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Do firms with more corporate sustainability attract foreign

institutional ownership across the world?

Jyotirmoy Podder a*, Sudipta Bose b, Ferdinand A. Gul c a Torrens University Australia, 88 Wakefield Street, Adelaide, SA 5000, Australia b School of Accounting, UNSW Business School, UNSW Australia, Kensington, NSW 2052, Australia c Department of Accounting and Finance, Monash University Malaysia, Jalan Lagoon Selatan, 47500 Bandar Sunway, Selangor Darul Ehsan, Malaysia * Corresponding author. Tel.: + 61 8 8113 7816 Email addresses: jyotirmoy.podder@tua.edu.au (J. Podder)

sudipta.bose@unsw.edu.au (S. Bose) f.a.gul@monash.edu (F.A. Gul)

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Do firms with more corporate sustainability attract foreign

institutional ownership across the world?

ABSTRACT

Drawing on prior studies on foreign institutional ownership and the importance of

corporate sustainability in attracting share ownership, this study examines whether corporate

sustainability is associated to foreign institutional ownership around the world. Using 14,389

firm-year observations over 2002-2010 from 39 countries, we show that foreign institutional

ownership is positively associated to corporate sustainability. Moreover, we find that

corporate sustainability is positively associated to firm values. This suggests that sustainable

firms also accumulate more wealth for their shareholders. Furthermore, we document that

more sustainable firms (1) maintain sustainability report quality, (2) have a higher probability

of wining corporate citizenship awards, and (3) have a higher likelihood of implementing

sustainability audit. These results suggest a possible information channel through which

institutional owners obtain information about sustainable firms. Our results are robust to

different specifications and alternative proxies for corporate sustainability.

JEL classification: G3, M4, Q2

Key words: Corporate sustainability; foreign institutional ownership; stakeholder orientation;

firm value; information asymmetry

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1. Introduction

More and more companies are increasingly recognizing the importance of corporate

sustainability to their long-term success (Paine, 2014). Corporate sustainability may be

defined as “the set of behaviors that meets the needs of the present without compromising the

ability of future generations to meet their own needs; such behaviors often involve

environmental activity and sustainable consumption” (Grinstein and Riefler, 2015, p.1).

Another way of looking at sustainability is through the lens of the firm’s strategy that is

designed to create value for their shareholders, while at the same time contributing to a

sustainable society (Eccles and Serafeim, 2013). It thus aims to address the social,

environmental and economic aspects of sustainbale development (Takala and Pallab, 2000).

At the same time, increasingly, institutional investors have started to show an interest

in companies that adopt enviornmental and social investment policies. For example,

Waygood (2014) points out that institutional investors are interested in corporations that do

sustainable business since it leads to long term finacial performance and lower cost of capital.

The growing concern about sustainable performance is also reflected by the increase in

issuance of sustainability reports. For example, compared to only five percent (5.41%) of

ASSET4 companies issuing sustainability reports in 2002, fifty-two percent (52.15%) of

ASSET4 companies in 2010 issued such reports.1 The Corporate Sustainability Reporting

Coalition created by institutional investor, Aviva Investors, in 2011 representing investors

with US$ 2 trillion has also pushed for more corporate sustainability reporting (Gleeson-

White, 2014, p. 138).

1 Whilst the most popular and available databases on CSR include MSCI ESG (formerly known as KLD), ASSET4, Bloomberg, and Sustainalytics, only ASSET4 provides integrated performance (combining economic, environmental, social, and governance performance). Although KLD is the widely used database for CSR, but this only covers US companies. Moreover, KLD includes indicator (i.e., 0 or 1) data about different environmental and social aspects and so the CSR variable construction using this database is largely driven by the choice of the researchers. The detail of the ASSET4 database is furnished in Section 3. Please see Cheng et al. (2013) for more discussion on ASSET4.

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As institutional owners are driving the environmental, social and governance (ESG)

discussion and emphasizing the integration with the economic performance (WBCSD and

UNEP FI, 2010), their ownership should be associated to corporate sustainability.2 While

institutional ownership can be both domestic and foreign, foreign institutional ownership

(FIO) is particularly important in an international context due to its role in international

corporate governance. Foreign institutional ownership has increased from ten percent

(10.41%) in 2002 to twenty two percent (21.98%) in 2010 for the companies included in the

ASSET4 database. As increased foreign institutional investment has become an important

engine for economic growth, an understanding of the association between sustainability and

foreign institutional ownership would be useful for both firms and policy makers. The

scarcity of similar research motivates us to examine the association between corporate

sustainability and foreign institutional ownership in a global setting.

Given the arguments that corporate sustainability is a factor that can improve the

reputation and value for firms and thus attract foreign institutional ownership, we examine

whether corporate sustainability is positively related to foreign institutional ownership. We

use the theoretical perspectives of stakeholder wealth/profit maximization to make a case for

the positive link between sustainability and foreign institutional investors. According to the

theory of stakeholder value maximization, a firm is viewed as a nexus of contracts between

shareholders and other stakeholders in which each group of stakeholders supplies the firm

with critical resources (Coase, 1937). Thus, a well-organized stakeholder relationship is an

important factor for firm performance and the survival of a firm in the long term (Freeman et

al., 2004). Focusing on the interests of other stakeholders increases shareholders’ willingness

to support a firm’s operation (Deng et al., 2013). Foreign institutional investors are an

2 While the annual reports and proxy files provide detailed information about financial and governance aspects of a company, the sustainability reports also highlight the social and environmental performance. So, to capture both financial and extra financial health of firms, sustainable performance includes economic, environmental, social, and governance performance.

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important component of the stakeholders who provide monitoring to the firms they invest in.

As sustainable firm performance may be influenced by a country’s stakeholder orientation

(Simnett et al., 2009; Dhaliwal et al., 2012), we also incorporate the influence of country

level stakeholder orientation on this relation. Firms operating in a more stakeholder-oriented

country are expected to have better sustainable performance and so are likely to attract more

foreign institutional owners. Moreover, we analyze whether corporate sustainability is

positively related to firm value from the agency theory perspective. More sustainable firms

attract more foreign institutional ownership, which is expected to reduce agency problems

through their monitoring activities (Aggarwal et al., 2011). This is because large foreign

institutional holding can reduce the free rider problem arising from the division of ownership

among many shareholders (Ferreira et al., 2010). Less agency problem is associated with

higher firm profits and higher firm value. So, following this line of reasoning, corporate

sustainability is expected to be positively related to firm value. We further analyze whether

sustainability offers an information channel through which investors can obtain information

about sustainable firms.

To test our hypotheses, we use a sample of 14,389 global firm-year observations over

2002-2010. Our findings suggest that corporate sustainability is positively related to foreign

institutional ownership. The evidence in this paper is consistent with the “stakeholder value

maximization” theory that foreign institutional investors invest more in firms with better

sustainable performance. Moreover, we show that this relationship is more pronounced in

countries with higher stakeholder orientation. This supports the influence of country level

stakeholder orientation since we demonstrate that while foreign institutional investors invest

in firms with better sustainable performance, the relationship is stronger in countries with

higher stakeholder orientation.

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We apply change analysis to address causality. To address endogeneity arising from

reverse causality, we examine sustainability and foreign institutional ownership using

unexplained sustainability as an exogenous variable. We address the potential selection bias

by using the Heckman (1979) two-stage procedure with an instrumental variable.

Government party ideology, following Dutt and Mitra (2005), is included as an instrument to

sustainability as left wing governments have a more socialist oriented view than their right

wing and other counterparts (Pettersson-Lidbom, 2008). We cross check the Heckman results

with propensity score matching following Lennox et al. (2012) and Hoi et al. (2013). We also

show evidence in support of monitoring role of foreign institutional owners by documenting

that more sustainable firms have higher firm values. This is consistent with the findings of

Cheng et al. (2013) and Dhaliwal et al. (2011) on the benefits of non-financial performance

and corporate social responsibility (CSR).

Our study of the direct impact of sustainability on foreign institutional investors

contributes to both the corporate governance and sustainability literature in the following

ways. First, it contributes to the governance literature by showing that foreign institutional

investors are attracted to firms with sustainable performance. Second, we contribute to the

literature on the determinants of institutional investors by showing that firms wishing to

increase institutional investors should pay more attention to sustainability issues. Third, we

contribute to the sustainability literature by documenting the relationship of sustainability

with firm value, sustainability report quality, corporate citizenship award, and sustainability

audit. Whereas prior studies (Ghoul et al., 2011; Dhaliwal et al., 2012; Yongtae et al., 2012;

Cheng et al., 2013; Deng et al., 2013) on sustainability primarily focus on non-financial

performance such as CSR performance, our measure is an integrated one that includes both

financial and non-financial performance.

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The remaining sections of the paper proceeds as follows. In section 2 we review the

literature and develop the testable hypotheses of the paper. In section 3 we describe the data

and methodology of empirical investigation. Section 4 reports the results. In section 5, we

present the results of our additional analyses and robustness tests. Section 6 concludes the

paper.

2. Literature review and hypotheses development

Prior studies have examined the relation of corporate social responsibility with

external financing constraints (Cheng et al., 2013), stakeholder value (Deng et al., 2013), cost

of equity (Dhaliwal et al., 2011), and crash risk (Kim et al., 2014), but have largely ignored

the impact of sustainability on institutional investors, arguably the most important investors

who play a pivotal role in monitoring and corporate control.

2.1. Corporate sustainability

The term corporate sustainability emerged in the 1980s but in recent years the concept

has gone viral. According to the World Commission on Environment and Development

(1987), “sustainability is the environmental, economic and social wellbeing for today and

tomorrow.” Another way of putting this is to say that a sustainable society is “one that meets

the demands of the current generation without sacrificing the needs of future generations”

(Eccles and Serafeim, 2013). In short sustainable performance offers many benefits to a firm.

The benefits come from easier and cheaper means of raising finance, more analyst following,

reduced litigation risk, increased brand value, increased operational efficiency and improved

financial performance (see Gleeson-White, 2014).

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It is important to note that sustainability is a broader concept than corporate social

responsibility as sustainability covers both financial or economic and non-financial or CSR.3

However, prior literature primarily emphasizes the importance of CSR and has not integrated

economic (or financial) performance with environmental, social and governance performance

to measure the sustainable performance of a firm. As such, our literature review heavily relies

on the CSR literature as it is a component of sustainability.

The extant literature on CSR has investigated the relationship between CSR and

financial performance from the theoretical and empirical viewpoint. Taking the agency-cost

perspective, a number of studies have argued that firm's CSR activities increases unnecessary

costs that places a firm in a competitively disadvantaged position (Friedman, 1970; Aupperle

et al., 1985; McWilliams and Siegel, 1997; Jensen, 2002). These studies also argue that

managers use CSR activities to extract personal benefits, such as advancing their careers or

pursuing their personal agenda, rather than financial benefits to the shareholders. A few

studies have supported the view that practicing CSR brings less transparent and reliable

accounting information. For example, Prior et al. (2008) show that regulated firms with more

CSR activities are engaged in earnings management.

On the other hand, a large number of studies have argued that CSR offers many

benefits to a firm. The benefits come from better access to firm's valuable resources

(Waddock and Graves, 1997), attract and retain talented employees and motivate them to

improve productivity (Waddock and Graves, 1997; Greening and Turban, 2000; Roberts and

Dowling, 2002; Edmans, 2011), better marketing of firm's products and services (Fombrun,

1996), attract socially conscious consumers (Hillman and Keim, 2001), raise external

3 The difference between sustainability and CSR is not very clear in the literature. Hence, sustainability is sometimes alternatively used as corporate responsibility, social responsibility, and environmental, social and governance (ESG). There appear, however, differences between sustainability and CSR if we follow the definition of sustainability provided by the Global Reporting Initiative (GRI). GRI (2015) defines a sustainability report as a report about a company’s economic, environmental, social and governance impacts caused by its everyday activities. CSR, however, excludes economic performance.

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financing from socially responsible investors (Kapstein, 2001), positive media coverage

(Borghesi et al., 2014), and more favourable treatment by regulators and policy makers

(Brown et al., 2006).

Recently, a number of studies have shown that firms with better CSR performance

gain benefits in the capital market.4 Specifically, Dhaliwal et al. (2011) focus on a sample of

US firms and show that firms with a higher cost of equity capital are more likely to issue

standalone CSR reports and that issuing firms with superior CSR performance enjoy a

subsequent reduction in the cost of equity capital. El Ghoul et al. (2011) find that firms with

better CSR performance have cheaper equity financing based on firms from the US. Kim et

al. (2014) document that socially responsible firms have a lower future stock price crash risk

for a sample of US firms. Moreover, Cheng et al. (2013) show that firms with better CSR

performance significantly enjoy lower capital constraints. Dhaliwal et al. (2012) find that

firms with the issuance of stand-alone CSR reports have lower analyst forecast error. In the

context of debt market, Goss and Roberts (2011) show that socially responsible firms pay less

for cost of bank loans compared to their counterparts. Further, a number of studies have

examined the impact of CSR on the firm's financial reporting environment. For example,

Yongtae et al. (2012) provide evidence that socially responsible firms are less engaged in

both accruals-based and real-activity earnings management. Hoi et al. (2013) find that firm

with excessive irresponsible CSR activities are more aggressive in avoiding taxes. Gelb and

Strawser (2001) document that firms with higher CSR performance provide more financial

disclosure.

In this study, we contribute to this emerging literature that examines the impact of

sustainability performance on the firm's critical resources providers i.e., foreign institutional

4 Crifo et al. (2015) find that entrepreneurs who do not manage environmental, social and governance issues are likely to suffer limited access to private equity, with a higher cost of capital, hence penalizing their shareholders by destroying firm value.

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investors. Unlike prior studies that focused mainly on US firms, our findings are based on a

broader range of samples from 39 countries thus providing some international evidence.

2.2. Foreign institutional ownership

The influence of institutional investor especially foreign institutional investors in the

corporate sector has increased over the years. The role of these institutional investors is

especially important in developed countries such as the US, UK and Australia where

institutional investors have significant concentration of equity ownership (OECD, 2011).

According to a report by the Centre for European Policy Studies (1995), pension funds from

the US and UK made up around 72% of the total pension funds in western countries,

implying that they could be instrumental in shaping the corporate governance standards. This

is reflected in an international study by Aggarwal et al. (2011) who examine the impact of

institutional investors on corporate governance for 23 countries and find that international

institutional investment is positively related to firm-level governance. They also find that

institutional investors from countries with strong investor protection play an important role to

improve corporate governance in non US countries.

Generally, the institutional investors could exercise their power through direct and

indirect monitoring (Ferreira and Matos, 2008; Aggarwal et al., 2011). The direct monitoring

refers to the direct influence on management or to voice up their dissatisfaction or

shareholder interests to the management (“voice”), while the indirect monitoring is the action

that could be taken by selling the shareholdings in a firm (“voting with their feet”) and

pushing up the cost of capital.

Foreign institutional owners play an important role in corporate control by protecting

the firm from takeovers. Corporate control transactions could be reduced if the foreign

institutional investors tend to work towards promoting better corporate governance which

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mitigates the agency conflicts in the firms (Ferreira et al., 2010). Besides, the opening up of

capital markets which enable shareholders to invest abroad is expected to reduce the

importance of diversification through merger and acquisitions. The diversification theory

advanced by Adler and Dumas (1975) and Errunza and Senbet (1984) suggests that capital

market imperfections drive international diversification. Companies tend to diversify

internationally through mergers and acquisitions if there is a barrier for investors to invest in

foreign stocks. The alternative view is that the foreign institutional investors can actually

facilitate cross-border mergers. One reason is because foreign institutional investors can

reduce information asymmetry between bidders and targets in international takeovers.

Another reason is that large foreign institutional holding can reduce the free rider problem as

a result of the dispersion of ownership among many shareholders (Shleifer and Vishny,

1986). Moreover, foreign institutional owners are less entrenched by ties with management or

by private benefits. While Ferreira et al. (2010) support the facilitating role by showing that

foreign institutional ownership increases the probability of cross border mergers and

acquisitions, the monitoring role has also been well documented (Ferreira and Matos, 2008).

2.3. Corporate sustainability and foreign institutional ownership

According to the stakeholder value maximization theory, corporate sustainability has

a positive effect on shareholder wealth because focusing on the interests of other stakeholders

increases their willingness to support a firm's operation, which increases shareholder wealth.

This is because a firm is viewed as a nexus of contracts between shareholders and other

stakeholders in which each group of stakeholders supplies the firm with critical resources

(Deng et al., 2013). Foreign institutional owners are stakeholders that offer financial

resources. As institutional investors, they consider not only financial performance but also

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non-financial performance of a firm.5 According to the Global Reporting Initiative (2015),

the sustainability report includes both financial (and economic) and non-financial

performance. As such, more sustainable performance should attract more foreign institutional

investors. This reasoning leads to the following hypothesis:

H1: Corporate sustainability is positively associated to foreign institutional

ownership.

Sustainable firm performance may be influenced by a country’s stakeholder

orientation (Simnett et al., 2009; Dhaliwal et al., 2012). According to resource dependence

theory of Salancik and Pfeffer (1978), a firm depends on the resources in its environment for

its survival and, thus, will be more concerned about the groups that can significantly

influence the supply of the resources critical to its operations. Hence, in countries with a

higher level of stakeholder orientation, stakeholder groups such as employees, consumers, the

government, and communities are likely to have a greater influence on firms’ operational

decisions. Therefore, our second hypothesis predicts that firms operating in a more

stakeholder-oriented country are expected to have better sustainable performance and so can

attract more foreign institutional owners.

H2: The positive association between sustainable performance and foreign

institutional ownership is stronger for countries with higher stakeholder

orientation.

5With a unique dataset of multiple ownership of institutional investors, we find that institutional owners invest more in sustainable firms. We use the Thomson 13F institutional ownership data over 1991-2012 to identify the institutional investors with multiple ownerships. We then rank their ownerships based on the median ownership of each institutional investor. A firm with higher than the median ownership is ranked as HIGH and lower than the median as LOW. Subsequently, HIGH is coded as 1 and LOW is coded as 0. We then combine this data with the MSCI ESG database. We calculated sustainability following Kim et al. (2014).

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3. Research methodology

3.1. Measures of sustainability

Our primary measure of sustainability is an equal-weighted rating of economic,

environmental, social and corporate governance performance (SUST). It reflects a balanced

view of a company's performance in these four areas. The ASSET4 ESG framework allows to

rate and compare companies against approximately 700 individual data points, which are

combined into over 250 key performance indicators (KPIs). These KPI scores are aggregated

into a framework of 18 categories grouped within 4 pillars that are integrated into a single

overall score. Appendix A provides with a summary of the pillars, categories and some

sample data points. Indicators, categories, pillars and overall score are calculated by equally

weighting and z-scoring all underlying data points and comparing them against all companies

in the ASSET4 universe. The resulting percentage is therefore a relative measure of

performance, z-scored and normalized to better distinguish values and position the score

between 0% and 100%.

< Appendix A >

3.2. Methodology

We use the following baseline model for foreign institutional ownership and

sustainability following Ferreira et al. (2010).

FIO = β0 + β1*SUST + β2*FSIZE + β3*MB + β4*IOP + β5*RET + β6*TURN

+ β7*DY + β8*ROE + β9*IRISK + β10*LEV + β11*CASH + β12*CLOSE

+ β13*DOM + β14*ADR + β15*DISC + β16*DIST + β17*LEGAL + β18*LNGDP

+ β19*CMCAP + β20*ENGLISH + Year Dummies + Industry Dummies + ε (1)

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Our dependent variable is foreign institutional ownership (FIO) and independent

variable is corporate sustainability (SUST).6 We include a number of variables to control for

firm level and country level characteristics.

We include firm size (FSIZE) because all institutional owners have a strong

preference for the stock of large firms (Ferreira and Matos, 2008). Foreign institutional

investors prefer value stocks (Gompers and Metrick (2001) and so we include the ratio of

market-to-book (MB). Foreign institutional investors also have a higher propensity to invest

in firms with higher investment opportunities and recent stock returns (Ferreira and Matos,

2008). Hence, we include investment opportunities (IOP) and stock returns (RET). We also

control the level of share turnover (TURN) as institutional investors prefer more liquid stocks

(Bushee and Noe, 2000). Foreign institutions avoid high dividend paying stock due to tax

withholding concerns (Ammer et al., 2006; Ferreira and Matos, 2008) and so dividend yield

(DY) is controlled. The return on equity (ROE) is included to capture the preference of

foreign institutional owners for firms with proven profitability. Institutional investors have a

tendency to invest in stocks that are more informative (Roll, 1988; Morck et al., 2000) and so

idiosyncratic volatility (IRISK) is included to proxy for stock price informativeness. We also

control for leverage (LEV) and cash holdings (CASH). Firms with concentrated control rights

are less preferred by foreign institutional investors (Ferreira and Matos, 2008; Aggarwal et

al., 2011). Thus, we include the percentage of closely held shares (CLOSE). We include

domestic institutional ownership (DOM) to control for any substitutability between domestic

and foreign institutional ownerships. Foreign institutional investors prefer stocks with cross

listing on a US exchange (Ferreira and Matos, 2008; Aggarwal et al., 2011) and hence we

include ADR.

6 We set foreign institutional ownership values to zero if no stock is held by any foreign institutional owner in FactSet’s LionShare. We, however, repeat our analysis with non-zero values of foreign institutional ownership. Our results are not affected.

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Further, foreign institutional investors prefer stocks from countries with good

disclosure standards (DISC) and those countries that are closer to their local market (DIST).

Further, country level legal environment (LEGAL) is also included to control for institutional

investors’ preference to invest in countries with stronger legal environment (La Porta et al.,

1998). We also control for GDP per capita (GDP), developed markets (CMCAP) and

English-speaking countries (ENGLISH) to account for country level factors that influences

the institutional investor preferences for investment decisions. Some of the control variables,

including firms size, book-to-market ratio, stock returns, liquidity, leverage, country level

legal environment, have also been shown to affect sustainability performance in prior studies.

Thus, it provides another reason for controlling their potential impact in our regression

models. Appendix B presents the operational definition of our control variables.

< Appendix B>

3. 3. Sample selection

The steps of sample selection for our empirical estimation are reported in Table 1. We

use several data sources for our baseline regression model estimation: ASSET4 for

sustainability, FactSet’s LionShare for global institutional ownership, Compustat North

America for financial, Compustat Global for financial and global share price, CRSP for

market, I/B/E/S for analysts forecast, World Bank for macroeconomic, and GeoDist for

bilateral distance between countries. We merge firm-year observations in all these databases

over 2002-2010. Our sample period is restricted by limitations of the ASSET4 database

because it only covers data from 2002 onwards. Total number of firm-year observations

reported in ASSET4 over 2002-2010 are 20,287. When combining with Compustat North

America and Compustat Global, 1,734 observations are not matched. After removing 4,164

more firm-year observations with incomplete data, we obtain a final sample of 14,389 firm-

year observations over 2002-2010 for our baseline estimation.

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< Table 1>

3.4. Summary statistics

Table 2 reports summary statistics of the firm level variables for our different models.

Panel A presents the descriptive statistics of baseline model between foreign institutional

ownership and sustainability. The mean (median) of foreign institutional investors is 14.80

(9.90) percent which is higher than the mean (median) of foreign institutional investors of

3.60 (4.00) percent reported by (Ferreira and Matos, 2008). The average sustainability

performance is 0.53 which is comparable to average of 0.52 reported by Cheng et al. (2013).

The mean of our sample size is 8.75, reflects the fact that ASSET4 tend to cover large firms.

The mean market-to-book ratio is 2.912, indicates that stocks of our sample firms are traded

at prices well above their book value. The average (median) investment opportunities (IOP)

of 0.11 (0.08) is closer to the average (median) of 0.10 (0.05) of Ferreira and Matos (2008).

The mean (median) stock return (RET) of 17.50 (12.60) percent is higher than the average

(median) of 0.00 (2.10) percent reported in Ferreira and Matos (2008) reflecting that our

sample firms are more attractive in terms of stock returns. The mean (median) share turnover

(TURN) of our sample firms are 1.86 (1.38) which is higher compared to the mean (median)

of share turnover of 0.71 (0.35) reported by Ferreira and Matos (2008), indicates that our

sample firms are traded well in the stock market. In terms of dividend yield (DY), the average

(median) of DY is 2.10 (1.50) percent which is closer to the average (median) DY of 2.20

(1.60) percent of Ferreira and Matos (2008). The average (median) ROE of 12.20 (12.30)

percent is higher than the average (median) percentage of ROE 3.30 (6.40) percent reflects

that our sample firms are more profitable. The average (median) idiosyncratic volatility

(IRISK) is 0.01 (0.01) which is lower than the mean (median) of 16.70 (9.20) percent of

Ferreira and Matos (2008). The mean (median) of leverage (LEV) and cash holdings (CASH)

of 0.24 (0.23) and 0.13 (0.09) and are closer to the mean (median) of 0.25 (0.23) and 0.13

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(0.9) reported by Ferreira and Matos (2008). The average (median) percentage of firms

having closely held shares (CLOSE) is 23.90 (18.00) percent which is lower than the average

(median) of 45.70 (46.10) percent reported by Ferreira and Matos (2008), indicates that our

sample firms have less block ownership by insiders (e.g., managers and families). The mean

(median) of domestic institutional ownership is 29.60 (13.80). About 10.20 percent of sample

firms are cross listed (ADR) in US exchanges.

< Table 2 >

Table 3 presents the descriptive statistics of the country-level variables. The US has

the highest country-level disclosure standards (DISC) which is consistent with the common

notion that the US has the most transparent information environment whereas Philippine has

the least. The average headquarter distance (DIST) is the highest for firms operating in New

Zealand whereas firms operating in Austria has the lowest. The US and Canada has the

highest legal regime quality index (LEGAL) indicates that investors are well protected in US

and Canada whereas Belgium has the lowest. Further, Norway has the highest GDP whereas

India has the lowest. With regards to capital market development (CMCAP), Hong Kong as

the strongest developed capital market while Austria has the weakest developed market.

About 28.20 percent of our sample countries’ official language is English.

< Table 3 >

Table 4 presents the Pearson correlation matrix among the baseline model variables.

Consistent with our main hypothesis, sustainability performance (SUST) is significantly

positively correlated with foreign institutional investors (FIO). The highest correlations are

between TOBINQ and MB. However, they do not present multicollinearity concerns because

they are used in separate two models. We also run the correlation matrix for variables

included in other analysis (unreported) and do not find any potential for multicollinearity.

< Table 4 >

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4. Results and analysis

4.1. Univariate results

To analyze the relation between sustainability and foreign institutional ownership, we

begin with a univariate test on whether better sustainable firm attracts more foreign

institutional investments. We also examine whether better sustainable firms are significantly

different in terms of other characteristics included in our regression models. Our measure of

better sustainable (SUST) firm is a dummy where a firm is assigned 1 if its sustainable

performance is greater than the median sustainable performance of our sample firms;

otherwise 0 (NON_SUST).7 As reported in Table 2, our results show that foreign institutional

owners invest more in better sustainable firms. There is also a significant difference in

sustainable performance between the two clusters of sustainable firms.

4.2. Results for Hypothesis 1

Table 5 reports the results from regression analysis of the relation between sustainable

performance and foreign institutional ownership after controlling for other potential

determinants of foreign ownership.8 As reported in Column (1) of Table 5, our baseline

regression results suggest that corporate sustainable performance is positively associated with

foreign ownership. On average, change of 1 percentage point in sustainable performance is

positively related to approximately 3.70 percentage point change in foreign institutional

ownership (coefficient = 0.037, p < 0.01). Thus, the effect of sustainable performance on

foreign ownership is both statistically and economically significant.9 To estimate Equation

7 Median sustainable performance is computed by country, industry and year. 8 While we use contemporaneous analysis, our findings and conclusions remain unchanged when we use a one-year ahead measure of foreign institutional ownership.

9 To test whether sustainability significantly increases the explanatory power (R2) of our baseline model, we compute the F-statistic following Gujarati (2003) using the R-square statistics for the regressions with and without SUST. The Gujarati (2003) F-statistic, 93.216, is significant at 1 percent, indicating that SUST

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(1), we apply an ordinary least square regression method with standard errors clustered at the

firm level. Year and industry dummies are also included in our estimation to capture for year

and industry fixed effects.

< Table 5 >

4.3. Results for Hypothesis 2

Table 5 reports the results of the moderating effect of country level stakeholder

orientation (STAKE) on the relation between corporate sustainability (SUST) and foreign

institutional ownership (FIO). STAKE is measured, following Dhaliwal et al. (2012), as the

principal factor of important country level factors. These include the legal environment of a

country in protecting labor rights, mandatory disclosure requirements for CSR issues, and

public awareness of the CSR issues at the country level (see Dhaliwal et al., 2012 for details).

As reported in Column (2) of Table 5, the interaction term (STAKE*SUST) between STAKE

and SUST is positive and significant (coefficient = 0.028, p value < 0.01). This suggests that

foreign institutional owners invest in sustainable firms even more in countries with higher

stakeholder orientation. As our stakeholder orientation measure is following the Dhaliwal et

al. (2012) measure, our sample is limited to 31 countries that Dhaliwal et al. (2012) cover.10

5. Additional analyses and robustness

5.1. Change analysis

To provide evidence of a causal relationship, we consider whether changes in

sustainability lead to changes in foreign institutional ownership following Cahan et al. (2015)

and Gao et al. (2015). We estimate a change version of Equation (1) where we use the yearly

significantly increases the explanatory power (R2) of our main regression model. It suggests that corporate sustainability is a value relevant information. 10 Columbia, Egypt, Indonesia, Ireland, Israel, Peru, Taiwan, and Turkey are excluded from the interaction

effect analysis due to non-availability of stakeholder orientation data.

20

change in each variable except bilateral distance (DIST), legal quality (LEGAL) and English

language (ENGLISH). We include their level values as these variables are time invariant and

have no yearly changes. We also run the change model for hypothesis 2 including the level

values of stakeholder orientation (STAKE) as STAKE has the same value for a country

during the sample period. The interaction term between sustainability and stakeholder

orientation is thus ∆SUST * STAKE.

Table 6, Column (1) provides the results for Equation (1) using a changes

specification. We find that ∆SUST is positively and significantly related to change in foreign

institutional ownership, ∆FIO, at the 5% level, indicating the increases in sustainable

performance are related to increases in foreign institutional ownership. Column (2) of Table 6

reports the results for the moderating effect of stakeholder orientation. The interaction term,

∆SUST * STAKE, is significant at the 10% level, suggesting that changes in sustainability

has a higher effect on changes in foreign institutional ownership in countries with higher

stakeholder orientation.

< Table 6 >

5.2. Unexplained sustainability and foreign institutional ownership

A potential endogeneity problem could exist insofar as the main results in Table 5

may be due to reverse causality. Firms with high foreign institutional ownership may focus

more on corporate sustainability. To address endogeneity arising from such reverse causality,

we apply a two stage regression analysis. In the first stage, we run a regression to determine

sustainability using the determinants reported in Table 8. Our second stage regression is

equation (1) with the sustainability measured by the residuals from the first stage regression.

This approach follows Gul et al. (2011) and Lys et al. (2015). The residual (i.e., error term)

captures the unexplained sustainability. The rationale behind using the error term is that, if

the same firm characteristics used to predict the sustainability also explain most of the

21

variation in foreign institutional ownership, then sustainability is simply an aggregate proxy

for firm characteristics. On the other hand, if the unexplained part of sustainability explains

most of the variation in foreign institutional ownership, it is more likely to be causally linked

to sustainability. The results on the second stage regression with unexplained sustainability

reported in Column (1) of Table 7 show that sustainability is positively associated with

foreign institutional ownership (coefficient = 0.035, p-value < 0.01). The results presented in

Column (4) of Table 7 show that the positive association between sustainability and foreign

institutional ownership is stronger in countries with higher stakeholder orientation

(coefficient of STAKE*SUST = 0.017, p < 0.01).

< Table 7 >

5.3. Heckman (1979) procedure to address selection bias

The sample used in this study may be biased because firms that voluntarily issue

sustainability information may have better sustainability performance compared to firms that

do not. Specifically, it is possible that the factors affecting whether a firm issue sustainability

information may be correlated with our dependent variable - foreign institutional investors.

We therefore use a two-stage Heckman (1979) selection model to correct for any such sample

selection bias. Heckman selection model has two stages. In the first stage, as reported in

Table 8, we run a probit regression between inclusion into the Dow Jones Sustainability

Index (SUST_DJSI) and the factors that have impact on such inclusion. To fulfil the

exclusion criteria we include the party ideology of the government as an exogenous variable

that is only related to stakeholder orientation and hence to sustainability but not with foreign

institutional ownership. This is because all countries encourage institutional investment

irrespective of the ideology of the government party. We measure party ideology as a dummy

variable with 1 if the political ideology of the Government is left wing and 0 otherwise. The

definition of political ideology could be sensitive to the political system of a country (Dutt

22

and Mitra, 2005). If a country has a presidential system, it might be more appropriate to

consider the political ideology of the chief executive; whereas if the country has a

parliamentary system, the affiliation of the major party in the cabinet is more likely to

represent the political ideology of the government. Thus, we consider party ideology of the

chief executive in a presidential system, and that of the major party in the cabinet in a

parliamentary system. This is consistent with Dutt and Mitra (2005). As reported in Column

(2) of Table 7, sustainability is positively related to foreign institutional ownership after

addressing the selection bias (coefficient = 0.025, p-value < 0.01). The results presented in

Column (5) of Table 7 show that the positive association between sustainability and foreign

institutional ownership is stronger in countries with higher stakeholder orientation

(coefficient of STAKE*SUST = 0.025, p < 0.01).

< Table 8 >

5.4. Propensity score matching test

Following Lennox et al. (2012) and Hoi et al. (2013), we use the propensity score

matching (PSM) procedure to cross-check the result of the Heckman (1979) procedure in

Table 7, Column (2). The PSM procedure involves a logistic regression with the same

specification as the first-stage regression in the Heckman procedure. Using the predicted

propensity score from this logistic regression, we match without replacement a firm-year

observations with SUST_DJSI equal to 1, a treatment observation, against another firm-year

observation with SUST_DJSI equal to 0, a control observation. We pool the treatment and

control observations for our foreign institutional ownership and sustainability. Table 7,

Column (3) reports the results. The estimates on SUST_DJSI from the PSM procedure is

significant and positive (coefficient = 0.012, p value < 0.10). This suggests that our baseline

results hold for our matched sample.

23

5.5. Fama-Macbeth estimation and country fixed effect analysis

We also estimate our baseline regressions in Table 5 using the Fama-MacBeth (1973)

method to address for serial correlation. The Fama-MacBeth regression results presented in

Table 9 (Column 1 and Column 3) are consistent with our baseline estimations. Moreover, we

apply country fixed effect analysis to address for unobserved heterogeneity. The country

fixed effect regression results reported in Table 9 (Column 2 and Column 4) are consistent

with our baseline estimations.

< Table 9 >

5. 6. Alternative measures of sustainability

We use three alternative measures of sustainability for consistency of our results: (1)

an equal weighted score of environmental, social and governance performance (ESGSCORE)

following Cheng et al. (2013), (2) sustainability measured with only environmental and social

performance (ESSCORE) following Dhaliwal et al. (2014), and (3) a dummy variable

(CSR_DISC), following Dhaliwal et al. (2012), where sustainability takes the value of one if

a firm discloses sustainability information and zero otherwise.

As there is a strong body of literature suggesting a positive relation between

governance and financial performance, we include a measure that covers only non-financial

performance to address the potential confounding effect of governance on financial

performance. We include an equal weighted score of environmental, social and governance

performance following Cheng et al. (2013). Likewise Cheng et al. (2013), our source of

sustainability data is also ASSET4. Thus it may enhance comparability of our results. To

further address the confounding effect of governance with environmental and social

performance, we also include an equal weighted score of environmental and social

performance following Dhaliwal et al. (2014). Our sustainability disclosure measure is based

on the idea put forwarded by Dhaliwal et al. (2012) that firms with more sustainable

24

performance are more likely to include separate non-financial disclosure. This is documented

by Plumlee et al. (2015) that higher level of voluntary environmental disclosure is associated

with a higher firm value in the US. Hence, the separate sustainability disclosure may reflect

on the financial and non-financial performance of firms. Table 10 reports the results of these

additional sustainability proxies with foreign institutional ownership. Alternative proxies

provide corroborative results to our primary measure, SUST.

< Table 10 >

5.7. Country sensitivity tests

Following Cahan et al. (2015), we repeat our analyses after excluding each of the

following groups one at a time: (1) US firms, (2) Japanese firms, (3) UK firms, (4) Nordic

countries of Finland, Sweden, Norway, and Denmark, and (5) countries with less than 20

observations. We find that the results of each of these analyses (not tabulated) are consistent

with our main results.

5. 8. Firm value analysis

Sustainable firms attract more foreign institutional investors as discussed in previous

sections. Foreign institutional ownership reduces agency problems through their monitoring

as large foreign institutional holding can reduce the free rider problem arising from the

division of ownership among many shareholders. Less agency problem is associated to higher

firm value and so we expect a positive relationship between sustainability and firm value.

To test whether sustainable firms are associated with higher firm values we run the

following equation following Ferreira and Matos (2008):

25

TOBINQ = β0 + β1*SUST+ β2*IO_TOT + β3*FSIZE + β4*IOP + β5*LEV + β6*CASH

+ β7*ADR + β8*GLOBALQ + β9*DISC + β10*DIST + β11*LEGAL

+ β12* LNGDP + β13*CMCAP + β14*ENGLISH + Year Dummies

+ Industry Dummies + ε (2)

The dependent variable is the firm value measured by TOBINQ and independent

variable is sustainability (SUST). Firm characteristics include foreign institutional ownership

(FIO), firm size (FSIZE), investment opportunities (IOP), leverage (LEV), cash holding

(CASH), US cross-listing (ADR), and global industry Tobin’s Q (GLOBALQ). Country

indicators cover disclosure quality (DISC), bilateral distance (DIST), legal quality (LEGAL),

gross domestic product per capita (LNGDP), stock market capitalization (CMCAP), and

English language (ENGLISH).

As reported in Table 11, SUST is positive and significant (coefficient = 0.547, p value

< 0.01). The results suggest that corporate sustainability is positively related to firm value.

The firm value is a market based measure and so the findings imply that more sustainable

firms receive positive reactions from the investors.

< Table 11 >

5. 9. The role of sustainability in reducing information asymmetry

Whilst we show the relation of sustainability on foreign institutional ownership and

firm value, the role that sustainability plays is not clearly known. As sustainable firms attracts

more foreign investors and generates more value for the investors, it is an important corporate

disclosure. Corporate disclosure is critical for the functioning of an efficient capital market as

it reduces the information asymmetry between management and investors (Healy and Palepu,

2001). Sustainability, however, is a complex measure and may not be directly observable by

all investors. Hence, we examine the relationship between sustainable performance and

observable external information to better understand the informational role of sustainability.

26

As shown is Table 9, more sustainable firms have (1) a better sustainability report quality, (2)

a higher probability of wining corporate citizenship award, and (3) a higher likelihood of

implementing sustainability audit. We measure sustainability report quality (SUST_QUAL),

following Cohen and Simnett (2015), as an indicator variable with 1 if a company

implements the global reporting initiative (GRI) guidelines for sustainability reporting and 0

otherwise.11 These results suggest that more sustainable firms provide more information to

investors including institutional investors.

< Table 12 >

6. Conclusions

This study examines the determinants of foreign institutional ownership from the

perspective of corporate sustainability in 39 countries around the world for the period 2003 to

2011. We find that corporate sustainability is positively related to foreign institutional

ownership suggesting that corporate sustainability is an important determinant for foreign

institutional ownership. One plausible reason for such preference might be the better value

that these firms offer. We provide support for this by showing that corporate sustainability is

positively related to firm value implying that sustainable firms add more value for their

shareholders as well. To further explain the mechanism through which sustainability is

positively perceived by investors, we document the informational role of sustainability.

Corporate sustainability is found to be positively related to (1) sustainability report quality,

(2) corporate citizenship award, and (3) sustainability audit. These results suggest a possible

information channel through which institutional owners obtain information about sustainable

firms.

Our study contributes to both the corporate governance and sustainability literature. It

contributes to the governance literature by showing that foreign institutional investors are

11 Whilst Cohen and Simnett (2015) is not an empirical study, they suggest this measure to be used for CSR quality.

27

attracted to firms with sustainable performance. This adds to Ferreira and Matos (2008) by

documenting that sustainability is an important determinant of foreign institutional

ownership. We contribute to the sustainability literature by documenting the relationship of

sustainability with firm value, sustainability report quality, corporate citizenship award, and

sustainability audit. It adds to Deng et al. (2013) by offering an international evidence. Whilst

Deng et al. (2013) find the positive relationship between CSR and stakeholder value in the

US context, we provide an international evidence. Our sustainability measure is also different

as it integrates the economic, environmental, social and governance performance. Moreover,

we provide some empirical support to Cohen and Simnett (2015) by showing a positive

relationship between sustainable performance and sustainability report quality.

28

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Table 1: Sample selection

Panel A: Sample Selection

Total number of firm-year observations reported in ASSET4 over 2002-2010 20,287

Less: Observations not available at Compustat Global and North America (1,734)

Less: Observations with missing control variables (4,164)

Final Sample for sustainability and foreign institutional ownership model 14,389

Panel B: Country Distribution of Sample Firms

Country Number of Firms % of Sample

1 Australia 544 3.78 2 Austria 93 0.65 3 Belgium 119 0.83 4 Brazil 77 0.54 5 Canada 305 2.12 6 Chile 28 0.19 7 Colombia 4 0.03 8 Denmark 114 0.79 9 Egypt 3 0.02 10 Finland 171 1.19 11 France 507 3.52 12 Germany 327 2.27 13 Greece 68 0.47 14 Hong Kong 283 1.97 15 India 75 0.52 16 Indonesia 28 0.19 17 Ireland 143 0.99 18 Israel 26 0.18 19 Italy 223 1.55 20 Japan 2,180 15.15 21 Malaysia 38 0.26 22 Mexico 22 0.15 23 Netherland 180 1.25 24 New Zealand 39 0.27 25 Norway 122 0.85 26 Peru 3 0.02 27 Philippine 11 0.08 28 Portugal 61 0.42 29 Singapore 153 1.06 30 South Africa 65 0.45 31 South Korea 91 0.63 32 Spain 244 1.70 33 Sweden 298 2.07 34 Switzerland 422 2.93 35 Taiwan 85 0.59 36 Thailand 20 0.14 37 Turkey 28 0.19 38 United Kingdom 1,611 11.20 39 United States 5,578 38.77

Total 14,389 100.00

33

Table 1 (Continued)

Panel B: Industry Membership of Sample Firms

Industries Number of Firms % of Sample

1 Mining/Construction 805 5.59 2 Food 619 4.30 3 Textiles/Print/Publish 685 4.76 4 Chemicals 723 5.02 5 Pharmaceuticals 540 3.75 6 Extractive 754 5.24 7 Manufacturing: Rubber/glass/etc. 373 2.59 8 Manufacturing: Metal 529 3.68 9 Manufacturing: Machinery 616 4.28 10 Manufacturing: Electrical Equipment 398 2.77 11 Manufacturing: Transport Equipment 601 4.18 12 Manufacturing: Instruments 476 3.31 13 Manufacturing: Miscellaneous 105 0.73 14 Computers 1,329 9.24 15 Transportation 1,287 8.94 16 Utilities 841 5.84 17 Retail: Wholesale 358 2.49 18 Retail: Miscellaneous 891 6.19 19 Retail: Restaurant 153 1.06 20 Financial 879 6.11 21 Insurance/Real Estate 268 1.86 22 Services 922 6.41 23 Others 237 1.65

Total 14,389 100

Panel C: Year Distribution of Sample Firms

2002 734 5.10 2003 750 5.21 2004 1,321 9.18 2005 1,624 11.29 2006 1,601 11.13 2007 1,658 11.52 2008 1,991 13.84 2009 2,293 15.94 2010 2,417 16.80

Total 14,389 100.00

34

Table 2 Summary statistics of firm level variables. Variable definitions are presented in Appendix B.

TOTAL SUST NON_SUST

N Mean SD Median N Mean Median N Mean Median t-test z-test

PANEL A: Variables included in the baseline model

FIO 14389 0.148 0.149 0.099 8067 0.155 0.107 6322 0.139 0.088 6.594*** 10.686***

SUST 14389 0.531 0.298 0.530 8067 0.696 0.768 6322 0.320 0.270 96.236*** 74.413***

FSIZE 14389 8.747 1.442 8.632 8067 9.131 9.058 6322 8.257 8.183 37.816*** 36.597***

MB 14389 2.912 3.003 2.101 8067 2.856 2.106 6322 2.983 2.092 -2.526** 0.688

IOP 14389 0.107 0.228 0.077 8067 0.098 0.077 6322 0.119 0.076 -5.477*** -1.028

RET 14389 0.175 0.517 0.126 8067 0.166 0.130 6322 0.187 0.120 -2.420** 0.339

TURN 14389 1.861 1.636 1.384 8067 1.750 1.338 6322 2.003 1.467 -9.249*** -5.814***

DY 14389 0.021 0.025 0.015 8067 0.023 0.017 6322 0.020 0.012 7.251*** 12.077***

ROE 14389 0.122 0.336 0.123 8067 0.138 0.131 6322 0.101 0.111 6.598*** 10.737***

IRISK 14389 0.001 0.005 0.000 8067 0.001 0.000 6322 0.001 0.000 -2.227** -14.115***

LEV 14389 0.243 0.172 0.228 8067 0.243 0.229 6322 0.242 0.224 0.050 2.893***

CASH 14389 0.129 0.128 0.087 8067 0.121 0.085 6322 0.139 0.091 -8.081*** -3.314***

CLOSE 14389 0.239 0.221 0.180 8067 0.223 0.161 6322 0.258 0.206 -9.553*** -12.176***

DOM 14389 0.296 0.303 0.138 8067 0.280 0.123 6322 0.317 0.167 -7.263*** -4.726***

ADR 14389 0.102 0.302 0.000 8067 0.147 0.000 6322 0.043 0.000 20.840*** 20.533***

PANEL B: Additional variables introduced for Heckman (1979) first stage model

FIN 14388 0.014 0.130 -0.002 8067 0.008 -0.002 6321 0.022 -0.001 -6.434*** -2.533**

ROA 14388 0.060 0.086 0.050 8067 0.063 0.052 6321 0.057 0.048 3.801*** 4.891***

COMPET 14389 -0.079 0.072 -0.052 8067 -0.079 -0.051 6322 -0.079 -0.052 0.281 -0.171

FOREIGN 14389 0.842 0.365 1.000 8067 0.881 1.000 6322 0.793 1.000 14.441*** 14.338***

LITG 14389 0.190 0.392 0.000 8067 0.193 0.000 6322 0.186 0.000 1.104 1.104

FAGE 14351 2.805 0.717 2.833 8054 2.865 2.890 6297 2.727 2.773 11.468*** 11.039***

CAPIN 14260 0.050 0.049 0.038 7984 0.050 0.040 6276 0.051 0.035 -0.990 7.415***

NEW 13576 0.515 0.159 0.497 7634 0.507 0.489 5942 0.525 0.508 -6.389*** -5.563***

35

Table 2 (Continued)

TOTAL SUST NON_SUST

N Mean SD Median N Mean Median N Mean Median t-test z-test

PIDEC 13146 0.223 0.416 0.000 7338 0.233 0.000 5808 0.209 0.000 3.349*** 3.348***

SUSTCOMM 14389 0.323 0.468 0.000 8067 0.438 0.000 6322 0.177 0.000 34.515*** 33.170***

PANEL C: Additional variables introduced for firm value models

TOBINQ 14389 1.626 1.150 1.296 8067 1.564 1.275 6322 1.705 1.325 -7.326*** -4.569***

IO_TOT 14389 0.442 0.320 0.404 8067 0.434 0.391 6322 0.453 0.432 -3.629*** -2.824***

GLOBALQ 14389 1.341 0.430 1.340 8067 1.335 1.339 6322 1.348 1.346 -1.870* -2.548**

PANEL D: Additional variables introduced for asymmetric information models

SUST_QUAL 14389 0.193 0.394 0.000 8067 0.294 0.000 6322 0.064 0.000 36.257*** 34.707***

CRA 14389 0.413 0.492 0.000 8067 0.549 1.000 6322 0.239 0.000 39.429*** 37.459***

SUSAUDIT 14389 0.149 0.356 0.000 8067 0.223 0.000 6322 0.054 0.000 29.124*** 28.302***

PANEL E: Alternative measures of sustainability

SUST_DJSI 14389 0.152 0.359 0.000 8067 0.238 0.000 6322 0.043 0.000 33.661*** 32.410***

ESGSCORE 14389 0.527 0.234 0.516 8067 0.646 0.669 6322 0.376 0.362 83.876*** 69.424***

ESSCORE 14389 0.520 0.292 0.507 8067 0.670 0.751 6322 0.329 0.247 85.258*** 69.657***

DISC_CSR 14389 0.323 0.468 0.000 8067 0.448 0.000 6322 0.164 0.000 38.020*** 36.244***

*** Denotes significance at 1%. ** Denotes significance at 5%. *Denotes significance at 10%.

36

Table 3 Summary statistics of country level variables. Variable definitions are presented in Appendix B.

Sl. Country STAKE LEGAL DISC DIST ENGLISH GDP CMCAP PIDEC

1 Australia 1.580 40.000 5.169 13009.220 1 43406.870 126.159 0.333 2 Austria 1.250 20.000 5.145 4832.903 0 41308.120 32.045 0.444 3 Belgium 1.290 0.000 5.011 5047.939 0 39055.540 64.732 0 4 Brazil -1.920 18.960 4.198 10696.410 0 9123.966 66.866 1 5 Canada 0.560 50.000 5.296 8401.225 1 39875.560 120.809 0.556 6 Chile -0.880 35.100 4.705 12559.250 0 11253.000 127.347 1 7 Columbia - 6.240 4.095 10863.370 0 5732.177 59.537 0 8 Denmark 2.950 20.000 5.531 4943.901 0 51913.460 65.321 0 9 Egypt - 8.340 4.007 5234.917 0 2382.624 46.011 - 10 Finland 1.890 30.000 5.646 5028.041 0 41166.880 90.123 0.111 11 France 1.120 26.940 5.056 5127.709 0 36624.070 80.356 0.111 12 Germany 0.810 9.230 5.360 4877.365 0 37207.280 44.270 0.444 13 Greece -0.330 12.360 4.223 4983.761 0 24039.010 44.996 0.444 14 Hong Kong -1.110 41.100 5.246 8129.586 1 29984.170 476.672 0 15 India -2.730 20.850 4.320 6367.429 1 1209.671 88.291 1 16 Indonesia - 7.960 4.350 9354.357 0 2622.033 40.648 0 17 Ireland - 31.200 4.923 5412.817 1 50329.160 41.161 0 18 Israel - 14.460 4.919 5146.875 0 25592.980 92.823 0 19 Italy -0.090 8.330 4.336 5018.260 0 32302.330 34.902 0.222 20 Japan -0.950 35.920 5.392 8638.519 0 37277.400 85.599 0 21 Malaysia -1.760 27.120 4.907 8560.420 0 8215.891 139.093 0 22 Mexico -1.470 5.350 4.203 10816.600 0 8791.507 34.333 0 23 Netherland 1.520 20.000 5.330 5039.824 0 42927.900 88.095 0.111 24 New Zealand 0.640 40.000 5.022 14527.460 1 28883.880 36.582 0.714 25 Norway 2.620 40.000 5.304 5105.399 0 72662.630 60.108 0.556 26 Peru - 7.500 4.023 11897.450 0 4717.846 54.594 1 27 Philippine -1.930 8.190 3.956 8841.277 1 2037.543 65.871 0 28 Portugal -0.290 26.040 4.583 5840.847 0 20288.590 40.790 0.667 29 Singapore -0.590 34.280 5.524 8759.136 1 34289.690 191.988 0 30 South Africa -1.420 22.100 4.350 8828.799 1 6426.858 253.675 1 31 South Korea -1.570 10.700 5.010 8019.411 0 18955.700 100.106 0 32 Spain -0.420 31.200 4.744 5559.696 0 28091.440 89.075 0.667 33 Sweden 2.900 30.000 5.606 5009.456 0 43571.850 105.535 0.556 34 Switzerland 1.340 20.000 5.577 5006.144 0 57756.030 228.425 1 35 Taiwan - 25.560 5.229 8332.762 0 33089.410 155.672 0 36 Thailand -1.960 12.500 4.550 7951.106 0 4247.101 68.141 0 37 Turkey - 10.360 4.193 4935.185 0 9577.409 33.633 0 38 U.K. 0.470 42.850 5.290 5194.096 1 38545.710 127.020 1 39 U.S.A. -1.550 50.000 5.683 8812.879 1 43828.740 120.760 0.222

Mean 0.000 23.100 4.872 7454.149 0.280 27418.257 98.004 0.346 Median -0.290 20.850 5.010 6367.429 0 29984.170 80.356 0.167

37

Table 4 Correlation matrix of the baseline model variables. Variable definitions are presented in Appendix B.

FIO TOBINQ SUST FSIZE MB IOP RET TURN DY ROE IRISK LEV CASH CLOSE GLOBALQ DOM DISC DIST STAKE LEGAL LNGDP CMCAP ENGLISH

FIO 1.000

TOBINQ 0.038 1.000

SUST 0.133 -0.06 1.000

FSIZE -0.029 -0.42 0.406 1.000

BM 0.008 0.659 0.000 -0.221 1.000

IOP -0.078 0.204 -0.109 -0.099 0.123 1.000

RET 0.048 0.237 -0.014 -0.102 0.183 0.052 1.000

TURN 0.061 0.038 -0.035 -0.024 0.007 -0.007 -0.021 1.000

DY 0.03 -0.12 0.126 0.056 -0.054 -0.036 0.129 -0.163 1.000

ROE 0.012 0.203 0.094 -0.014 0.42 0.061 0.077 -0.108 0.095 1.000

IRISK 0.034 -0.048 0.032 -0.097 -0.044 -0.009 -0.143 0.016 -0.010 -0.044 1.000

LEV -0.056 -0.193 0.003 0.19 -0.011 -0.043 -0.056 0.021 0.12 -0.055 0.027 1.000

CASH 0.051 0.412 -0.125 -0.253 0.195 0.068 0.089 0.19 -0.177 -0.013 -0.017 -0.366 1.000

CLOSE -0.125 0.069 -0.192 -0.14 0.021 0.084 0.049 -0.275 -0.036 0.011 -0.022 -0.009 0.073 1.000

GLOBALQ 0.072 0.454 -0.027 -0.382 0.279 0.117 0.154 -0.027 -0.13 0.089 -0.065 -0.148 0.219 0.062 1.000

DOM -0.1 0.032 0.042 -0.007 0.055 -0.064 -0.033 0.412 -0.026 0.013 0.095 0.013 -0.019 -0.369 -0.078 1.000

DISC 0.008 0.006 -0.067 0.065 0.010 -0.041 -0.088 0.302 -0.04 -0.018 -0.063 -0.052 0.033 -0.382 -0.022 0.385 1.000

DIST -0.129 0.003 -0.207 0.059 -0.031 0.011 -0.029 0.182 -0.051 -0.036 -0.155 -0.03 0.061 -0.069 -0.078 0.179 0.294 1.000

STAKE 0.178 0.016 0.155 -0.206 -0.003 0.09 0.067 -0.295 0.148 0.025 0.093 -0.02 -0.067 0.139 0.128 -0.36 -0.267 -0.612 1.000

LEGAL -0.019 0.016 -0.044 0.027 0.037 -0.048 -0.061 0.348 -0.007 -0.015 0.033 0.003 0.003 -0.399 -0.077 0.565 0.625 0.551 -0.531 1.000

LNGDP 0.106 -0.058 0.014 -0.009 -0.034 -0.044 -0.105 0.235 -0.006 -0.044 0.002 -0.005 -0.004 -0.29 -0.006 0.231 0.58 -0.005 0.18 0.357 1.000

CMCAP 0.04 0.126 -0.069 -0.063 0.088 0.072 0.118 -0.057 0.062 0.061 -0.06 -0.074 0.074 0.043 0.076 0.051 0.178 0.113 -0.09 0.21 0.023 1.000

ENGLISH 0.02 0.09 0.018 -0.06 0.109 0.011 -0.001 0.278 0.068 0.035 0.117 0.012 -0.009 -0.314 -0.066 0.601 0.374 0.381 -0.405 0.776 0.14 0.317 1.000 *** Denotes significance at 1%. ** Denotes significance at 5%. *Denotes significance at 10%.

38

Table 5 Sustainability and foreign institutional ownership This table contains regression results of sustainability, firm characteristics, and country level factors on foreign institutional ownership. Column (1) reports our baseline estimation using ordinary least square regression with standard errors clustered at the firm level. Column (2) presents results of the moderating effect of stakeholder orientation on our baseline model. All variables are defined in Appendix B. (1) (2) FIO FIO

SUST 0.037*** 0.037*** (4.713) (4.356) SUST * STAKE 0.028*** (5.303) STAKE 0.003 (0.758) FSIZE -0.000 0.004* (-0.107) (1.915) MB -0.000 0.000 (-0.027) (0.446) IOP -0.015** -0.019*** (-2.086) (-2.718) RET 0.003 0.001 (0.901) (0.427) TURN 0.007*** 0.008*** (3.514) (3.983) DY 0.006 -0.101 (0.073) (-1.263) ROE 0.005 0.007 (1.100) (1.334) IRISK 0.620*** 0.599*** (2.775) (2.749) LEV -0.035** -0.031** (-2.368) (-2.109) CASH 0.029 0.036* (1.373) (1.706) CLOSE -0.103*** -0.105*** (-9.041) (-9.195) DOM -0.152*** -0.136*** (-9.976) (-8.605) ADR 0.002 -0.010 (0.247) (-1.311) DISC 0.040*** 0.046*** (4.202) (5.399) DIST -0.095*** -0.062*** (-8.828) (-5.264) LEGAL -0.000 0.000 (-1.248) (0.172) LNGDP 0.015*** -0.008 (2.987) (-1.463) CMCAP 0.000 0.000 (0.562) (0.961) ENGLISH 0.062*** 0.059*** (6.109) (5.888) Constant 0.610*** 0.454*** (5.466) (4.061) Year Fixed Effects YES YES Industry Fixed Effect YES YES

N 14389 14069 Adj. R2 0.182 0.197

*** Denotes significance at 1%. ** Denotes significance at 5%. *Denotes significance at 10%.

39

Table 6 Results for baseline estimation and moderating effect – using change regression specification

(1) (2) ∆FIO ∆FIO

∆SUST 0.009** 0.011** (1.974) (2.363) ∆SUST*STAKE 0.006* (1.919) STAKE -0.000 (-0.057) ∆FSIZE 0.002 0.002 (0.458) (0.358) ∆MB -0.000 -0.000 (-1.408) (-1.466) ∆IOP -0.004 -0.004 (-0.905) (-0.848) ∆RET 0.004*** 0.005*** (2.907) (3.078) ∆TURN 0.005*** 0.005*** (4.525) (4.534) ∆DY -0.015 -0.026 (-0.268) (-0.475) ∆ROE 0.003 0.004 (0.942) (1.034) ∆IRISK 0.136 0.134 (0.994) (0.977) ∆LEV 0.016 0.016 (0.878) (0.904) ∆CASH -0.007 -0.007 (-0.659) (-0.601) ∆CLOSE -0.017** -0.017** (-2.092) (-2.003) ∆DOM -0.731*** -0.727*** (-46.349) (-45.495) ∆ADR 0.013 0.014 (0.846) (0.871) ∆DISC 0.002 0.003 (0.582) (0.679) DIST -0.024*** -0.025*** (-7.455) (-5.796) LEGAL 0.000*** 0.000*** (3.913) (3.852) ∆LNGDP 0.041*** 0.041*** (3.585) (3.370) ∆CMCAP 0.000 0.000* (1.629) (1.703) ENGLISH 0.010*** 0.011*** (6.054) (6.382) Constant 0.231*** 0.234*** (8.619) (6.624) Year Fixed Effects YES YES Industry Fixed Effects YES YES

N 11499 11281 Adj. R2 0.656 0.652

40

Table 7 Sustainability and foreign institutional ownership: Additional analyses All variables are defined in Appendix B.

(1) (2) (3) (4) (5) (6) FIO FIO FIO FIO FIO FIO Unexpected

SUST Heckman PSM Unexpected

SUST Heckman PSM

SUST 0.035*** 0.025*** 0.012* 0.024*** 0.024** 0.011*

(4.053) (2.764) (1.845) (2.655) (2.547) (1.670)

SUST * STAKE 0.017*** 0.025*** 0.002

(2.634) (4.530) (0.345)

STAKE 0.017*** 0.003 0.016***

(5.512) (0.563) (3.096)

FSIZE 0.004** -0.005 -0.004 0.008*** 0.001 -0.001

(2.331) (-1.334) (-1.279) (3.942) (0.173) (-0.388)

MB 0.000 -0.000 -0.001 0.001 0.000 -0.000

(0.482) (-0.540) (-0.396) (0.709) (0.101) (-0.192)

IOP -0.016** -0.005 0.021 -0.023*** -0.010 0.018

(-2.133) (-0.693) (1.298) (-3.109) (-1.292) (1.099)

RET 0.001 0.001 -0.002 0.000 0.001 -0.004

(0.402) (0.456) (-0.285) (0.147) (0.280) (-0.589)

TURN 0.007*** 0.006*** 0.006* 0.008*** 0.007*** 0.007**

(3.285) (2.955) (1.746) (4.107) (3.428) (2.120)

DY 0.051 0.018 0.186 -0.061 -0.094 0.018

(0.585) (0.200) (1.139) (-0.696) (-1.038) (0.110)

ROE 0.007 0.006 0.013 0.007 0.007 0.012

(1.344) (1.245) (1.462) (1.437) (1.408) (1.350)

IRISK 0.666*** 0.923*** 1.281*** 0.634*** 0.909*** 1.220***

(2.957) (4.101) (3.088) (2.850) (4.102) (2.923)

LEV -0.045*** -0.022 -0.044 -0.042*** -0.022 -0.038

(-2.961) (-1.338) (-1.587) (-2.757) (-1.387) (-1.376)

CASH 0.020 0.019 0.030 0.025 0.024 0.032

(0.915) (0.861) (0.792) (1.149) (1.050) (0.828)

CLOSE -0.107*** -0.107*** -0.161*** -0.108*** -0.113*** -0.167***

(-9.233) (-9.042) (-8.517) (-9.174) (-9.563) (-8.927)

DOM -0.152*** -0.154*** -0.219*** -0.138*** -0.141*** -0.204***

(-9.524) (-9.230) (-7.249) (-8.194) (-7.833) (-6.145)

ADR 0.002 0.003 0.014 -0.005 -0.006 0.010

(0.283) (0.382) (1.533) (-0.610) (-0.771) (1.057)

DISC 0.041*** 0.052*** 0.000 0.046*** 0.055*** 0.000

(4.539) (5.775) (0.592) (5.321) (6.388) (0.952)

DIST -0.105*** -0.086*** 0.056*** -0.077*** -0.059*** 0.060***

(-9.848) (-7.296) (4.381) (-6.403) (-4.610) (4.779)

LEGAL -0.000 0.000 -0.136*** 0.000 0.000 -0.097***

(-1.197) (0.144) (-8.355) (0.326) (1.201) (-4.323)

LNGDP 0.013*** 0.013*** 0.055*** -0.008 -0.008 0.058***

(2.845) (2.792) (3.471) (-1.325) (-1.335) (3.452)

CMCAP 0.000 -0.000 0.014 0.000 -0.000 -0.010

(0.441) (-1.010) (1.251) (0.891) (-1.481) (-0.838)

ENGLISH 0.065*** 0.044*** 0.000 0.060*** 0.045*** 0.000

(6.733) (4.338) (0.729) (5.878) (4.305) (0.144)

IMR -0.017** -0.013 0.755***

(-2.100) (-1.601) (3.440)

Constant 0.688*** 0.557*** 0.903*** 0.569*** 0.449*** (6.154) (4.909) (4.644) (5.089) (3.986) Year Fixed Effects YES YES YES YES YES YES Industry Fixed Effect YES YES YES YES YES YES

N 13479 12236 3374 13172 11991 3321

Adj. R2 0.178 0.200 0.273 0.190 0.213 0.284 *** Denotes significance at 1%. ** Denotes significance at 5%. *Denotes significance at 10%.

41

Table 8 Heckman first stage results This table presents the Heckman (1979) first stage regression results of firm and country characteristics on sustainability. All variables are defined in Appendix B.

Dependent variable DJSI

Coefficient Z P>z

FIN 0.059 0.409 0.682 TOBINQ 0.196 6.627 0.000*** FSIZE 0.557 16.585 0.000*** LEV -0.581 -2.591 0.010*** TURN 0.019 0.854 0.393 ROA -0.516 -1.615 0.106 COMPET -0.722 -1.384 0.166 FOREIGN 0.014 0.130 0.897 LITG -0.180 -0.955 0.340 FAGE 0.158 2.742 0.006*** CAPIN 1.905 2.659 0.008*** NEW -0.926 -3.849 0.000*** SUSTCOMM 0.448 7.785 0.000*** ADR -0.019 -2.796 0.005*** DISC 0.008 0.056 0.955 DIST 0.436 4.402 0.000*** LEGAL -0.173 -0.734 0.463 LNGDP 0.253 1.938 0.053* CMCAP 0.479 3.638 0.000*** ENGLISH 0.001 0.826 0.409 PIDEC 0.596 4.768 0.000*** Constant -9.686 -3.268 0.001*** Year Fixed Effects YES Industry Fixed Effects YES

Observations 12236 Pseudo R2 0.2709 Log pseudo likelihood -3928.70 Partial R2 (PIDEC) 0.0082***

42

Table 9 Sustainability and foreign institutional ownership: Additional analyses All variables are defined in Appendix B.

(1) (2) (3) (4) Fama-MacBeth

Analysis Country Fixed

Effects Fama-MacBeth

Analysis Country Fixed

Effects FIO FIO FIO FIO

SUST 0.038*** 0.021*** 0.035*** 0.031*** (7.012) (2.643) (3.410) (3.717) SUST * STAKE 0.022** 0.024*** (2.619) (4.645) STAKE 0.008 -0.004 (1.020) (-0.511) FSIZE -0.001 0.003 0.003 0.003 (-0.502) (1.577) (1.767) (1.387) MB 0.000 0.000 0.000 0.000 (0.315) (0.199) (0.998) (0.294) IOP -0.002 -0.023*** -0.010 -0.021*** (-0.288) (-3.237) (-1.417) (-2.940) RET 0.002 -0.002 -0.001 -0.001 (0.384) (-0.602) (-0.195) (-0.404) TURN 0.009*** 0.008*** 0.011*** 0.006*** (3.609) (3.804) (5.533) (3.252) DY 0.019 -0.095 -0.131** -0.121 (0.286) (-1.168) (-2.711) (-1.469) ROE -0.002 0.006 -0.001 0.006 (-0.264) (1.185) (-0.173) (1.167) IRISK -12.976** 1.009*** -16.847** 1.066*** (-2.817) (4.770) (-3.247) (5.035) LEV -0.029*** -0.038*** -0.029*** -0.031** (-8.722) (-2.586) (-9.652) (-2.164) CASH 0.030*** 0.035 0.040*** 0.037* (4.173) (1.631) (4.593) (1.734) CLOSE -0.090*** -0.106*** -0.092*** -0.109*** (-6.595) (-9.518) (-6.302) (-9.694) DOM -0.150*** -0.143*** -0.135*** -0.142*** (-4.405) (-8.362) (-3.422) (-8.237) ADR 0.003 -0.006 -0.006 -0.008 (0.462) (-0.756) (-1.308) (-1.098) DISC 0.057** 0.068** (2.995) (3.191) DIST -0.080*** -0.045*

(-4.256) (-2.256)

LEGAL -0.001** -0.000

(-3.013) (-0.806)

LNGDP 0.019 -0.027

(1.524) (-1.599)

CMCAP -0.000 0.000

(-0.619) (0.007)

ENGLISH 0.051** 0.044*

(2.913) (1.962)

Constant 0.445 0.108*** 0.489 0.094*** (1.380) (5.161) (1.687) (4.230) Year Fixed Effects NO YES NO YES Industry Fixed Effect YES YES YES YES Country Fixed Effect NO YES NO YES

N 14389 14389 14069 14069 R2/Adj.R2 0.193 0.209 0.227 0.213 *** Denotes significance at 1%. ** Denotes significance at 5%. *Denotes significance at 10%.

43

Table 10 Sustainability and foreign institutional ownership: Alternative proxies This table contains regression results of sustainability, firm characteristics, and country level factors on foreign institutional ownership and firm value with alternative measures of sustainability. All variables are defined in Appendix B. (1) (2) (3) (4) (5) (4)

FIO FIO FIO FIO FIO FIO

ESGSCORE ESSCORE CSR_DISC ESGSCORE ESSCORE CSR_DISC

SUST 0.043*** 0.017* 0.014*** 0.041*** 0.022** 0.013***

(3.970) (1.893) (3.376) (3.593) (2.237) (3.002)

SUST * STAKE 0.038*** 0.034*** 0.011***

(5.619) (5.677) (4.010)

STAKE -0.002 0.002 0.017***

(-0.368) (0.414) (5.308)

FSIZE 0.000 0.002 0.003 0.005** 0.006*** 0.006***

(0.111) (0.971) (1.368) (2.154) (2.828) (3.193)

MB 0.000 0.000 0.000 0.000 0.000 0.000

(0.021) (0.241) (0.282) (0.572) (0.694) (0.580)

IOP -0.014** -0.016** -0.016** -0.019*** -0.021*** -0.022***

(-1.992) (-2.171) (-2.207) (-2.743) (-2.942) (-3.127)

RET 0.003 0.003 0.002 0.001 0.001 0.001

(0.979) (0.923) (0.876) (0.460) (0.403) (0.396)

TURN 0.007*** 0.007*** 0.007*** 0.008*** 0.008*** 0.009***

(3.436) (3.496) (3.517) (4.022) (3.898) (4.369)

DY 0.015 0.031 0.040 -0.086 -0.074 -0.069

(0.182) (0.387) (0.498) (-1.082) (-0.931) (-0.862)

ROE 0.007 0.007 0.007 0.007 0.007 0.007

(1.318) (1.317) (1.338) (1.467) (1.433) (1.420)

IRISK 0.604*** 0.590*** 0.557** 0.581*** 0.647*** 0.525**

(2.702) (2.640) (2.505) (2.667) (2.974) (2.414)

LEV -0.039*** -0.041*** -0.041*** -0.032** -0.033** -0.034**

(-2.593) (-2.726) (-2.773) (-2.206) (-2.285) (-2.352)

CASH 0.029 0.028 0.028 0.036* 0.036* 0.034

(1.369) (1.317) (1.312) (1.678) (1.700) (1.583)

CLOSE -0.103*** -0.108*** -0.108*** -0.105*** -0.110*** -0.106***

(-9.052) (-9.413) (-9.403) (-9.248) (-9.626) (-9.226)

DOM -0.152*** -0.151*** -0.151*** -0.136*** -0.137*** -0.134***

(-9.959) (-9.890) (-9.875) (-8.574) (-8.628) (-8.515)

ADR 0.002 0.004 0.004 -0.010 -0.009 -0.005

(0.311) (0.539) (0.551) (-1.405) (-1.269) (-0.616)

DISC 0.040*** 0.039*** 0.038*** 0.046*** 0.042*** 0.045***

(4.209) (4.080) (3.985) (5.468) (4.931) (5.244)

DIST -0.095*** -0.100*** -0.102*** -0.061*** -0.059*** -0.068***

(-8.674) (-9.202) (-9.510) (-5.147) (-4.957) (-5.859)

LEGAL -0.000 -0.001 -0.001 -0.000 0.000 0.000

(-1.345) (-1.378) (-1.349) (-0.028) (0.294) (0.739)

LNGDP 0.015*** 0.016*** 0.017*** -0.008 -0.010* -0.012**

(2.928) (3.138) (3.276) (-1.357) (-1.810) (-2.236)

CMCAP 0.000 0.000 0.000 0.000 0.000 0.000

(0.560) (0.390) (0.399) (0.935) (1.060) (1.172)

ENGLISH 0.062*** 0.068*** 0.068*** 0.060*** 0.061*** 0.057***

(6.032) (6.806) (6.842) (5.908) (6.070) (5.781)

Constant 0.602*** 0.643*** 0.657*** 0.432*** 0.458*** 0.549***

(5.362) (5.689) (5.885) (3.815) (4.036) (5.013)

Year Fixed Effects YES YES YES YES YES YES

Industry Fixed Effect YES YES YES YES YES YES

N 14389 14389 14389 14069 14069 14069

Adj. R2 0.181 0.179 0.180 0.198 0.197 0.194

*** Denotes significance at 1%. ** Denotes significance at 5%. *Denotes significance at 10%.

44

Table 11 Sustainability and firm value This table contains regression results of sustainability, firm characteristics, and country level factors on firm value. All variables are defined in Appendix B.

(1) TOBINQ

SUST 0.547***

(9.590)

IO_TOT 0.133**

(2.128)

FSIZE -0.258***

(-15.820)

IOP 0.650***

(9.137)

LEV 0.043

(0.346)

CASH 2.636***

(13.556)

ADR 0.038

(0.753)

GLOBALQ 0.811***

(11.471)

DISC 0.172**

(2.485)

DIST 0.129*

(1.738)

LEGAL -0.004

(-1.375)

LNGDP -0.251***

(-5.166)

CMCAP 0.000

(1.300)

ENGLISH 0.122**

(2.241)

Constant 2.416***

(2.762)

Year Fixed Effects YES Industry Fixed Effects YES

N 14389

Adj. R2 0.415

*** Denotes significance at 1%. ** Denotes significance at 5%. *Denotes significance at 10%.

45

Table 12 Sustainability and information asymmetry This table contains regression results of sustainability, firm characteristics, and country level factors on three measures of information asymmetry: sustainability report quality (SUST_QUAL), corporate citizenship award (CRA) and sustainability audit (SUSAUDIT). All variables are defined in Appendix B.

(1) (2) (3) SUST_QUAL CRA SUSAUDIT

SUST 6.782*** 3.429*** 4.464***

(20.905) (26.493) (15.546)

FSIZE 0.271*** 0.164*** 0.374***

(4.825) (5.302) (5.970)

ROA -2.225*** -0.981*** -1.912***

(-3.353) (-2.643) (-2.639)

MB -0.036* -0.010 -0.011

(-1.696) (-0.939) (-0.514)

LEV -0.269 0.141 0.003

(-0.730) (0.748) (0.007)

FIN -0.000* -0.000*** 0.000*

(-1.845) (-3.216) (1.869)

TOBINQ 0.202*** 0.009 0.071

(2.830) (0.238) (0.769)

TURN 0.045 -0.015 -0.043

(1.232) (-0.703) (-0.988)

COMPET -1.406 0.399 -1.291

(-1.222) (0.882) (-1.435)

FOREIGN 0.477*** 0.055 0.407*

(2.728) (0.612) (1.775)

LITG 0.914** 0.130 0.664

(2.321) (0.763) (1.482)

SRI 0.654** 0.495** 1.187***

(1.984) (2.387) (3.654)

SUSTCOMM 0.561*** 0.174*** 0.818***

(5.506) (2.587) (6.994)

ADR 0.090 -0.081 0.378**

(0.554) (-0.770) (2.320)

PIDEC 0.420** 0.366*** 0.462**

(2.160) (3.308) (2.191)

DISC -0.228 0.352*** -0.791***

(-0.925) (2.579) (-3.227)

DIST 1.567*** 0.340* -0.299

(4.738) (1.939) (-0.876)

LEGAL -0.027*** -0.003 0.002

(-2.706) (-0.585) (0.147)

LNGDP -0.097 -0.626*** -0.149

(-0.699) (-5.436) (-0.946)

CMCAP 0.003 -0.004*** 0.004**

(1.494) (-2.790) (2.429)

ENGLISH -1.438*** 0.115 -1.473***

(-7.093) (0.999) (-6.827)

Constant -21.646*** -1.789 -0.936

(-5.550) (-0.776) (-0.228)

Year Fixed Effects YES YES YES Industry Fixed Effects YES YES YES

N 13145 13145 13145

Wald Chi2 1458.950 1846.660 929.550 Log likelihood -3224.497 -6897.7695 -3201.019 Pseudo R2 0.4897 0.2231 0.4104

*** Denotes significance at 1%. ** Denotes significance at 5%. *Denotes significance at 10%.

46

Appendix A

Corporate Sustainability

Pillars Categories Sample data points

Economic Client loyalty Performance Shareholder loyalty

Market leadership Brand value Consumer clients Return on assets Net income growth Return on equity Return on invested capital Policy for maintaining loyal shareholder base Insider dealings controversies

Environmental Resource reduction Emission reduction Product innovation

Energy use total Electricity purchased Water withdrawal total Water recycled CO2 equivalents emissions total NOx emissions SOx emissions VOC emissions Waste total Waste recycled total Hazardous waste Environmental management system Spills and pollution controversies

Social Employment quality Health and safety Training and development Diversity Human rights Community Product responsibility

Employees leaving Turnover of employees Total injury rate Accidents total Lost time injury rate Lost working days Average training hours Training costs total Women employees Women managers Donations total Health and safety controversies

Governance Board structure Compensation policy Board functions Shareholder rights Vision and strategy

Audit committee independence Compensation committee independence Nomination committee independence Board meeting attendance average Board gender diversity Compensation policy/Sustainability compensation incentives Senior executive total compensation Board member total compensation Highest remuneration package Anti-takeover devices Non-executive board member total Compensation controversies

47

Appendix B

Variables Description

Variable Measure Description

FIRM LEVEL VARIABLES

FIO Foreign institutional investors

Institutional ownership by foreign institutions as a percentage of market capitalization

SUST Sustainable performance

An equal-weighted rating of economic, environmental, social and corporate governance performance

FSIZE Firm size Natural logarithm of the total assets in US dollars at the beginning of each year

MB Market-to-book The ratio of market value of equity and book value of equity at the end of the year

IOP Investment opportunities

Sales growth measured as the geometric average of two-year annual sales in US dollars

RET Annual stock return Annual stock return calculated as compounding of daily stock return

TURN Liquidity Ratio of number of shares traded to total shares outstanding at the end of year

DY Dividend yield Ratio of dividend available to common shares and the market value of equity at the beginning of the fiscal year

ROE Return on equity The ratio of income before extraordinary items to book value of equity

IRISK Idiosyncratic risk Natural logarithm of the standard deviation of the market-model residuals computed using the daily stock returns

LEV Leverage Ratio of total debt to total assets at the end of the year

CASH Cash Ratio of cash and short term investments to total assets

CLOSE Closely held shares Number of shares held by insiders as a proportion of the number of shares outstanding

DOM Domestic institutional investors

Institutional ownership by domestic institutions as a percentage of market capitalization

ADR US cross-listing Indicator variable that equals 1 if a firm is cross-listed on a US exchange, and 0 otherwise

ROA Return on assets Total return on assets measured as the ratio of income before extraordinary items and total assets at the beginning of the year

COMPET Competition The Herfindahl-Hirschman Index (HHI) multiplied by -1

FOREIGN Foreign sales An indicator variable 1 if a firm reports foreign sales, and 0 otherwise

LITG Litigation risk An indicator variable that equals 1 if the firm operates in a high-litigation industry (SIC codes of 2833–2836, 3570–3577, 3600–3674, 5200–5961, and 7370), and 0 otherwise

CAPIN Capital intensity The ratio of capital spending divided by total revenue.

NEW Asset Newness The ratio of net properties, plant and equipment divided by the gross properties, plant and equipment.

TOBINQ Firm value The ratio of market value of assets (measured as market value of equity plus book value of debt) and book value of assets

48

Appendix B (Continued)

Variable Measure Description

IO_TOT Total institutional ownership

Percentage of shares held by all institutional owners

GLOBALQ Global industry Tobin’s Q

Median Tobin’s Q of firms in each two-digit SIC global industry

SUST_QUAL Sustainability reporting quality

An indicator variable that equals 1 if the firm follows the sustainability reporting suggested by global reporting initiative (GRI) and 0 otherwise

CRA Corporate citizenship award

An indicator variable that equals 1 if the firm wins the corporate citizenship award and 0 otherwise

SUSAUDIT Sustainability audit An indicator variable that equals 1 if the firm implements sustainability audit and 0 otherwise

FIN New finance Ratio of new finance issue and total assets. New finance is measured as the issuance of common shares, preferred shares and long term debt minus the purchase of common shares, preferred shares and repayment of long term debt

SUST_DJSI Sustainable performance

An indicator variable of 1 if a firm is listed in Dow Jones Sustainability Index and 0 otherwise

ESGSCORE Sustainable performance

An equal-weighted rating of environmental, social and corporate governance performance

ESSCORE Sustainable performance

An equal-weighted rating of environmental and social performance

CSR_DISC Sustainable performance

A dummy variable that takes the value of 1 if a firm discloses sustainability information and 0 otherwise

COUNTRY LEVEL VARIABLES

DISC Disclosure quality The global competitiveness index developed by World Economic Forum

DIST Bilateral distance Natural logarithm of the average bilateral distance in kilometers between the capital city of a country and other capital cities

LEGAL Legal quality The multiplication of Anti-director rights by the rule of law index (La Porta et al., 1998)

LNGDP Gross domestic product per capita

Natural logarithm of annual gross domestic product per capita

CMCAP Stock market capitalization

The ratio of annual stock market capitalization to gross domestic product

ENGLISH English language An indicator variable that takes a value of 1 if a country's official language is English and 0 otherwise

STAKE Stakeholder Orientation

Stakeholder orientation of a company following Dhaliwal et al (2012)

PIDEC Political ideology of the government

An indicator variable that equals 1 if there is a left wing government in a country in a year, and 0 otherwise. Our measure of left and non-left follows Dutt and Mitra (2005)