides data on the full sample. The sub-samples in columns (2) and (3) are ‘Marketi- sation =1’ and ‘Marketisation =0’, respectively. The sub-samples in columns (4) and (5) are ‘Power_concen- tration=1’ and ‘Power_concentration=0’, respectively. (2) Refer to Table 1 for the deﬁnition of variables. (3) All of the t-statistics, reported in brackets, are based on standard errors adjusted for heteroscedasticity and ﬁrm-level clustering. ***, ** and * represent signiﬁcance at the 1%, 5% and 10% levels, respectively. 340 Jin et al. Table 8. Female directors and investment efﬁciency: The effect of market development and power concentration. Dependent variable: Investment_inefﬁciency_2 Variables （1）（2）（3）（4）（5） INTERCEPT 0.082*** 0.119*** –0.095 0.090** 0.085** (2.93) (3.82) (–1.37) (2.29) (2.12) Female_director_no 0.011*** 0.002 0.008*** 0.001 0.006*** (3.68) (1.15) (2.77) (0.92) (2.75) Marketisation –0.001 –0.010*** –0.002 (–0.17) (–2.68) (–0.57) Power_concentration 0.000 –0.006 0.002 (0.08) (–1.55) (0.24) Female_director_no× –0.006** Marketisation (–2.21) Female_director_no× –0.005** Power_concentration (–2.26) Qualiﬁcation_experience –0.003 –0.005 0.002 –0.005 0.001 (–0.72) (–0.99) (0.26) (–1.04) (0.17) Education –0.001 –0.000 –0.002 –0.003 0.002 (–0.32) (–0.03) (–0.31) (–0.70) (0.30) Board_size –0.012** –0.009 –0.021 –0.016* –0.009 (–2.10) (–1.38) (–1.62) (–1.78) (–1.18) Firm_size –0.002 –0.003** 0.008** –0.000 –0.003 (–1.12) (–2.15) (2.24) (–0.13) (–1.43) Leverage –0.000 –0.003 0.002 –0.013 0.015 (–0.02) (–0.30) (0.11) (–1.12) (1.29) ROA 0.025 0.023 0.017 0.009 0.038 (1.06) (0.80) (0.42) (0.28) (1.09) State_ownership 0.007*** 0.005* 0.010* 0.005 0.009** (2.64) (1.89) (1.82) (1.49) (2.18) Ownership_centralisation 0.047*** 0.043*** 0.062* 0.045** 0.049** (3.37) (2.99) (1.74) (2.17) (2.51) Board-independence –0.015 –0.007 –0.041 –0.056* 0.028 (–0.62) (–0.24) (–1.02) (–1.78) (0.82) Ownership_balance 0.011*** 0.011*** 0.013* 0.011*** 0.013** (3.38) (3.00) (1.70) (2.63) (2.25) Duality –0.008** –0.007* –0.005 0.000 –0.008** (–2.27) (–1.69) (–0.61) . (–2.02) Growth_1 –0.001 –0.002 0.001 –0.000 –0.002 (–0.56) (–1.00) (0.34) (–0.07) (–0.91) ROA_1 –0.035 –0.018 –0.101** –0.049 –0.024 (–1.36) (–0.60) (–2.21) (–1.44) (–0.61) Free_cashﬂow_1 0.000 –0.004 0.013 0.002 –0.002 (0.01) (–0.37) (0.93) (0.21) (–0.13) Firm_age 0.001*** 0.001*** 0.000 0.001** 0.001** (3.10) (3.20) (0.07) (2.43) (2.53) Industry dummy Yes Yes Yes Yes Yes Year dummy Yes Yes Yes Yes Yes Adj. R 0.058 0.061 0.050 0.054 0.068 N 6,857 5,172 1,685 3,996 2,861 Notes: (1) Column (1) provides data on the full sample. The sub-samples in columns (2) and (3) are ‘Marketi- sation =1’ and ‘Marketisation =0’, respectively. The sub-samples in columns (4) and (5) are ‘Power_concen- tration=1’ and ‘Power_concentration=0’, respectively. (2) Refer to Table 1 for the deﬁnition of variables. (3) All of the t-statistics, reported in brackets, are based on standard errors adjusted for heteroscedasticity and ﬁrm-level clustering. ***, ** and * represent signiﬁcance at the 1%, 5% and 10% levels, respectively. China Journal of Accounting Studies 341 with greater checks and balances of ownership and older ﬁrms have a lower level of investment efﬁciency. 7. Empirical results: Robustness checks In Table 6, we use Investment_inefﬁciency_2 instead of Investment_inefﬁciency_1 as the dependent variable. All of the independent variables in Table 6 are the same as those in Table 5. The results in column (1) show that the coefﬁcient of Female_direc- tor_ratio is positive and signiﬁcant at the 1% level, the coefﬁcient of Female_direc- tor_ratio×Marketisation is negative and signiﬁcant at the 5% level, and the coefﬁcient of Female_director_ratio×Power_concentration is negative and signiﬁcant at the 10% level. The coefﬁcient of Female_director_ratio is positive in both columns (2) and (3), but only signiﬁcant in column (3). The coefﬁcient Female_director_ratio is positive in column (4) and in column (5), but only signiﬁcant in column (5). As a whole, the results presented in Table 6 are similar to those in Table 5, suggesting that our results are not affected by the use of different measures of investment efﬁciency. In Tables 7 and 8, we replace Female_director_ratio (the percentage of female directors) with Female_director_no (the number of female directors) and re-estimate the equations in Tables 5 and 6. The results are similar to those shown in Tables 5 and 6. Speciﬁcally, the results presented in Tables 7 and 8 show that a more developed mar- ket and a lower power concentration can weaken the negative effect of female directors on investment efﬁciency. We also ﬁnd that the negative relationship between female directors and investment efﬁciency only exists in regions with less developed markets and in ﬁrms with a higher power concentration. In summary, the results shown in Tables 5–8 are consistent with our two hypothe- ses, and are robust to different measures of investment efﬁciency and the proportion of female directors. The above results clearly show that the relationship between female directors and corporate investment efﬁciency depends on a ﬁrm’s regional market envi- ronment and its organisational environment. Although female directors in China are found to have, in general, a negative effect on investment efﬁciency, this negative effect is only observed in regions with less developed markets and in ﬁrms with a higher power concentration. Both a more developed regional market environment and a lower ﬁrm power concentration can weaken the negative effect of female directors on invest- ment efﬁciency. 8. Conclusions and implications Although an increasing number of studies have investigated the roles of female direc- tors in board governance, researchers have paid insufﬁcient attention to the effects of institutional environment and organisational environment on the inﬂuence of female directors. Using a sample of Chinese listed ﬁrms from 2005–2010, we investigate the effects of market environment and organisational environment on the relationship between female directors and investment efﬁciency in the institutional context of China. Overall, our results suggest that the relationship between female directors and corporate investment efﬁciency depends on ﬁrms’ regional market environment and on their organisational environment. A higher level of regional market development and a lower board power concentration can weaken the negative effect of female directors on investment efﬁciency. Although female directors in China are found in general to have 342 Jin et al. a negative effect on investment efﬁciency, this negative effect only exists in regions with less developed markets and in ﬁrms with a higher power concentration. The implications of our empirical ﬁndings are as follows. First, although several European countries such as Sweden, Norway and Spain have mandated quotas for female directors and some Western studies provide evidence of the positive role of female directors in board governance, our ﬁndings show that in the context of China, an increase in female directors not only fails to improve board governance, but under certain conditions has a negative effect. Therefore, the ﬁndings of this study indicate that governments must seriously consider local institutional environments before legally mandating that ﬁrms employ a speciﬁc number of female directors. Second, we show that gender discrimination continues to be an important social issue in China. Eliminat- ing gender discrimination is vital to building a harmonious society. Although women’s employment, revenue and promotion statistics have improved in recent years, we show that female directors still play negative roles in board governance and are given insufﬁ- cient power to monitor corporate boards. Therefore, the Chinese government should work to enhance women’s roles in corporate governance by establishing laws and regu- lations that ensure gender equality, and protect women’s rights. Third, as existing cor- porate governance studies pay insufﬁcient attention to the gender traits of directors, future researchers in this ﬁeld are advised to investigate the effects of female directors on board governance. Our ﬁndings suggest that whether a governance mechanism plays a positive role in a country depends on the country’s institutional environment. There- fore, it is important to consider the institutional environment when investigating the effect of female directors on board governance. Finally, it should be noted that a ﬁrm’s female director ratio is not exogenous because ﬁrms can choose whether or not to hire female directors. The endogeneity problem may affect the result of the relationship between female directors and investment efﬁciency. Acknowledgments We thank the joint editors (Liansheng Wu and Jason Xiao), the associated editor Tong Yu and the anonymous referees for their constructive comments and suggestions. Special thanks are given to Professor Jinsong Tan for his inspiring conversation. However, we are completely responsible for the content of this paper. We also acknowledge research support from the National Natural Science Foundation of China (‘The power structure of board of directors: Causes and consequences’ (Grant No. 71272196) and ‘The international convergence of account- ing standards and Chinese capital market: Institution, governance and market microstructure’ (Grant No. 71302185)); the Humanities and Social Science Foundation of the Ministry of Educa- tion (Grant No. 13YJC790060 and 14YJC790101); the Humanities and Social Science Founda- tion of Guangdong Province (Grant No. 2012JDXM-0002) and the innovation team on Chinese ﬁrms’ cost management based on international competitiveness (Grant No. JBK130508). Notes 1. For a detailed discussion of the studies by Adams and Ferreira (2009), Campbell et al. (2008), Carter et al. (2003), Erhardt et al. (2003), Hussein and Kiwia (2009) and Miller and Triana (2009), among others, please refer to the literature review in Section 2. 2. In terms of job devotion, female board directors are regarded as being more diligent than their male counterparts (Adams & Ferreira, 2009). In terms of business ethics, women are believed to adhere to ethical standards more strictly than men and to be less tolerant of opportunistic behaviour (Ambrose & Schminke 1999; Thorne, Massey, & Magnan, 2003). In addition, the presence of female directors is believed to increase the diversity of views and fullness of information available to the board, and thereby improve its decision making. China Journal of Accounting Studies 343 Therefore, researchers argue that the presence of women on a board can improve the board’s consultancy role and governance (Gul, Srinidhi, & Ng, 2011). 3. Many slogans were put forward during these three periods, such as the following: ‘females turn around’ and ‘females become masters’ in the 1950s; ‘females leave home for jobs’ and ‘liberating females’ during the Great Leap Forward (1958–1960); and ‘females make half of the dome’, ‘time for females’ and ‘gender equality’ during the Cultural Revolution (1966– 1976) (Jin, 2006). 4. Please refer to page 118 of Chapter 7, ‘Capitalism and Discrimination’, in Friedman’s (1962) Capitalism and Freedom. 5. Board size is limited to seven people for several reasons. First, according to Olson in The Logic of Collective Action (1965), small groups can be controlled more easily. Olson also refers to a study by James, who points out that such small groups usually comprise 6.5 peo- ple. 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China Journal of Accounting Studies
– Taylor & Francis
Published: Oct 2, 2014
Keywords: board governance; corporate investment; female directors; regional and organisational environment