Do women directors improve firm performance in China?

    Do Women Directors Improve Firm Performance in China? Yu Liu, Zuobao Wei, Feixue Xie PII: DOI: Reference:

S0929-1199(13)00123-5 doi: 10.1016/j.jcorpfin.2013.11.016 CORFIN 746

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Journal of Corporate Finance

Received date: Revised date: Accepted date:

4 October 2013 22 November 2013 25 November 2013

Please cite this article as: Liu, Yu, Wei, Zuobao, Xie, Feixue, Do Women Directors Improve Firm Performance in China?, Journal of Corporate Finance (2013), doi: 10.1016/j.jcorpfin.2013.11.016

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Do Women Directors Improve Firm Performance in China?

Yu Liu*, Zuobao Wei, Feixue Xie

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College of Business, University of Texas at El Paso, El Paso, Texas, USA

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Abstract

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This paper examines the effect of board gender diversity on firm performance in China's listed firms from 1999 to 2011. We document a positive and significant relation between board gender diversity and firm performance. Female executive directors have a stronger positive effect on firm performance than female independent directors, indicating that the executive effect outweighs the monitoring effect. Moreover, boards with three or more female directors have a stronger impact on firm performance than boards with two or fewer female directors, consistent with the critical mass theory. Finally, we find that the impact of female directors on firm performance is significant in legal person-controlled firms but insignificant in state-controlled firms. This paper sheds new light on China's boardroom dynamics. As governments increasingly contemplate board gender diversity policies, our study offers useful empirical guidance to Chinese regulators on the issue.

Highlights

The fraction of female directors has a positive impact on firm performance in China. Female executive/independent directors have different impacts on firm performance. The absolute number of female directors also matters. Legal person-controlled firms are more likely to benefit from female directors. State-controlled firms are less likely to benefit from female directors.

JEL Classification G30; G34; J16 Keywords Women directors; Gender diversity; Firm performance; Ownership structure; China

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ACCEPTED MANUSCRIPT * Corresponding author. Address: Room 239, College of Business, University of Texas at El Paso, El Paso, Texas 79968, USA. Tel: 1-915-747-7728; Email: [email protected] (Yu Liu).

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1. Introduction

“What if Lehman Brothers had been Lehman Sisters?”

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Christine Lagarde, IMF Managing Director

After recent corporate scandals and financial crises, an important question has been

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raised: would things have been different if more women were running the corporations in the

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U.S. and around the world (Adams and Funk, 2012)? There are reasons to believe that the answer might be affirmative. Existing empirical evidence shows that female executives are more

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cautious than male executives in making important corporate decisions (Huang and Kisgen, 2013; Levi et al., 2014-this issue). Female board directors are more diligent monitors and

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demand more audit efforts than male directors (Adams and Ferreira, 2009; Gul et al., 2008). In

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addition, female directors bring different perspectives and experiences into the boardroom, which help improve the quality of board decisions and enhance the legitimacy of firm practices

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(Hillman et al., 2007). Gender-diverse boards could also partially offset weak corporate governance (Gul et al., 2011). With these arguments, many European countries are encouraging or even mandating public companies to add more women to their boards.1 However, can genderdiverse boards lead to improved firm performance?

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For instance, in 2003, Norway promoted board gender diversity by signing into a law requiring that 40% of board members be female, beginning in 2008. Spain followed suit by mandating the same quota be met by 2015. Belgium, France, Germany, Netherlands, Sweden and the UK are all considering the feasibility of imposing a gender quota on their corporate boards. Multiple research agencies in the U.S., such as the Interfaith Center on Corporate Responsibility and the National Association of Corporate Directors Blue Ribbon Commission, all highly recommend board gender and racial diversity.

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ACCEPTED MANUSCRIPT In an attempt to address this question, many scholars in recent years have studied the effect of women directors on firm performance. However, the empirical evidence in the extant

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literature is inconclusive and most of the studies focus on firms in the U.S. and a few other

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developed economies. For example, Carter et al. (2003) and Campbell and Minguez-Vera (2008) document a significant and positive relation between the percent of female directors and firm

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performance. Using acquisition bids by S&P 1500 firms, Levi et al. (2014-this issue) show that

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female directors help create shareholder value through reducing bids and bid premium. On the contrary, Ahern and Dittmar (2012) find that imposing a quota of 40% female directors on

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boards in Norway’s public companies results in lower firm value. They attribute the findings to the possibility that the law forces firms to hire younger and less experienced women as directors.

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Bøhren and Staubo (2014-this issue) further indicate that the mandatory gender balance in

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Norway may produce firms with inefficient boards. Adams and Ferreira (2009) also find a negative relation between board gender diversity and firm performance in the U.S., partially

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attributing the negative relation to the over-monitoring by women directors.2 Triana et al. (2013)

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show that board gender diversity is a double-edged sword since it can drive or impede strategic changes depending on the firm performance and the power of women directors. The aforementioned findings do not provide clear guidance in the case of China. Corporate governance in China is significantly weaker than that in the U.S. and other developed countries (Allen et al., 2005). Do women directors improve firm performance in China? To empirically answer our research question, we employ a panel of over 2,000 listed firms for the period 1999-2011. We find that firm performance is positively related to gender 2

There are other studies that do not find a significant relation between board gender diversity and firm performance. For example, Farrell and Hersch (2005) and Carter et al. (2010) find that the number or addition of female directors has no significant impact on firm performance in the U.S. firms. Rose (2007) shows no performance effect of gender diversity in a sample of Danish firms.

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ACCEPTED MANUSCRIPT diversity measured as the percentage or the number of female directors on boards. We further separate female directors into executive and independent directors, and examine their influences

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on firm performance separately. We find that the effect of female executive directors is stronger

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than that of female independent directors, suggesting a more pronounced executive effect over the monitoring effect. The female executive directors, due to the virtue of their proximity to

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operating activities, have more opportunities to observe and influence firm decisions beyond the

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board room. Additionally, we find that boards with three or more female directors have a much stronger impact on firm performance than boards with two or fewer, supporting the critical mass

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theory which states “one is a token, two is a presence, and three is a voice”(Kristie, 2011).

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Next, we investigate whether the effect of board gender diversity varies under different ownership structures. The majority of China’s listed firms are privatized former state-owned

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enterprises (SOEs) with very unique ownership structures controlled by either state owners or

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legal person owners. We find that the board gender diversity effect is positive and significant in legal person-controlled firms but insignificant in state-controlled firms, reflecting the divergence

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of the primary motives of the controlling owners. Legal person owners are profit-driven while state owners have both political and economic considerations (Chen et al., 2006). Our study contributes to the literature on board gender diversity and firm performance in several aspects. First, we extend the literature beyond developed economies by providing the first empirical evidence on board gender diversity and firm performance from China, the world’s largest developing economy. Second, we add new empirical evidence to the literature that board gender diversity can be beneficial to firm performance. Third, we decompose the effect of female directors into the executive effect and the monitoring effect, and find that the executive effect outweighs the monitoring effect. Fourth, we provide direct evidence supporting the critical mass 4

ACCEPTED MANUSCRIPT theory concerning board gender diversity. Lastly, we add new evidence concerning the effect of board gender diversity on firm performance under different ownership structures in China.

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The rest of the paper is organized as follows: Section 2 reviews the relevant theories on board gender diversity and firm performance. The sample and summary statistics are discussed

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in Section 3, while the methodology is explained in Section 4. Section 5 examines the relation between women directors and firm performance in China. Section 6 further examines this

2.1.

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2. Theories and Board Gender Diversity

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relation under different controlling ownership structures. Section 7 concludes the study.

Resource dependence theory and board gender diversity

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Resource dependence theory (Pfeffer and Salancik, 1978) posits that businesses depend on the resources in their external environments to survive. These dependencies pose risks to the

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businesses. To reduce the dependencies and their surrounding uncertainties, businesses can

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cultivate linkages to the external entities that control those resources. Pfeffer and Salancik (1978) attribute three benefits to corporate board linkages: advice and counsel, legitimacy, and

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communication channels. In terms of advice and counsel, the extant literature suggests that gender-diverse boards are linked to higher quality board deliberations of complex issues, some of which might be considered unpalatable in all-male boards (Kravitz, 2003; Huse and Solberg, 2006; among others). In terms of legitimacy, firms’ practices are legitimized by accepting societal norms and values. Cox et al. (1991) propose the “value-in-diversity” hypothesis stating that as women’s equal rights become more and more mainstream in society, firms gain legitimacy by appointing female directors to their boards. As for communication channels, women leaders, due to their different life experiences and perspectives, are better equipped to connect their firms to female customers, women in the labor force and society at large. Hillman 5

ACCEPTED MANUSCRIPT et al. (2007) apply the resource dependence theory to examine board gender diversity and find that the U.S. firms with gender-diverse boards can accrue these benefits. In sum, the resource

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dependence theory points to beneficial effects of gender-diverse boards. Agency theory, corporate governance and board gender diversity

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In corporate settings, agency problems occur when managers do not have shareholders’ best interest in mind when making corporate decisions. One solution is to enhance monitoring by

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corporate boards. Fama and Jensen (1983) argue that efficient board guidance and monitoring are

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essential in mitigating these conflicts of interests. Empirical evidence shows that women directors tend to be more active in monitoring activities. For instance, Gul et al. (2008) and

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Adam and Ferreira (2009) show that more gender-diverse boards demand more audit efforts and

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managerial accountability.

The effects of board gender diversity on corporate decisions also depend on firms’

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governance quality. In well-governed firms, board gender diversity can be detrimental to firm

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value due to unnecessary over-monitoring (Adam and Ferreira, 2009). On the other hand, Gul et al. (2011) suggest that firms can partially remedy their weak governance by having genderdiverse boards.

As mentioned earlier, the legal institutions in China regarding investor protections, corporate governance, accounting standards, and quality of governments, are much less developed than those in the U.S and other developed economies (Allen et al., 2005). Hence, over-monitoring is less likely an issue. Given China’s current state of weak corporate governance, gender-diverse boards may have beneficial effects on firm performance due to the aforementioned partial substitute effect.

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ACCEPTED MANUSCRIPT 2.3.

Token status theory, sex-role stereotypes and board gender diversity Kanter (1977) coins the rarity of females or minorities in top management as “tokens”

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and in extreme cases, “solos,” referring to someone who is the sole representative of a particular

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demographic group (e.g. gender and race). Kanter (1977) further suggests that observers tend to distort the images of female token managers in ways that are more closely linked to femininity

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rather than to the qualities of leadership. This image distortion leads to sex-role stereotypes of

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female directors, stereotypes that are inconsistent with people’s perceptions of leaders. Kulich et al. (2007) show that gender-role stereotypes of women leaders contribute to the pay gap between

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male and female executive directors. Similarly, the literature on schemas suggests that individuals develop mental modes of the attributes for certain job holders (Lee and James 2007).

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Because men hold a majority of the top management positions, male job applicants are more

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likely than female applicants to be associated with those attributes (Powell and Butterfield, 2002). The historical token status of women in top management also reinforces the stereotypes

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that women have fewer necessary attributes for such positions (Lee and James 2007).

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Due to the token status and sex-role stereotypes of female directors, a lone female director may be treated as a mere “token” by both internal and external stakeholders and that her impact on corporate decisions is likely to be limited. As an extension of the token status theory, the critical mass theory on board gender diversity posits that “one is a token, two is a presence, and three is a voice” (Kristie, 2011). Kramer et al. (2007) point out that “The magic seems to occur when three or more women serve on a board together. We find that having three or more women on a board can create a critical mass where women are no longer seen as outsiders and are able to influence the content and process of board discussions more substantially”. If women

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ACCEPTED MANUSCRIPT directors have impacts on corporate decisions and firm performance, those impacts should be more pronounced when the critical mass is reached.

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3. Data and Summary Statistics

We obtain the financial and board composition data of listed firms in China from the Chinese

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Securities Market and Accounting Research (CSMAR) organization. Our initial sample contains

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all listed firms in Shanghai and Shenzhen Stock Exchanges for the period 1999-2011. Following the convention in the literature, we exclude the financial and public utility firms from our

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sample. Firm-years with negative equity or negative sales are also excluded. The final sample consists of 16,964 firm-years observations and over 2,000 firms. Firm performance measures

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3.1.

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Our primary measures of firm performance are return on sales (ROS) and return on assets (ROA). Compared to ROS, ROA could be downward biased due to the occasional seasoned

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equity offerings (SEOs) and the subsequent assets escalations (Sun and Tong, 2003). We do not

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employ return on equity (ROE) as a performance measure since it is often manipulated to satisfy a SEO requirement.3 Tobin’s Q, though widely used to proxy firm performance in the existing literature, is not considered a proper performance measure for Chinese listed firms. Most Chinese listed firms originated from state-owned enterprises (SOEs) with majority shares not tradable in the secondary market. The non-tradable shareholders, mainly governments or stateowned legal persons, typically acquire their shares of stocks at prices significantly lower than the initial public offering prices. Since there are big pricing gaps between tradable and non-tradable

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One of the rules imposed by the China Securities Regulatory Commission (CSRC) concerning SEOs is that firms have to achieve a minimum average ROE of 10% three years before the SEO and a minimum ROE of 10% one year before the SEO. Many firms aggressively manipulate their ROEs in order to meet the SEO requirement.

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ACCEPTED MANUSCRIPT shares, Tobin’s Q would not correctly reflect firm financial performances or firm values.4 In addition, Chinese stock markets are highly speculative and share prices bear little relationship to

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their fundamental values (Bai et al., 2004; Markoczy et al., 2013). We calculate ROS as net income divided by sales and ROA as net income divided by

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assets. Both ROS and ROA are truncated at the top and bottom 0.5% percentiles to reduce the effect of outliers. Panel A of Table 1 presents summary statistics of performance measures. The

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averages of ROS and ROA are 4.8% and 3.2%, respectively, over the whole sample period.

3.2.

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[Insert Table 1 here] Board gender diversity measures and director characteristics

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The key variable of interest in this study is board gender diversity. Many studies have used the percent of women directors on board (%_Women) to measure board gender diversity

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(Adam and Ferreira, 2009; Ahern and Dittmar, 2012). Some other studies have employed the

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number of women directors on board or a dummy variable based on the idea that a critical mass needs to be reached before the influence of women directors emerges (Simpson et al., 2010). We

diversity.

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employ both the percent and the number of women directors on board as measures of gender

Panel B of Table 1 presents the summary statistics for board gender diversity measures. We find that 10.2% of all directors are women in our full sample. About 3.6% (6.6%) of all directors are women independent directors (women executive directors), indicating that about

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The Chinese state ownership reform in 2005 required that the listed firms gradually convert their non-tradable shares into tradable shares. The ownership reform was basically completed by 2007. However, the former nontradable shareholders still face a number of restrictions on share trading in terms of, for instance, the percent of shares allowed to be traded and the lockup period (Haveman and Wang, 2013).

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ACCEPTED MANUSCRIPT 35% of female directors are independent and the remaining 65% hold executive or management positions.

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The alternative measure for board gender diversity is a set of three dummy variables defined as follows. The dummy variable D_1Woman equals 1 when the board has one female

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director and 0 otherwise. The dummy variable D_2Women equals 1 when the board has two female directors and 0 otherwise. The dummy variable D_3Women equals 1 when the board has

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three or more female directors and 0 otherwise. Among all 16,964 firm-years, about 36.5%,

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17.0% and 7.5% firm-years have one woman, two women, and three or more women on their boards, respectively, and the remaining 39.0% firm-years have no female directors on their

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boards. Additionally, about 4.1% of board chairs are female. Figure 1 illustrates the trend of board gender diversity from 1999 to 2011. Fig.1a shows

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that the percent of women directors on board (%_Women) gradually rises from an average of

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8.9% in 1999 to 12.0% in 2011. Fig. 1b exhibits the following trends over time: (1) the percent of firms with one or more female directors increases from 52.2% in 1999 to 66.3% in 2011; (2)

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the percent of firms with two or more female directors increases from 21.3% in 1999 to 29.2% in 2011; and (3) the percent of firms with three or more female directors does not change much, hovering around 8.6%, suggesting that attaining a critical mass on a board over the sample period is not easy. [Insert Figure 1 here] Panel C of Table 1 provides information on director characteristics such as age and education background for all directors and women directors. For instance, the women directors are 1.6 years younger on average; the average education level is 3.6 for all board directors and

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ACCEPTED MANUSCRIPT 3.4 for women directors;5 74.7% of all board directors and 75.8% of women directors hold one or more concurrent positions at other firms and are therefore considered busy. 6 However, these

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statistics do not suggest a material difference in backgrounds between these two groups of

Measures of control variables

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3.3.

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directors.7

Following the recent corporate board literature (Bebchuk and Cohen, 2005; Francis et al.,

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2011; among others), we group the control variables into three categories. The group of board

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characteristic variables includes the percent of independent board directors (%_Independent), the natural log of the board size (Ln_BoardSize), and a CEO_Chair dummy variable (Duality) which

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equals 1 when the chief executive officer (CEO) and the board chair are the same person. The group of ownership characteristic variables includes the percent of shares owned by governments

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or state-owned legal persons (%_State), the percent of shares owned by non-state-owned

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domestic legal persons or foreign legal persons (%_LegalPerson),8 the percent of shares owned by firm management (%_Management), and the natural log of the number of shareholders

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(Ln_Shareholder). The group of firm characteristic variables includes a dummy variable (Woman_CEO) which equals 1 when the firm CEO is a woman, the natural log of the number of employees (Ln_Employee), the book value of debt divided by total assets (Leverage), and the natural log of the number of years that a firm is listed on the exchange (Ln_FirmAge).

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For education level, 1 means middle school or lower education, 2 means high school education, 3 means college education, 4 means masters education and 5 means doctoral education. The information about education data is only available after 2003 and less than 50% of the firms report such information. 6 The information about busy directors is only available after 2005. 7 Compared to all directors, women directors are more likely to have a financial background (27% of women directors vs. 12% of all directors) and less likely to have an engineering background (14% vs. 27%). Note that the professional background reporting is voluntary and only about 20% of our sample firms reported such information. 8 Legal person shares are calculated as the sum of domestic promoter’s legal person shares, foreign promoter’s legal person shares and raised legal person shares.

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ACCEPTED MANUSCRIPT Panel D of Table 1 presents the summary statistics for the control variables used in this study. For instance, an average board has about 9 or 10 members, about 29.4% of board

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members are independent and about 16.0% of board chairs are also CEOs of the same firm. The

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state owners, legal person owners and firm management account for 24.6 %, 18.1% and 2.1% of all shares, respectively. An average firm has about 32,000 shareholders. As for the firm

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characteristics, about 5.0% of the CEOs in our sample are women. On average, a listed firm has

Correlations among variables

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3.4.

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about 1,617 employees with 6 years of listing history and a leverage ratio of 47.0%.

As a rudimentary check for multicollinearity, Table 2 reports the correlations among all

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independent variables used in our regression analysis. As a rule of thumb, a correlation of 0.7 or higher in absolute value may indicate a multicollinearity issue. Table 2 shows that the highest

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correlation coefficient of 0.81 (in bold) appears between %_Women and %_ExecutiveWomen.

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Since these two variables are used alternatively instead of simultaneously in the regression model, the high correlation among these two is not an issue. No other correlation coefficient has

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an absolute value higher than 0.7. [Insert Table 2 here]

4. Research methodology 4.1.

The main model and estimation method The following is our main regression model:

Firm_Performance it = γ Board_Gender_Diversity it+ β1 Board_Charit+β2 Ownership_Charit+β3 Firm_Charit+αi+λt+εit (1)

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ACCEPTED MANUSCRIPT Board_Gender_Diversity is measured by the percent of female directors on board (%_Women) or the set of three female director dummy variables (D_1Woman, D_2Women, and

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D_3Women). We also measure Board_Gender_Diversity as the percent of female independent

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directors (%_IndependentWomen) and the percent of female executive directors (%_ExecutiveWomen) to further examine how female directors influence firm performance in

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Section 5.2. Board_Char, Ownership_Char, and Firm_Char are the three sets of control

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variables related to board characteristics, ownership characteristics, and firm characteristics,

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respectively.

There are two estimation methods commonly used in the board and performance

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literature. One is the pooled ordinary least squares (OLS) regression controlling for industry effects and the other is the panel regression with fixed effects. We apply the F-test to determine

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which is more appropriate for our study. The null hypothesis for the F-test is that the unobserved

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heterogeneity or firm fixed effect does not exist. Our F-test statistic with either ROS or ROA as a dependent variable exceeds the corresponding critical value at the 1% level, suggesting that we

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reject the pooled OLS approach in favor of the panel regression with fixed effects approach. Thus, our main regression model (1) includes firm fixed effects, αi, which help eliminate constant omitted variable bias, and year fixed effects, λt, which help control for economy-wide yearly fluctuations. We use the panel regression with fixed effects to estimate our main regression model (1) and refer to this approach as the Fixed Effects (FE) method. The reported standard errors are adjusted for potential heteroscedasticity. 4.2.

Endogeneity One may raise concern about the endogeneity between women directors and firm

performance since firm performance can affect both the incentive of women joining the boards 13

ACCEPTED MANUSCRIPT and the motivation of boards hiring women directors (Adams and Ferreira, 2009). We employ three alternative model specifications to address the potential endogeneity problem. The first

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alternative uses a one-year lagged board gender diversity measure and one-year lagged board

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characteristic variables in the main regression to replace the contemporary ones since female directors and board characteristics need time to influence firm performance. This alternative

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to as the FE with lagged board variables method.

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model specification is also estimated using the panel regression with fixed effects, and is referred

The second alternative specification uses instrument variables (“IVs”) and estimates the

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main regression model via the two-stage least squares (“2SLS”) method. We refer to this

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approach as the FE with IV method. The proper exogenous IVs need to meet the instrument exogeneity and the instrument relevance conditions. Considering that %_Women of a firm can

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be affected by the percent of women directors in its own industry and/or the percent of female employment in its own industry, we choose the percent of women directors in the firm’s 2-digit

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SIC coded industry (%_WomenIndustry) 9 and the percent of female employment in the firm’s 2-

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digit SIC coded industry (%_WomenWorkers)10 as IVs for %_Women. The exogeneity and relevance conditions of the IVs are analyzed in Section 5.1. The third alternative specification incorporates a lagged ROS or ROA into the main regression and estimates the augmented regression via Arellano-Bond one step method. The Arellano-Bond dynamic panel estimator takes care of the endogeneity originated from unobserved heterogeneity, simultaneity, and dynamic relation between board structure and past 9

The board gender diversity of an industry where a specific firm belongs to is calculated as the ratio of (total number of women directors per 2-digit SIC code minus the number of women directors in that specific firm) to (total number of directors per 2-digit SIC code minus the number of directors in that specific firm). 10 The percent of female employment data by industry, from 1999 to 2011, are collected from the China Labor Statistical Yearbook.

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ACCEPTED MANUSCRIPT firm performance (Roodman, 2009; Wintoki et al., 2012). All of the independent variables are assumed to be endogenous except Ln_FirmAge and the year dummies. The third and fourth lags

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of the dependent variable and the endogenous variables, together with all the lags of the

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exogenous variables, are employed as IVs. To relieve the transient error correlation concern, only the odd year data are employed in the dynamic model estimation (Wintoki et al., 2012).

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Since the data is selected every two years, the two year-lagged ROS or ROA are included in the

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main regression; the third and fourth lags of the dependent and the endogenous variables call for the sixth and eighth year-lagged endogenous variables, together with all the available lags of the

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exogenous variables, as IVs. Heteroskedasticity is controlled by robust standard errors. The exogeneity of the IVs and the serial correlation of the fist-differenced residuals are discussed in

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Section 5.1. We refer to this specification as the Arellano-Bond method.

Percent of women directors and firm performance

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5.1.

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5. Do women directors affect firm performance?

We first examine if the percent of women directors on board (%_Women) has a

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significant impact on firm performance. Table 3 presents the results of the main regression model (1) where board gender diversity is measured by %_Women and the firm performance is measured by ROS or ROA. The results for ROS and ROA as dependent variables are presented in columns (1) – (4) and (5) – (8), respectively. With regard to the alternative methods, the results based on the FE Method are reported in columns (1) and (5); the FE with lagged board variables method in columns (2) and (6); the FE with IV method in columns (3) and (7); and the Arellano-Bond method in columns (4) and (8). Firm fixed effects, year fixed effects and robust errors are controlled for in all regression analyses. [Insert Table 3 here] 15

ACCEPTED MANUSCRIPT The overall results suggest that female directors have a significant and positive impact on firm performance. For instance, with the FE method, a 1% rise in %_Women increases ROS and

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ROA by 0.13% and 0.03%, respectively. With the FE with lagged board variables method, a 1%

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rise in %_Women increases ROS and ROA by 0.14% and 0.03%, respectively.

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Concerning the FE with IV method, we test whether the IVs meet the exogeneity and the relevance conditions. We first employ the Hansen’s J instrument test, also known as the over

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identification test (Davidson and MacKinnon, 1993), to examine if the IVs mentioned in Section

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4.2, %_WomenIndustry and %_WomenWorkers, meet the exogeneity requirement. The null hypothesis here is that the IVs are not correlated with the regression errors. Our regressions with

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performance measured by either ROS or ROA produce insignificant J statistics at the 10% level, indicating that the null hypothesis cannot be rejected at that level. We then examine the

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relevance of the above IVs through a first stage F-test involved in the 2SLS regression. Our test

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results show that the F-test statistic is significant at the 1% level, with performance measured by either ROS or ROA, indicating that the IVs are jointly significant. However, the values of the F-

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test statistics vary around 6 and 7, signaling a potential weak IV problem. Our results based on the FE with IV method also indicate that %_Women has a positive impact on firm performance. However, one should interpret the magnitude and the significance level of the coefficient with caution since weak IVs may cause estimators to perform poorly. To further address the endogeneity issue, we apply the Arellano-Bond method by including the past performance in the main regression. The Hansen χ2 test of over-identification is used to examine the validness of the IVs used in the Arellano-Bond method. Our test results show that the χ2 test statistics are insignificant at the 10% level with either ROS or ROA used as a proxy for firm performance. We test the first-differenced residuals for autocorrelations and find 16

ACCEPTED MANUSCRIPT no significant second-order serial correlations at the 10% level. Using the Arellano-Bond method, a 1% increase in %_Women improves ROS by 0.43% and ROA by 0.07%.

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With regard to other board characteristics, the results in Table 3 show that the percent of independent directors generally has a strong and positive impact on firm performance. Neither

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board size nor the board chair-CEO duality seems to have a consistent impact on firm performance. With regard to ownership characteristics, the results show that both %_State and

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%_LegalPerson have a significantly positive impact while the dispersion of ownership measured

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by Ln_Shareholder exerts a significantly negative impact on firm performance. As for firm characteristics, our results show that Ln_Employee tends to have a positive influence while both

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leverage and firm listing history tend to have a negative influence on firm performance. As a robustness check on the results in Table 3, we redefine ROS and ROA as operating

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income divided by sales and operating income divided by assets, respectively. We re-run the

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regressions in Table 3 with re-defined ROS and ROA and report the results in Table 4. The results are fairly similar to those presented in Table 3. We find that %_Women has a

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significantly positive impact on ROA using all four methods and a significantly positive impact on ROS using the FE with IV and Arellano-Bond methods. [Insert Table 4 here] 5.2.

Independent vs. executive women directors and women board chairs Independent directors are likely to influence firm performance through the monitoring

channel due to their independence status while executive directors mainly through the executive channel due to their executive power and management skills. We therefore examine through which channel(s) female directors influence firm performance. We first allocate women directors

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ACCEPTED MANUSCRIPT into one of the two groups: the independent directors group or the executive directors group. We then replace the board gender diversity measure in the main regression model (1) by the percent

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of women independent directors (%_IndependentWomen) and the percent of women executive

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directors (%_ExecutiveWomen). To save space, we do not report the estimation results of control variables in Table 5, except for %_Independent and Woman_CEO for comparison

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purposes.11

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[Insert Table 5 here]

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Table 5 shows that %_IndependentWomen has no impact on ROS using the FE, FE with lagged board variables, and Arellano-Bond methods, and a marginally positive impact on ROA

ED

using the FE method. However, a 1% increase in %_ExecutiveWomen tends to increase the ROS (ROA) by 0.18% and 0.16% (0.03% and 0.03%) using the FE or FE with lagged board variables

PT

methods, respectively. The results in Table 5 provide relatively strong evidence of women

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executive directors’ positive impact and very weak evidence of women independent directors’ positive impact on firm performance.

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Similar to the results in Table 3, we also find that %_Independent is positively linked with both performance measures using the FE or FE with lagged board variables methods. The weak evidence of %_IndependentWomen’s impact on ROS and ROA indicates that women independent directors are no more beneficial to firm performance than independent directors in general. On the other hand, the results of a positive impact of Woman_CEO on ROA corroborate the %_ExecutiveWomen’s impact on firm performance. Overall, our results suggest that the beneficial effect of women directors on firm performance primarily comes through the women 11

%_WomenIndustry and %_WomenWorkers are weak IVs and they cannot appropriately approximate the independence of women directors or the absolute number of women directors, we do not report results based on the FE with IV method in Table 5 and hereafter.

18

ACCEPTED MANUSCRIPT executive directors’ executive effect rather than the women independent directors’ monitoring effect.

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T

To provide further support for the executive effect finding, we examine whether a woman board chair has any positive influence on firm performance since a woman board chair is always

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served by an executive director instead of an independent director in the Chinese listed firms. We re-run the regressions in Table 5 by replacing board gender diversity in the main regression

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model (1) with a dummy variable Woman_Chair, where Woman_Chair equals 1 if the board

MA

chair is a woman and 0 otherwise. The regression results are reported in Table 6. The results show that the performance of firms with a woman board chair are, on average, 0.06% and 0.05%

ED

(0.02% and 0.01%) higher based on the ROS (ROA) measure than their counterparts without a woman board chair, using the FE and FE with lagged board variables methods, respectively.

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The results on Woman_Chair further substantiate women executive directors’ influence on firm

[Insert Table 6 here]

The number of women on board and firm performance

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5.3.

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performance.

As mentioned in the Introduction, the absolute number of women directors matters for firm performance. Three women on a fifteen-member board may exert a stronger influence than one woman on a five-member board. We next test the critical mass theory by using the three female director dummy variables (D_1Woman, D_2Women, and D_3Women) to measure board gender diversity in regression model (1). To save space, we only report regression results on the three dummy variables in Table 7. [Insert Table 7 here]

19

ACCEPTED MANUSCRIPT We first focus on the influence of D_1Woman, D_2Women and D_3Women on ROS using the FE method. It seems that a board with one woman director (D_1Woman) exerts no

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significant impact on ROS. Compared to a board with no female directors, a board with two

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women directors (D_2Women) is associated with a 0.02% higher ROS and a board with three or more women directors (D_3Women) is associated with a 0.06% higher ROS. Similar results are

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found for ROS using the FE with lagged board variables method and for ROA using the FE, FE

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with lagged board variables and Arellano-Bond methods. We also perform a robustness check on the main results by re-run the regression in Table 7 with ROS and ROA re-defined as

MA

operating income divided by sales and operating income divided by assets, respectively, and

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obtain similar results as those reported in Table 7.

Overall our results presented in Tables 3 to 7 suggest that board gender diversity, whether

PT

measured by percentages or dummies, has a significantly positive impact on firm performance. Moreover, the female executive directors’ executive effect outweighs the female independent

CE

directors’ monitoring effect. Boards with a critical mass of female directors generally have a

5.4.

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stronger positive impact on firm performance. Discussion

We present three theories on how the presence of female directors on corporate boards might affect firm performance. The resource dependence theory suggests that firms accrue benefits through boards in three channels: advice and counsel, legitimacy, and access to resources/channels of communication (Pfeffer and Salancik, 1978). Gender-diverse boards can help broaden these channels. For example, some firms add female directors to their boards to sustain good relationships with female clients or consumers. Some view female directors as inspirations and connections to their female employees. Others desire a female perspective in 20

ACCEPTED MANUSCRIPT important board decisions. Hence, board gender diversity helps improve board reputation and the quality of board decisions and therefore is beneficial to the firm. Our overall findings are

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consistent with the resource dependence theory in that boards with a high fraction of female

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directors have a positive effect on firm performance.

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In our subsample analysis, we find that female executive directors have a stronger positive effect on firm performance while female independent directors have a weak positive

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effect. This result warrants further elaboration since the resource dependence theory seems to

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suggest that independent/outside directors can bring more useful external resources to the firm. After controlling for %_Independent, the weak positive impact from %_IndependentWomen

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indicates that external resources possessed by women independent directors are no more beneficial to firm performance than the resources possessed by independent directors in general.

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On the other hand, executive directors fully participate in the daily operations of the firms, from

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personnel decisions, raw materials procurements, to product marketing. As such, it is plausible that women executive directors have more useful working connections and communication

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channels than directors in general, in both the factor and the product markets, leading to a stronger impact on firm performance. It is widely agreed in the literature that strong corporate governance reduces agency problems, leading to performance improvement. Empirical evidence further shows that genderdiverse boards can serve as a partial substitute for weak corporate governance (Gul et al., 2011). Given the currently underdeveloped corporate governance in China (Allen et al., 2005), our findings suggest that female directors may improve firm performance by easing the weak governance in Chinese listed firms. For instance, female directors can strengthen corporate governance through improved monitoring and greater oversight of management (Adam and 21

ACCEPTED MANUSCRIPT Ferreira 2009; Gul et al., 2008). Empirical evidence further shows that the presence of female directors at board meetings improves the quality of board deliberations of complex issues,

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reducing the probability of major decision missteps (Kravitz, 2003; Huse and Solberg, 2006;

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among others).

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The critical mass theory states that “one is a token, two is a presence, and three is a voice” (Kristie 2011). We find that the insignificant impact of the sole female director on firm

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performance is consistent with both the token theory and the gender-role stereotypes theory in

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that both theories point to the insignificant effect of token female directors on firm performance (Kanter, 1977). As the number of female directors on a board increases, the effect of female

ED

directors on firm performance strengthens. We document that when the number of female directors on a board reaches three, the performance impact of board gender diversity becomes

PT

significantly positive, supporting the aforementioned critical mass theory.

Does women directors’ effect on firm performance vary by ownership?

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6.1.

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6. Corporate ownership and the impact of board gender diversity on firm performance

The listed firms in China have unique ownership structures. However, the real control power for the majority of the firms lies with either state owners or legal person owners.12 Controlling shareholders can appoint their preferred delegates to the boards and use their power to benefit themselves, sometimes at the expense of the minority shareholders. However, state owners and legal person owners are vastly different in terms of their desired management motives. Legal person owners are usually charged with profit goals and hence have strong 12

The shares of the Chinese listed firms can generally be classified into five categories: state shares, legal person shares, employee shares, A-shares and B-shares. Employee shares and B shares do not have significant impacts on firm management due to their minimal weights. A-shares are mainly held by individual Chinese investors.

22

ACCEPTED MANUSCRIPT incentives to maximize firm values and monitor managerial activities of the controlled firms. State owners, such as the local Communist Party committees or SOEs, are charged with political

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T

and social, as well as economic goals (Chen et al., 2006). Since different dominant ownership comes with different goals, we examine if corporate

SC

ownership influences the relation between women directors and firm performance. We focus our analysis on two subsamples: the State Subsample and the Legal Person Subsample. The State

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Subsample consists of firms with state ownership but no legal person ownership; therefore the

MA

state owners are more likely to have a dominant effect on the board in this subsample. The Legal Person Subsample consists of firms with legal person ownership but no state ownership;

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therefore the legal person owners are more likely to have a dominant effect on the board.13 Panel A of Table 8 presents regression results for the State Subsample and Panel B for the Legal

[Insert Table 8 here]

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Person Subsample.

The results show that the percent of women directors (%_Women) has an insignificant

AC

impact on either ROS or ROA for the State Subsample in Panel A and a significantly positive impact on both ROS and ROA for the Legal Person Subsample in Panel B. Specifically, Panel B suggests that a 1% increase in %_Women is linked with 0.55%, 0.35% and 0.97% increases in ROS using the FE, FE with lagged board variables and Arellano-Bond methods, respectively. These increases in performance are much stronger than the corresponding increases in ROS obtained from the whole sample as shown in Table 3, which are 0.13%, 0.14% and 0.43%, respectively. We obtain similar findings when ROA is used as the measure of firm performance.

13

We exclude firms with neither state ownership nor legal person ownership from the analysis in this subsection.

23

ACCEPTED MANUSCRIPT As a robustness check of the results in Panels A and B, we modify the above subsample classification as follows: We form a subsample of firms that have state ownership larger than

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legal person ownership and a subsample of firms that have legal person ownership larger than

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state ownership. The test results are reported in Panels C and D of Table 8, respectively. The results in Panel C are similar to those reported in Panel A and the results in Panel D are similar to

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those in Panel B. Overall, we find that board gender diversity better improves firm performance

NU

in a legal person-controlled environment than in a state-controlled environment. In another robustness check we also replace net income with operating income in the performance measure

Does ownership affect board gender diversity?

ED

6.2.

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calculation and obtain quantitatively similar results.

Though the positive impact of board gender diversity on firm performance varies with

PT

corporate ownership, the variation could be caused by a selection bias between corporate

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ownership and board gender diversity. To address this concern, we run the following regression

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to examine the impact of ownership on board gender diversity: (2)

The regression model (2) is estimated separately with one of the three sets of control variables using a panel fixed effects regression. The first set of control variables, referred to as Set I, includes the usual control variables used in our main regression model (1) plus a new control variable of firm performance (measured by ROS or ROA). The second set of control variables, Set II, includes all the control variables in Set I plus the one-year lag of %_Women. The third set of control variables, Set III, includes all the control variables in Set II plus the oneyear lag of the firm performance measure.

24

ACCEPTED MANUSCRIPT [Insert Table 9 here] Table 9 presents the regression results of model (2). To save space, we only report the

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T

regression coefficients of %_State and %_LegalPerson. The results reveal that neither %_State nor %_LegalPerson has a significant impact on the percent of women directors, regardless of the

SC

control variables or performance measures used. Hence, corporate ownership does not seem to significantly affect board gender diversity. Discussion

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6.3.

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The results in this section show that the positive effect of female directors on firm performance is stronger in legal person-controlled firms than in state-controlled firms. It could be

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that the female directors in legal person-controlled firms are more capable than those in statecontrolled firms. However, our data show that these two groups of female directors have similar

PT

ages, educational backgrounds, and busyness levels. A more plausible explanation may be that

CE

these two groups of female directors are charged with different mandates by their respective controlling owners, as discussed earlier. Given the profit-centric charges, female directors in

AC

legal person-controlled firms focus their efforts (monitoring as well as executive) on improving firm financial and operating performance. On the other hand, female directors in state-controlled firms are required to divert part of their efforts to non-profit related political and social activities. Therefore, even though these two groups of female directors may be equally capable and diligent in performing their duties, their influences on firm performance can be different due to their different charges. Our untabulated statistics provide some support for the above argument that female directors in state-controlled firms are more likely charged with political tasks. We find that 8%

25

ACCEPTED MANUSCRIPT of female directors in state-controlled firms hold politically-related positions such as a chair or an officer of a local communist party branch, which is significantly higher than the 2% in legal

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person-controlled firms. The evidence is even more striking in terms of female board chairs. We

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find that 16% of female board chairs and vice chairs in state-controlled firms are political commissars while the number is only 4% in legal person-controlled firms. Another plausible

SC

explanation is that the incentive system is different for these two groups of firms. Our data show

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that female directors in legal person-controlled firms hold significantly more shares and have significantly higher monetary rewards than those in state-controlled firms. Since the female

ED

performance is likely to be stronger.

MA

directors in legal person-controlled firms tend to be better incentivized, their effect on firm

7. Conclusion

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This study extends the existing literature on board diversity by providing the first

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empirical evidence on the effect of women directors on firm performance in China. Our results show that the percent of women directors has a significant and positive impact on firm

AC

performance measured by return on sales and return on assets. The positive impact primarily originates from the executive women directors’ executive effect rather than from the independent women directors’ monitoring effect. The number of women directors is also important. We find that boards with three or more women have a stronger impact on firm performance compared to those with two or fewer women, providing support for the critical mass hypothesis concerning board gender diversity (Kristie, 2011). We further document that the positive impact of board gender diversity is significant in firms mainly controlled by legal person owners and insignificant in firms mainly controlled by state owners, reflecting the divergence of the primary managerial motives of the controlling shareholders. 26

ACCEPTED MANUSCRIPT In recent years, firms in developed countries are facing increased pressure from government regulators to increase gender diversity in their boardrooms. As the world’s largest

T

developing economy and the second largest economy overall, the regulators, policy makers, and

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business practitioners in China are actively absorbing the better-established corporate governance practices in the developed countries. Should the Chinese government follow the lead

SC

of Norway and other countries to encourage or mandate a board gender quota in Chinese

NU

publicly listed firms? In answering a similar question, Karen J. Curtin, executive vice president of Bank America, puts it succinctly, “There is a real debate between those who think we should

MA

be more diverse because it is the right thing to do and those who think we should be more diverse because it actually enhances shareholder value. Unless we get the second point across,

ED

and people believe it, we’re only going to have tokenism (Brancato and Patterson, 1999)”.

PT

The empirical evidence in this study helps get the second point across in the case of

CE

China. Our findings provide useful empirical guidance for the Chinese policymakers, regulators, and corporate decision makers concerning board gender diversity. The most important policy

AC

implication of our study is that in the current state of weak corporate governance in China, gender-diverse boards are beneficial to firm performance. As corporate governance in China advances and becomes more efficient, this beneficial effect may diminish over time. Until then, firms with weak corporate governance should look into adding more female directors to their boards.

27

ACCEPTED MANUSCRIPT Acknowledgements We are grateful to an anonymous reviewer, Luc Renneboog, Sami Vahamaa, Tod Perry,

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and Renee Adams for their very helpful and constructive comments. We thank conference participants at the 2013 Annual Meeting of the Eastern Finance Association, the 2013 Annual

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Meeting of the Southwestern Finance Association and the 2013 Annual Meeting of the Financial Management Association. We also acknowledge the financial support given by the College of

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CE

PT

ED

MA

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Business Administration at the University of Texas at El Paso.

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Adams, R., Funk, P., 2012. Beyond the glass ceiling: Does gender matter? Manage. Sci. 58(2), 219-235.

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Ahern, K., Dittmar, A., 2012. The changing of the boards: The impact on firm valuation of mandated female board representation. Q. J. Econ. 127(1), 137–197.

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Allen, F., Qian, J., Qian, M.J., 2005. Law, finance, and economic growth in China. J. Financ. Econ. 77, 57–116.

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Bai, C.E., Liu, Q., Lu, J., Song, F. M., Zhang, J., 2004. Corporate governance and market valuation in China. J. Comp. Econ. 32, 599–616. Bebchuk, L.A., Cohen, A., 2005. The costs of entrenched boards. J. Financ. Econ. 78, 409-433.

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Bøhren, Ø., Staubo, S., 2014. Does mandatory gender balance work? Changing organizational form to avoid board upheaval. J. Corp. Financ. (This issue.)

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Campbell, K., Minguez-Vera, A., 2008. Gender diversity in the boardroom and firm financial performance. J. Bus. Ethics 83, 435–451.

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Carter, D.A., D'Souza, F., Simkins, B. J., Simpson, W., 2010. The gender and ethnic diversity of US boards and board committees and firm financial performance. Corp. Gov. 18, 396–414. Carter, D.A., Simkins, B.J., Simpson, W.G., 2003. Corporate governance, board diversity, and firm value. Fin. Rev. 38, 33-53. Chen, G., Firth, M., Gao, D.N., Rui, O., 2006. Ownership structure, corporate governance, and fraud: Evidence from China. J. Corp. Financ. 12, 424-448. Cox, T., Lobel, S., McLeod, P., 1991. Effects of ethnic group cultural differences on cooperative and competitive behavior on a group task. Acad. Manage. J. 34(4), 827–847. Davidson, R., MacKinnon, J.G., 1993. Estimation and inference in econometrics. New York, NY: Oxford University Press. Fama, E. F., Jensen, M. C., 1983. Separation of ownership and control. J. Law Econ. 26, 301– 325. Farrell, K.A., Hersch, P.L., 2005. Additions to corporate boards: The effect of gender. J. Corp. Financ. 11, 85-106. 29

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Gul, F. A., Srinidhi, B., Ng, A. C., 2011. Does board gender diversity improve the informativness of stock prices? J. Account. Econ. 51(3), 314-338.

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Haveman, H. A., Wang, Y., 2013. Going (more) public: Institutional isomorphism and ownership reform among Chinese firms. Manage. Organ. Rev. 9(1), 17-51.

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Hillman, A. J., Shropshire, C., Cannella Jr, A. A., 2007. Organizational predictors of women on corporate boards. Acad. Manag. J. 50(4), 941-952.

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Huang, J., Kisgen, D., 2013. Gender and corporate finance: Are male executives overconfident relative to female executive? J. Financ. Econ. 108, 822-839.

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Huse, M., Solberg, A., 2006. How Scandinavian women make and can make contributions on corporate boards. Women Manage. Rev. 21, 113–130. Kanter, R.M., 1977. Men and women of the corporation. Basic Books: New York.

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Kravitz, D.A., 2003. More women in the workplace: Is there a payoff in firm performance? Acad. Manage. Exec. 17 (3), 148-148.

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Simpson, W., Carter, D., D’Souza, F., 2010. What do we know about women on boards? J. Appl. Financ. 20, 27–39.

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Sun, Q., Tong, W., 2003. China’s share issue privatization: the extent of its success. J. Financ. Econ. 70, 183-222.

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Wintoki, M.B., Linck, J., Netter, J., 2012. Endogeneity and the dynamics of internal corporate governance. J. Financ. Econ. 105, 581-606.

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Triana, M.d.C., Miller, T.L., Trzebiatowski, T.M., 2013. The double-edged nature of board gender diversity: Diversity, firm performance, and the power of women directors as predictors of strategic change. Org. Sci. Forthcoming.

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ACCEPTED MANUSCRIPT Figure 1

2000

2005

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.09

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.1

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.11

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.12

Women directors descriptive statistics by year

2010

+

0

.2

AC

.4

CE

.6

PT

.8

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Fig.1a: Percent of women directors on board

2000

2005

2010

Percent of firms with one or more women directors Percent of firms with two or more women directors Percent of firms with three or more women directors

Fig.1b: Percent of firms with women directors

32

ACCEPTED MANUSCRIPT Table 1

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Summary statistics. Panel A presents statistics on firm performance measured by return on sales (ROS) and return on assets (ROA). Panel B presents statistics on board gender diversity measures. %_Women indicates the percent of women directors on board and is separated into two groups: the percent of women independent directors (%_IndependentWomen) and the percent of women executive directors (%_ExecutiveWomen) on board. D_1Woman equals 1 when the board includes one woman and 0 otherwise; D_2Women equals 1 when the board includes two women and 0 otherwise; and D_3Women equals 1 when the board includes three or more women and 0 otherwise. Woman_Chair is a dummy variable that equals 1 when the board chair is a woman and 0 otherwise.

MA

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Panel C presents the summary information on directors’ background. The average director age (DirAge) and the average women director age (Women_DirAge) are available from 1999 to 2011. The average director’s education level (DirEduc) and the average female director’s education level (Women_DirEduc) are available from 2003 to 2011 for firms that report the information. (For education level, 1 means middle school or lower education, 2 means high school education, 3 means college education, 4 means masters education and 5 means doctoral education.) The percent of busy directors (DirBusy) and the percent of women busy directors (Women_DirBusy) are available from 2005 to 2011 for firms that report the information.

AC

CE

PT

ED

Panel D presents statistics on the control variables. %_Independent is the percent of independent board directors. Ln_BoardSize is the natural log of the board size. Duality, which represents the CEO-chair duality, is a dummy variable which equals 1 when the CEO and the board chair are the same person and 0 otherwise. %_State is the percent of shares owned by governments or SOEs. %_LegalPerson is the percent of shares owned by other domestic and foreign legal persons. %_Management is the percent of shares owned by firm management. Ln_Shareholders is the natural log of the number of shareholders. Women_CEO is a dummy variable that equals 1 when the firm CEO is a woman and 0 otherwise. Ln_Employee is the natural log of the number of employee. Leverage is the book value of debt divided by total asset. Ln_FirmAge is the natural log of the number of years that a firm is listed with an exchange.

33

ACCEPTED MANUSCRIPT Variable

Obs

Mean

16964 16964

4.8% 3.2%

16964 16964 16964 16964 16964 16964 16964

10.2% 3.6% 6.6% 36.5% 17.0% 7.5% 4.1%

Std

Min

Max

0.33 0.07

-6.94 -0.82

1.69 0.29

0.11 0.06 0.09 0.48 0.38 0.26 0.20

0 0 0 0 0 0 0

0.70 0.40 0.70 1 1 1 1

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%_Women %_IndependentWomen %_ExecutiveWomen D_1Woman D_2Women D_3Women Woman_Chair

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Panel B: Women directors

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ROS (Net Income/Sales) ROA (Net Income/Assets)

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Panel A: Performance measures

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Panel C: Women directors' background information 16943 10333 7363 3953 10571 6751

48.5 46.9 3.6 3.4 74.7% 75.8%

4.1 7.5 0.6 0.8 0.2 0.4

33 20 1 1 0 0

64 76 5 5 1 1

16964 16964 16964

29.4% 2.22 16.0%

0.14 0.22 0.37

0 0 0

0.80 3.14 1

Ownership characteristics %_State %_LegalPerson %_Management Ln_Shareholders

16964 16964 16964 16964

24.6% 18.1% 2.1% 10.39

0.26 0.23 0.09 0.92

0 0 0 6.39

0.97 0.92 0.89 19.05

Firm characteristics Woman_CEO Ln_Employee Leverage Ln_FirmAge

16964 16964 16964 16964

5.0% 7.39 47.0% 1.82

0.22 1.35 0.20 0.78

0 1.95 0 0

1 13.22 1.05 3.09

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Board characteristics %_Independent Ln_BoardSize Duality

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Panel D: Control variables

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DirAge Women_DirAge DirEduc Women_DirEduc DirBusy Women_DirBusy

34

ACCEPTED MANUSCRIPT

Table 2

4

5

6

1.00 -0.34 -0.22 0.08 0.03 0.00 0.05 -0.03 0.00 -0.02 -0.02 0.02 -0.03 0.01 -0.01 0.02 0.02

1.00 -0.13 0.30 0.36 0.11 0.04 0.08 0.04 -0.03 0.01 0.02 -0.02 0.08 -0.05 0.00 0.00

1.00 0.30 0.55 0.15 -0.01 0.13 0.05 -0.07 0.04 0.04 -0.04 0.17 -0.05 -0.02 0.01

1.00 -0.01 0.01 0.28 -0.05 0.04 -0.12 -0.03 0.08 -0.03 0.03 -0.01 0.00 0.07

1.00 0.28 -0.13 -0.01 0.08 -0.06 0.07 0.05 -0.08 0.29 -0.14 -0.03 -0.02

7

8

9

10

11

12

13

14

15

16

17

18

1.00 -0.09 0.14 -0.05 -0.09 0.13 -0.05 0.21 0.06 0.00

1.00 -0.14 0.07 0.19 -0.11 0.00 -0.06 -0.10 -0.13

1.00 -0.47 -0.20 0.10 -0.06 0.16 0.02 -0.10

1.00 -0.09 -0.22 0.03 -0.18 -0.04 -0.18

1.00 -0.22 0.04 -0.08 -0.25 -0.34

1.00 -0.03 0.35 0.11 0.30

1.00 -0.06 0.01 0.00

1.00 0.15 0.02

1.00 0.36

1.00

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3

1.00 0.00 -0.02 0.01 -0.03 0.03 0.01 -0.02 0.19 -0.05 -0.01 0.00

ED

2

PT

1 1.00 0.07 0.47 0.62 0.57 0.81 0.23 0.06 -0.04 0.09 -0.12 0.04 0.08 -0.09 0.26 -0.12 -0.02 0.02

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%_Women D_1Woman D_2Women D_3Women %_IndependentWomen %_ExecutiveWomen Woman_Chair %_Independent Ln_BoardSize Duality %_State %_LegalPerson %_Management Ln_Shareholders Woman_CEO Ln_Employee Leverage Ln_FirmAge

AC

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18

CR

IP

T

Correlation matrix. The table presents the correlation matrix among all the independent variables employed in this study. Refer to Table 1 for detailed variable descriptions.

1.00 -0.07 0.02 -0.24 -0.14 0.13 -0.01 0.03 0.02 0.08 0.25

35

ACCEPTED MANUSCRIPT

Table 3

IP

T

Effect of the percent of women directors on firm performance. This table presents regression results of model (1):

CR

Firm_Performance it = γ Board_Gender_Diversity it +

β1 Board_Charit + β2 Ownership_Charit + β3 Firm_Charit + αi+λt+εit

AC

CE

PT

ED

MA NU S

where the gender diversity is measured by the percent of woman directors on board (%_Women). The left panel presents results when firm performance is measured by return on sales (ROS), calculated as net income divided by sales. The right panel presents results when firm performance is measured by return on assets (ROA), calculated as net income divided by assets. See Table 1 for the description of independent variables. The FE method employs the panel fixed effects estimation. The FE with lagged board variables method employs the panel fixed effects estimation with a lagged women director measure and lagged board variables instead of the contemporaneous ones in the main regression model. The FE with IV method employs the 2SLS panel fixed effects estimation. The Arellano-Bond method employs the system GMM estimation after augmenting the main regression with a lagged dependent variable. Year and firm fixed effects are controlled in all regressions. The robust standard error of each coefficient is shown in parentheses. Significance at the 1%, 5%, and 10% levels are indicated by ***, **, and *, respectively.

36

ACCEPTED MANUSCRIPT

Duality %_State %_LegalPerson %_Management Ln_Shareholders Woman_CEO Ln_Employee Leverage Ln_FirmAge

Obs R2

**

*** ***

***

*** ***

16,885

14,704

0.07

0.07

3.89 (1.43) 0.18 (0.08) -0.03 (0.03) -0.04 (0.02) 0.09 (0.03) 0.11 (0.03) -0.12 (0.08) -0.06 (0.01) -0.25 (0.1) 0.03 (0.01) -0.53 (0.04) -0.03 (0.01)

*** **

* *** ***

***

15,875

** ** *** ***

0.43 * (0.25) -0.06 (0.78) 0.20 (0.18) -0.07 (0.07) 0.23 *** (0.08) -0.01 (0.09) -0.52 (0.32) -0.01 (0.04) 0.23 (0.21) 0.03 (0.02) -0.15 (0.22) -0.06 * (0.03)

IP CR

0.14 *** (0.04) 0.22 *** (0.06) 0.01 (0.02) 0.00 (0.01) 0.11 *** (0.02) 0.13 *** (0.02) 0.00 (0.04) -0.05 *** (0.01) 0.00 (0.02) 0.00 (0.01) -0.56 *** (0.04) -0.03 *** (0.01)

FE

MA NU S

Ln_BoardSize

***

(4)

ED

%_Independent

0.13 (0.05) 0.12 (0.06) 0.00 (0.02) -0.01 (0.01) 0.10 (0.02) 0.12 (0.02) 0.01 (0.03) -0.05 (0.01) 0.01 (0.02) 0.01 (0.01) -0.55 (0.04) -0.03 (0.01)

(3)

PT

%_Women

(2)

Arellano Bond

CE

(1)

FE with IV

AC

FE with Lagged Board Variables

FE

ROA (Net Income/Assets)

6,633

T

ROS (Net Income/Sales)

(5)

0.03 (0.01) 0.03 (0.01) 0.00 (0.00) 0.00 (0.00) 0.03 (0.00) 0.03 (0.00) -0.02 (0.01) -0.02 (0.00) 0.01 (0.00) 0.01 (0.00) -0.18 (0.01) 0.00 (0.00)

FE with Lagged Board Variables (6)

*** ***

*** *** ** *** *** *** *** ***

0.03 *** (0.01) 0.04 *** (0.01) 0.00 (0.00) 0.00 (0.00) 0.03 *** (0.00) 0.04 *** (0.00) -0.02 ** (0.01) -0.02 *** (0.00) 0.01 *** (0.00) 0.00 *** (0.00) -0.18 *** (0.01) -0.01 ** (0.00)

16,920

14,733

0.17

0.16

FE with IV

Arellano Bond

(7) 0.97 (0.34) 0.05 (0.02) -0.01 (0.01) -0.01 (0.01) 0.02 (0.01) 0.03 (0.01) -0.05 (0.02) -0.02 (0.00) -0.06 (0.03) 0.01 (0.00) -0.17 (0.01) -0.01 (0.00) 15,905

(8) *** ***

* *** *** *** *** ** *** *** *

0.07 (0.05) 0.08 (0.15) 0.07 (0.04) -0.02 (0.02) 0.04 (0.02) -0.01 (0.02) -0.11 (0.07) -0.01 (0.01) 0.01 (0.02) 0.01 (0.00) -0.02 (0.02) -0.01 (0.01)

*

**

**

*

6,659

37

ACCEPTED MANUSCRIPT

Table 4

AC

CE

PT

ED

MA NU S

CR

IP

T

Effect of the percent of women directors on firm performance: robustness test. This table presents regression results of model (1) as in Table 3 except that ROS is calculated as operating income divided by sales and ROA is calculated as operating income divided by assets. See Table 1 for the description of independent variables and Table 3 for the description of the FE, FE with lagged board variables, FE with IV and Arellano-Bond methods. Year and firm fixed effects are controlled in all regressions. The robust standard error of each coefficient is shown in parentheses. Significance at the 1%, 5%, and 10% levels are indicated by ***, **, and *, respectively.

38

ACCEPTED MANUSCRIPT

Duality %_State %_LegalPerson %_Management Ln_Shareholders Woman_CEO Ln_Employee Leverage Ln_FirmAge

Obs 2

R

*** ***

***

*** *** ***

16,867

14,686

0.06

0.06

** **

*** ***

***

15,862

*

*** *** ***

0.55 (0.29) -0.18 (0.74) 0.42 (0.18) 0.00 (0.07) 0.26 (0.1) 0.04 (0.11) -0.35 (0.39) -0.01 (0.04) -0.13 (0.33) 0.04 (0.02) -0.25 (0.07) -0.03 (0.03)

IP *

CR

3.09 (1.35) 0.21 (0.09) 0.00 (0.03) -0.03 (0.02) 0.09 (0.03) 0.15 (0.03) -0.06 (0.09) -0.06 (0.01) -0.19 (0.1) 0.06 (0.01) -0.62 (0.05) -0.03 (0.01)

(5)

MA NU S

Ln_BoardSize

**

0.05 (0.06) 0.16 ** (0.06) 0.01 (0.02) -0.01 (0.01) 0.09 *** (0.02) 0.17 *** (0.03) 0.09 (0.11) -0.05 *** (0.01) 0.01 (0.02) 0.04 *** (0.01) -0.63 *** (0.05) -0.05 *** (0.01)

FE

(4)

**

***

ED

%_Independent

0.04 (0.06) 0.17 (0.08) 0.02 (0.02) 0.00 (0.01) 0.09 (0.02) 0.14 (0.03) 0.04 (0.06) -0.05 (0.01) 0.02 (0.02) 0.05 (0.01) -0.63 (0.05) -0.03 (0.01)

(3)

PT

%_Women

(2)

Arellano Bond

CE

(1)

FE with IV

AC

FE with Lagged Board Variables

FE

ROA (Operating Income/Assets)

6,629

T

ROS (Operating Income/Sales)

** ***

0.02 (0.01) 0.04 (0.01) 0.00 (0.00) 0.00 (0.00) 0.02 (0.00) 0.03 (0.00) -0.02 (0.01) -0.02 (0.00) 0.01 (0.00) 0.01 (0.00) -0.18 (0.01) -0.01 (0.00)

FE with Lagged Board Variables (6)

**

FE with IV (7)

0.02 ** (0.01) 0.04 *** (0.01) 0.00 (0.00) 0.00 (0.00) 0.02 *** (0.00) 0.04 *** (0.00) -0.02 ** (0.01) -0.02 *** (0.00) 0.01 *** (0.00) 0.01 *** (0.00) -0.18 *** (0.01) -0.01 *** (0.00)

0.91 (0.32) 0.05 (0.02) -0.01 (0.01) -0.01 (0.00) 0.02 (0.01) 0.03 (0.01) -0.05 (0.02) -0.02 (0.00) -0.05 (0.02) 0.01 (0.00) -0.18 (0.01) -0.01 (0.00)

16,890

14,705

15,874

0.17

0.16

***

*** *** ** *** *** *** *** ***

Arellano Bond (8) *** ***

** *** *** *** *** ** *** *** **

0.09 (0.04) 0.03 (0.14) 0.06 (0.04) -0.01 (0.02) 0.03 (0.02) 0.00 (0.02) -0.08 (0.07) -0.02 (0.01) -0.01 (0.02) 0.01 (0.00) -0.04 (0.01) -0.01 (0.01)

**

*

** ***

6,635

39

ACCEPTED MANUSCRIPT Table 5

FE with Lagged Board Variables

Obs R

2

FE

0.02 (0.01) 0.03 (0.01) 0.03 (0.01) 0.01 (0.00)

16,885

14,704

6,633

0.07

0.07

CE

Woman_CEO

FE with Lagged Board Variables

0.31 (0.27) 0.58 (0.44) -0.10 (0.76) 0.22 (0.21)

AC

%_Independent

ROA (Net Income/Assets)

0.10 (0.07) 0.16 *** (0.06) 0.23 *** (0.06) -0.01 (0.02)

PT

%_ExecutiveWomen

0.06 (0.07) 0.18 *** (0.06) 0.14 ** (0.06) 0.01 (0.02)

ED

%_IndependentWomen

Arellano Bond

MA

FE

NU

ROS (Net Income/Sales)

SC

RI P

T

Independent versus executive women directors on firm performance. This table presents regression results of model (1) where board gender diversity is replaced by the percent of women independent directors (%_IndependentWomen) and the percent of women executive directors (%_ExecutiveWomen). See Table 1 for the description of independent variables and Table 3 for the description of the FE, FE with lagged board variables and Arellano-Bond methods. Year and firm fixed effects are controlled in all regressions. To save space, the estimation results of control variables are omitted in the table, except for the results on %_Independent and Woman_CEO. The robust standard error of each coefficient is shown in parentheses. Significance at the 1%, 5%, and 10% levels are indicated by ***, **, and *, respectively.

*

Arellano Bond

0.01 (0.01) 0.03 *** (0.01) 0.05 *** (0.01) 0.01 *** (0.00)

0.08 (0.05) 0.06 (0.08) 0.10 (0.15) 0.02 (0.02)

16,920

14,733

6,659

0.17

0.16

*** *** ***

40

ACCEPTED MANUSCRIPT Table 6

Obs R

2

0.05 * (0.03) 0.22 *** (0.06) 0.00 (0.02)

PT

Woman_CEO

16,885

CE

%_Independent

0.06 ** (0.03) 0.13 ** (0.06) 0.02 (0.02)

0.07

Arellano Bond

14,704 0.07

0.05 (0.14) 0.00 (0.75) 0.28 (0.21) 6,633

ROA (Net Income/Assets) FE with Lagged Board Variables

FE

0.02 *** (0.00) 0.03 *** (0.01) 0.01 *** (0.00) 16,920 0.17

0.01 *** (0.01) 0.04 *** (0.01) 0.01 *** (0.00) 14,733

Arellano Bond

0.02 (0.03) 0.13 (0.15) 0.02 (0.02) 6,659

0.16

AC

Woman_Chair

ED

FE

MA

FE with Lagged Board Variables

NU

ROS (Net Income/Sales)

SC

RI P

T

Effect of women board chairs on firm performance. This table presents regression results of model (1) where board gender diversity is replaced by the dummy variable woman board chair (Woman_Chair). See Table 1 for the description of independent variables and Table 3 for the description of the FE, FE with lagged board variables and Arellano-Bond methods. Year and firm fixed effects are controlled in all regressions. To save space, the estimation results of control variables are omitted in the table, except for the results on %_Independent and Woman_CEO. The robust standard error of each coefficient is shown in parentheses. Significance at the 1%, 5%, and 10% levels are indicated by ***, **, and *, respectively.

41

ACCEPTED MANUSCRIPT Table 7

D_2Women D_3Women

Obs

-0.01 (0.01) 0.02 * (0.01) 0.06 *** (0.02)

16,885

14,704

0.07

0.07

FE with Lagged Board Variables

FE

Arellano Bond

-0.07 (0.05) 0.05 (0.08) 0.19 (0.12)

0.00 (0.00) 0.00 ** (0.00) 0.01 *** (0.00)

0.00 (0.00) 0.00 ** (0.00) 0.01 ** (0.00)

0.00 (0.01) -0.01 (0.02) 0.05 ** (0.02)

6,633

16,920

14,733

6,659

0.16

0.16

CE

2

Arellano Bond

ROA (Net Income/Assets)

AC

R

0.01 (0.01) 0.02 ** (0.01) 0.06 *** (0.02)

PT

D_1Woman

ED

FE

MA

FE with Lagged Board Variables

NU

ROS (Net Income/Sales)

SC

RI P

T

Effect of the number of women directors on firm performance. This table presents regression results of model (1) where board gender diversity is measured by a set of dummy variables D_1Woman, D_2Women and D_3Women. See Table 1 for the description of independent variables and Table 3 for the description of the FE, FE with lagged board variables and Arellano-Bond methods. Year and firm fixed effects are controlled in all regressions. To save space, the results of control variables are omitted in the table. The robust standard error of each coefficient is shown in parentheses. Significance at the 1%, 5%, and 10% levels are indicated by ***, **, and *, respectively.

42

ACCEPTED MANUSCRIPT Table 8

AC

CE

PT

ED

MA

NU

SC

RI P

T

Women directors, firm performance and corporate ownership. This table presents regression results of %_Women on firm performance for subsamples classified by corporate ownership. Panel A shows the results for firms with state ownership but without legal person ownership, Panel B for firms without state ownership but with legal person ownership, Panel C for firms with state ownership larger than legal person ownership, and Panel D for firms with legal person ownership larger than state ownership. See Table 1 for the description of independent variables and Table 3 for the description of the FE, FE with lagged board variables and Arellano-Bond methods. Year and firm fixed effects are controlled in all regressions. The robust standard error of each coefficient is shown in parentheses. To save space, the results of control variables are omitted in the table. Significance at the 1%, 5%, and 10% levels are indicated by ***, **, and *, respectively.

43

ACCEPTED MANUSCRIPT ROS (Net Income/Sales)

Obs

2

%_Women

Obs 2

SC

3,781

3,462

0.17

0.16

Panel B: Firms without state ownership, with legal person ownership 0.55 *** 0.35 *** 0.97 ** 0.07 *** 0.06 *** (0.16) (0.13) (0.37) (0.02) (0.02) 3,947

3,239

0.09

0.09

1,453

3,963

3,253

0.18

0.17

PT

Panel C: Firms with state ownership larger than legal person ownership 0.04 0.03 0.26 0.01 -0.01 (0.06) (0.07) (0.5) (0.01) (0.01) 8,135

7,202

0.07

0.07

CE

Obs

R

0.07

2

%_Women

R

0.08

1,582

NU

%_Women

R

3,458

3,116

8,146

7,211

0.19

0.18

Panel D: Firms with legal person ownership larger than state ownership 0.28 *** 0.19 ** 0.62 * 0.03 ** 0.03 ** (0.11) (0.09) (0.33) (0.02) (0.02)

AC

R

3,777

2

MA

Obs

FE

Panel A: Firms with state ownership, without legal person ownership -0.03 0.01 0.18 0.02 0.01 (0.07) (0.07) (0.25) (0.02) (0.02)

ED

%_Women

Arellano Bond

RI P

FE

FE with Lagged Board Variables

6,015

5,020

0.08

0.08

Arellano Bond

T

FE with Lagged Board Variables

ROA (Net Income/Assets)

2,194

6,030

5,031

0.16

0.15

-0.05 (0.07) 1581

0.22 ** (0.09) 1,470

-0.02 (0.08) 3123

0.17 ** (0.08) 2213

44

ACCEPTED MANUSCRIPT Table 9

T

Effect of ownership on board gender diversity. This table presents the panel fixed effects regression results of model (2):

NU

SC

RI P

where board gender diversity is measured by %_Women and corporate ownership is measured by %_State and %_LegalPerson. Set I includes the control variables used in the main regression model (1) plus a new control variable of firm performance. Set II includes all control variables in Set I plus a new control variable of the lag of %_Women. Set III includes all control variables in Set II plus the lag of firm performance. Year and firm fixed effects are controlled in all regressions. To save space, only regression results on %_State and %_LegalPerson are reported in the table. The robust standard error of each coefficient is shown in parentheses. Significance at the 1%, 5%, and 10% levels are indicated by ***, **, and *, respectively.

R2

16,886 0.04

III

I

II

III

0.001 (0.005) -0.004 (0.005)

-0.001 (0.005) -0.003 (0.005)

0.003 (0.008) 0.001 (0.009)

0.001 (0.005) -0.004 (0.005)

0.000 (0.005) -0.002 (0.005)

14,709

14,675

16,920

14,733

14,702

0.41

0.40

0.04

0.41

0.40

PT

Obs

CE

%_LegalPerson

0.003 (0.008) 0.001 (0.009)

Dependent variable %_Women; Performance measured by ROA

AC

%_State

II

ED

I

MA

Dependent variable %_Women; Performance measured by ROS

45