# A study of the relationships among environmental performance, environmental disclosure, and financial performance

Lucy Wenxiang Lu (Department of Accounting, Foster College of Business, Bradley University, Peoria, Illinois, USA)
Martin Edward Taylor (Department of Accounting, College of Business Administration, University of Texas at Arlington, Arlington, Texas, USA)

ISSN: 1321-7348

Publication date: 5 February 2018

## Abstract

### Purpose

The purpose of this paper is to study the relationships among environmental performance (EP), environmental disclosure (ED), and financial performance (FP) (three corporate constructs) using data from Newsweek’s green rankings.

### Design/methodology/approach

Previous studies document mixed results about the relations among the three constructs. A firm’s overall management strategy may affect the three constructs simultaneously; therefore, the interrelationships among EP, ED, and FP were jointly examined. A simultaneous equations approach was used to test the hypothesis.

### Findings

The three-stage least square (3SLS) estimation results show a negative relationship between EP and FP and a positive relationship between EP and ED, suggesting that financially successful firms are less likely good environmental performers but green firms are more likely to disclose their EP.

### Research limitations/implications

Since the sample firms examined in this study are US large-size companies, the results found in this paper may not apply to small- and/or medium-size firms or to companies in other countries.

### Practical implications

Three corporate constructs are jointly correlated with each one. A firm’s overall strategic plan on environmental engagement is likely reflected in how it engages in each of the constructs that affect costs and benefits. Sustainable efforts, in short term, may put firms at risk. Companies may need to take a long-term perspective when cutting costs is curtailed.

### Originality/value

The research contributes to the ED and EP literature by using a 3SLS simultaneous equation method and analyzing a more recent and comprehensive multi-industry data. By controlling industry effect, the research investigates the interrelationships among three corporate constructs and finds interesting results. An interpretation and discussion are provided.

## Keywords

#### Citation

Lu, L. and Taylor, M. (2018), "A study of the relationships among environmental performance, environmental disclosure, and financial performance", Asian Review of Accounting, Vol. 26 No. 1, pp. 107-130. https://doi.org/10.1108/ARA-01-2016-0010

### Publisher

:

Emerald Publishing Limited

## 1. Introduction

The environmental issues of today have become global hot topics. Compared to a decade ago, environmental issues bring more and more discussion among corporations and regulators. As most large corporations compete in a global economy, environmental sustainability practices become a competitive strategy for a company’s success. How does environmental performance (EP) impact environmental disclosure (ED) and further impact a corporation’s profitability or equity value? Does EP affects financial performance (FP)? Is there any relationship between ED and FP? To answer these questions, this paper studies the relationships among the three corporate constructs: EP, ED, and FPFP jointly, using more current and comprehensive data obtained from Newsweek’s green rankings. The new data are more rigorous and reliable than data used in previous studies. In addition, the overall green score is z-standardized, making intra- and inter-industry comparison possible and meaningful.

Prior research has largely examined the three constructs either by using data from a single industry that is too old or a sample size that is relatively small. For example, Al-Tuwaijri et al. (2004) studied 198 firms using one-year data which are the Investor Responsibility Research Center’s 1994 Environmental Profiles Directory data. Clarkson et al. (2011) examined the relationship between EP and economic performance of 191 firms using data from 1990 to 2003. However, the research on environmental studies has changed significantly in the past decade. These changes include measurement of EP, requirements/standards of ED, data variability, and research methodology (Patten, 2002). For example, large corporations are now required to make more mandatory disclosures of their EP. In addition, recent studies in this area call for a comprehensive study using more current data and different environmental measures (Al-Tuwaijri et al., 2004). In this study, we reexamine the interrelationships among the three constructs using more current comprehensive data.

Previous studies document mixed results about the relationships among the three constructs. For example, Jaggi and Freedman (1992), Blacconiere and Patten (1994), and McPeak et al. (2010) found a negative relationship exists between EP and FP; a positive association has been documented by Hart and Ahuja (1996), Sroufe (2003), Al-Tuwaijri et al. (2004), Clarkson et al. (2011), and Davis et al. (2016); and no relationship was found by Yu et al. (2009). As for the relationship between EP and ED, a positive relationship has been documented by Al-Tuwaijri et al. (2004), Clarkson et al. (2011), and Gelb and Strawser (2001); a negative relationship has been observed by Patten (2002) and Cho and Roberts (2010); and a no relationship was found by Wiseman (1982). Ullmann (1985) explored the interrelationships among social performance, social disclosure, and economic performance, and suggested that an unobservable variable – management overall strategy – may jointly affect the relationships among the three constructs. A firm’s FP may depend on EP, ED, and other control variables. Similarly, EP is affected by FP, and EP reflects the disclosure of its performance. The error term in each function is correlated; therefore, the interrelationships among EP, ED, and FP were jointly examined. A simultaneous equations approach was used to test the hypothesis.

We investigate the interrelationships among EP, ED, and FP using a simultaneous equations system (SEM) and explored more current third-party provided data: 2012 Green Rankings for the top 500 largest US companies provided by Newsweek magazine. These companies were chosen to be included in the green ranking based on their size: market capitalization, employee numbers, and revenue. Individual companies themselves had no option to be included or excluded from the green ranking list, thus reducing the problem of selection bias. The green ranking report assigns rankings for each firm based on overall green scores. The green scores are calculated and compiled by two leading environmental research institutes, Truecost and Sustainalytics[1] who analyzed more than 700 environmental impact variable metrics, environmental policies and programs, and degree of transparency reporting. Due to the nature of rigorous and data-driven ranking procedures, the environmental data released by Newsweek are more comprehensive and objective. We observe a positive relationship between EP and ED, but a negative relationship between FP and EP in the three-stage least squares (3SLS) model specifications.

The system used in this study consists of three equations: the first one for FP proxied by firm value (Tobin’s Q); the second one for EP (revised green scores and revised ranks); and the third one for ED (disclosure scores). In total, a system of three equations has to be estimated. There are three endogenous variables. The three endogenous variables are the variables of interest. They are dependent variables in the three equations – EP, ED, and FP. FP and EP are also independent variables in EP-FP and FP-EP equations. A more in-depth discussion of the above variables is presented in Section 3.

This study finds a significantly positive relationship between EP and ED, a significantly negative relationship between EP and FP. In addition, the results of the study show that firm size is positively correlated to ED. This suggests that bigger firms are more likely to disclose their EP. Industry rank (INDRANK) is negatively correlated to EP, suggesting that industry green leaders are more likely leaders in EP.

In the additional tests section, an identification test was conducted on the system equations, and all three equations passed the identification test. To test the sensitivity of the model, revised ranks were used as an alternative measure of EP. The results are consistent with the main findings in which revised green score are used.

Information on EP and ED is important to stakeholders (shareholders, consumers, suppliers, employees, government regulators, and the general public). Without reliable, consistent, and accurate information for comparing companies, it is difficult for stakeholders to make informed strategic decisions. Thus, it is important to have a standardized measurement of EP and ED. Green scores are z-standardized measures, making intra- and inter-industry comparisons possible and meaningful. The empirical findings and analysis have important implications to both internal stakeholders, for example, employees and shareholders, and external stakeholders, such as customers and environmental regulators.

The remainder of the paper is organized as follows: Section 2 reviews the related literature and develops hypotheses; Section 3 provides research models and variable measurements; Section 4 describes data and sample selection; Section 5 discusses empirical results; Section 6 contains additional econometric tests and sensitivity analysis; and Section 7 concludes the paper, discusses its limitations, and provides suggestions for future research.

## 2. Theories, literature review, and hypotheses development

### 2.1 EP and FP

There are two views about EP and FP: the “traditionalist” view and the “revisionist” view. The former is rooted in neo-classical theory, which posits that pollution abatement measures are predicted to increase production costs and are assumed to have increasing marginal costs (Patten, 2002). The latter, also called the Porter theory, was initiated and developed mainly by Porter who theorized that pollution reduction provides future cost savings by increasing efficiency, reducing compliance costs, and minimizing future liabilities (Porter and van der Linde, 1995), thus increasing firm value.

The relationship between financial and EP has been investigated and debated for several decades. Under neo-classical theory, researchers have found that FP is negatively associated with EP (Lorraine et al., 2004; Murray et al., 2006; Blacconiere and Patten, 1994; Cordeiro and Sarkis, 1997; Jaggi and Freedman, 1992; McPeak et al., 2010), Scholars under this stream of EP studies argue that there is a conflict between the competitiveness of firms and their EP (Walley and Whitehead, 1994). Their discussion posits that firms in industries with higher environmental compliance costs (such as paper and pulp manufacturing industry) face a competitive disadvantage, because compliance costs of production activities outweigh the value added to the firm. Thus, high EP corresponds to low economic performance and vice versa.

Under the Porter theory, the high EP of firms would increase firms’ FP. This stream of research has documented that high EP is associated with increased FP (Davis et al., 2016; Lu and Taylor, 2016; Al-Tuwaijri et al., 2004; Clarkson et al., 2011; King and Lenox, 2001; Hart and Ahuja, 1996; Judge and Douglas, 1998; Montabon et al., 2007; Orlitzky et al., 2003; Russo and Fouts, 1997; Sroufe, 2003). King and Lenox (2001) found an association between reduced environmental emissions and increased financial profits. Scholars under this stream of environmental studies argue that the improved EP is a potential source for competitive advantage as it can lead to more efficient processes, improvements in productivity, lower costs of compliance, and new market opportunities (Porter, 1991; Porter and van der Linde, 1995; Schmidheiny, 1992). Thus, a positive relationship is expected to exist between EP and FP. Recent studies from Dhaliwal et al. (2011) and Lev et al. (2010) documented that firms with higher level of CSR have lower cost of capital and higher revenue growth, respectively. de Villiers et al. (2011) suggested that there is a positive relationship between strong EP and shareholder wealth. A most recent research study conducted by Davis et al. (2016) looked at a company’s corporate social responsibility (CSR) activity and tax avoidance practice and found socially responsible firms pay less tax. Reduced tax payment results in increased profit, thus increasing a firm’s FP. The findings of Davis et al. (2016) implicitly indicate a positive relationship between EP and FP. Lu and Taylor (2016) found a positive relationship between EP and FP using meta-analysis method. Another small group of researchers found no significant relationship between FP and EP (Yu et al., 2009).

### 2.2 EP and ED

There are two major theories on ED: legitimacy theory and stakeholder theory (Chan et al., 2014; Freedman and Jaggi, 2010). Legitimacy theory posits that firms, in order to legally exist, try to operate within the norms and expectations of the society within which they operate. Stakeholder theory posits that a company should be accountable to various stakeholders and thus a company’s ED is reflective to stakeholders’ demand.

In the USA, most EDs are made voluntarily. Companies have many channels to disclose their EP, for example, company website, annual report, or standalone non-financial report. Prior research documents that firms tend to disclose more environmental information on companies’ website when they face environmental crisis and more on annual report when they had environmental reputation (de Villiers and van Staden, 2011). Firms with good EP and a high level of ED are sending signals to the public that they take credit for their actions, and that the good EP is not to the detriment of stakeholders. Similarly, poor environmental performers tend to disclose less of their environmental activities. Guthrie and Parker (1990) suggested that even with regulation, poor performers may not be willing to disclose. They argued that “Corporations appear to respond to government or public pressure for information about their environmental impact but may choose to disclose such information only to the minimum degree required.”

The literature provides explanations about why companies would voluntarily disclose environmental information. Most researchers refer to legitimacy theory. Legitimacy theory posits that to achieve legitimacy firms should operate within the norms and expectations of the society within which they operate (Cong and Freedman, 2011; Deegan, 2002; de Villiers and van Staden, 2006; Dowling and Pfeffer, 1975; O’Donovan, 2002; van Staden and Hooks, 2007). Previous empirical evidence provides mixed results on the relationship between EP and the level of EDs. Some studies found a significant positive ED-EP relationship (Al-Tuwaijri et al., 2004; Clarkson et al., 2008, 2011; Gelb and Strawser, 2001; van Staden and Hooks, 2007), suggesting that EDs reflect EP. Al-Tuwaijri et al. (2004) found a positive relationship between EP and ED only after controlling for the endogeneity of EP. Their ED measure is based on information reported on the form 10 K and focused on pollution-related information in four areas: the total amount of toxic waste generated and transferred or recycled; financial penalties resulting from violations of federal environmental laws; potential responsible party for the cleanup of hazardous-waste sites; and the occurrence of reported oil and chemical spills. The authors used a content analysis method and self-assigned ED scores ranging from 0 to +3. Some studies (i.e. Patten, 2002; Cho and Patten, 2007; Cho and Roberts, 2010; Ingram and Frazier, 1980; Cho and Roberts, 2010) found that poor environmental performers make more disclosures than good performers to legitimize their environmental activities (Patten, 2002; Lindblom, 1994). Lindblom (1994) suggested that a corporation may use disclosure as a legitimizing device to change public perceptions or expectations about company’s performance, to distract public attentions from the company’s poor performance in environment by highlighting other accomplishments related to the environmental issue.

Stakeholder theory holds that EDs are made because they are demanded by the stakeholders. Managers provide environmental information that they believe is really what the stakeholders want. If a firm’s long-term survival and success depends on the resources provided by its external stakeholders, then a firm “requires the support of all its stakeholders” (van der Laan Smith et al., 2005) and the stakeholder demands will be addressed by management through performing and disclosing environmental strategies and activities. Environmental improvement programs can bring benefits and reputation to the business. It is reasonable to expect a positive relationship between EP and ED. In addition, as an increase in the global economy, companies are becoming more international. It is likely that those international companies have a growing impact on the social and ecological environment of both local and international communities, and therefore a growing expectation that companies should be accountable to various stakeholder groups for all such impacts is resulted (Chan et al., 2014).

According to Clarkson et al. (2008), firms with favorable EP voluntarily convey information to the stakeholders, while those with poor environmental records withhold information to avoid negative exposure. Further, Aerts and Cormier (2009) argued that “environmental legitimacy is significantly and positively affected by the extent and quality of annual report EDs.” Better environmental performers make more disclosures about positive environmental activities and the disclosures reflect a form of legitimacy; however, if poor performers make more statements about positive environmental activities, the disclosures reflect legitimization (Freedman and Wasley, 1990; Gray et al., 1995). Others (Freedman and Jaggi, 1982; Wiseman, 1982) found no significant relationship between performance and disclosure.

The reasons for an inconclusive result on the relationship between EP and ED can be many. Patten (2002) suggested several reasons for this, mainly that the samples were too small and that the studies did not control for extraneous variables that could influence the relationship.

Given the competing theories and conflicting results found about the relationships among EP, ED, and FP, we state our hypothesis in a null form as below:

There is no significant relationship between any two of the three corporate constructs: environmental performance, environmental disclosure, and financial performance.

## 3. Research models and variable measurements

### 3.1 Research models

The interrelationships among EP, FP, and ED can be jointly determined. Ullmann (1985) examined the interrelationships among social performance, social disclosure, and economic performance. Ullmann (1985) suggested that an unobservable variable, management overall strategy, may jointly affect the relationships among the three constructs. Thus, following the notion of Ullmann (1985) and the research conducted by Al-Tuwaijri et al. (2004), the following functions are established to test the null hypothesis that no relationship exists between any two of EP, ED, and FP:

(1) Financial performance = f ( Environmental performance + Control variables )
(2) Environmental performance = f ( Financial performance + Control variables )
(3) Environmental disclosure = f ( Environmental performance + Control variables )

The above functions imply that a firm’s FP depends on EP and other control variables. Similarly, EP is affected by FP, and EP reflects the disclosure of its performance. The empirical models, specifically, are shown below in a system of simultaneous equations:

(4) F P t = ω 0 + ω 1 E P t + 1 + ω 2 E D t + ω 3 S A L E S G t + ω 4 S I Z E t + ω 5 R O A t + ω 6 C F O t + ω 7 I N S T O W N t + ω 8 I N D R A N K t + ω 9 27 I N D U S T R Y + μ 1
(5) E P t + 1 = γ 0 + γ 1 F P t + γ 2 E D t + γ 3 L E V t + γ 4 I N S T O W N t + γ 5 C O N C E R N t + γ 6 C A P I N T E N S t + γ 7 I N D R A N K t + γ 8 26 I N D U S T R Y + μ 2
(6) E D t + 1 = θ 0 + θ 1 + E P t + 1 + θ 2 S I Z E t + θ 3 C O N C E R N t + θ 4 C A P I N T E N S t + θ 5 A G E t + θ 6 24 I N D U S T R Y + μ 3
In which, t=year of 2011.

Newsweek, working with two research providers – Truecost and Sustainalytics – spent over a year to compile the green rankings, thus in the above models, to match the actual EP, the 2011 financial data for each company are used in the estimation. In Equation (4), EDt represents 2011 ED score, we call it lagED (relative to 2012 ED score) in the data analysis and discussion sections.

It normally takes a year to compile green rankings report, so when 2012 green ranking was issued; it corresponds to the fiscal year of 2011 financial data. Therefore, all control variables and FP are measured with one-year lag.

In this system, FP, EP, and ED are the endogenous variables as well as dependent variables, and the rest of the variables are control variables.

The variables included in the equations consider prior studies and model identification in a SEM. Al-Tuwaijri et al. (2004) argued that prior period ED may affect FP and EP, thus prior year disclosure score (EDt or lagED) was added to the FP and the EP equations. Clarkson et al. (2011) posited that sales growth and enterprise value (Tobin’s Q) are evidence of the proactive investment strategy in intangibles and thus used them as proxies for unobservable management talent or capability. In this paper, we use sales growth (SALESG), capital intensity (CAPINTENS), and firm value (FP calculated as Tobin’s Q) to proxy for management ability and thus overall management strategy (Al-Tuwaijri et al., 2004; Clarkson et al., 2011; Lyon and Shimshack, 2015; Porter and van der Linde, 1995). Industry rank (INDRANK) is used to proxy for environmental exposure within the industry. Prior studies tend to use SIC code as a proxy for environmental exposure (Al-Tuwaijri et al., 2004; Deegan and Gordon, 1996; Wiseman, 1982). In addition, the relationships among EP, ED, and FP are likely affected by industries that firms belong to[2], therefore, our models control for industry effect by adding industry dummy variables. There are 19 industries included in the models (one industry sector is dropped when the models are run, since the dropped industry is served as a control industry. Table III in Section 4.2 presents a whole list of industry sectors found in the final sample.

The data in this paper are initially from 2012 Newsweek’s green ranking[3], which reports EP and ED for 500 largest US publicly traded firms. These companies were chosen to be included in the green ranking based on their size. EP is measured by revised green scores and revised green rank scores obtained from Newsweek’s (2012) green rankings.

### 3.2 Measurement of variables

#### 3.2.1 Dependent variables

Following Clarkson et al. (2011), FP is measured as market capitalization plus debt and preferred shares divided by beginning of period total assets. It measures the firm value and proxies for intangible assets associated with innovation (Al-Tuwaijri et al., 2004; Lyon and Shimshack, 2015; Porter and van der Linde, 1995). The measurement for EP is the revised green score: 50 percent of impact score plus 50 percent of management score on Newsweek’s (2012) green rankings. A revised green score is used because the original green score provided by Newsweek is a weighted score of three components: environmental impact score (45 percent), environmental management score (45 percent), and disclosure score (10 percent). The disclosure score is a measure of the ED, thus it is necessary to adjust the green score so that it would not be contaminated by disclosure score. The additional analysis shows that even using the original green score, the main results of this study do not change. The measurement for ED is the disclosure score obtained from Newsweek’s (2012) green rankings. The lagged ED score was obtained from Newsweek’s (2011) green rankings.

#### 3.2.2 Control variables

Prior research shows that SIZE, LEV, ROA, CFO, sales growth (SALESG), equipment age, and capital intensity are determinants of FP and EP (Al-Tuwaijri et al., 2004; Clarkson et al., 2008, 2011). INDRANK is a company’s rank within industry, obtained from Newsweek’s (2012) green rankings. Other control variables include institutional ownership (INSTOWN) (Graves and Waddock, 1994) and environmental concern score (CONCERN) (Al-Tuwaijri et al., 2004). INSTOWN was hand collected from MSN money website. CONCERN was calculated as the difference between environmental concern score and environmental strength score from Kinder, Lydenberg, and Domini (KLD).

## Table V

Correlation coefficients

 Panel A: correlation matrix of environmental variables RANK EP ED IMPACT MGMT GREENSCORE RANK 1.00000 EP −0.9246* (0.0000) 1.0000 ED −0.3095* (0.0000) 0.0064 (0.8920) 1.0000 IMPACT −0.5866* (0.0000) 0.7809* (0.0000) −0.4149* (0.0000) 1.0000 MGMT −0.6938* (0.0000) 0.5555* (0.0000) 0.5626* (0.0000) −0.0857 (0.0694) 1.0000 GREEN SCORE −0.9730* (0.0000) 0.9542* (0.0000) 0.3052* (0.0000) 0.6196* (0.0000) 0.6972* (0.0000) 1.0000 Panel B: correlation matrix of all variables 1 2 3 4 5 6 7 FP 1 1.0000 EP 2 0.0365 (0.4397) 1.0000 ED 3 −0.1388* (0.0032) 0.0064 (0.8920) 1.0000 lagED 4 −0.1092* (0.0205) 0.1060* (0.0245) 0.8478* (0.0000) 1.0000 SIZE 5 −0.3665* (0.0000) 0.0587 (0.2142) 0.3985* (0.0000) 0.3765* (0.0000) 1.0000 ROA 6 0.7258* (0.0000) 0.0744 (0.1148) −0.0958* (0.0422) −0.0561 (0.2353) −0.2422* (0.0000) 1.0000 CFO 7 0.7405* (0.0000) 0.1072* (0.0230) −0.0907 (0.0546) −0.0581 (0.2185) −0.2625* (0.0000) 0.7605* (0.0000) 1.0000 SALESG 8 0.2949* (0.0000) −0.0529 (0.2624) −0.1429* (0.0024) −0.1888* (0.0001) −0.1360* (0.0038) 0.2884* (0.0000) 0.2330* (0.0000) LEV 9 0.0323 (0.4946) −0.1544* (0.0010) 0.0455 (0.3351) −0.0019 (0.9687) −0.0213 (0.6522) −0.1051* (0.0257) −0.0119 (0.8007) CONCERN 10 −0.0097 (0.8373) −0.3773* (0.0000) −0.4311* (0.0000) −0.4093* (0.0000) −0.1466* (0.0018) −0.0036 (0.9388) −0.0013 (0.9777) INSTOWN 11 0.0694 (0.1416) 0.0363 (0.4418) −0.2681* (0.0000) −0.2641* (0.0000) −0.3289* (0.0000) 0.0164 (0.7294) 0.0552 (0.2422) AGE 12 −0.1038* (0.0277) −0.4604* (0.0000) 0.3160* (0.0000) 0.1828* (0.0001) 0.1348* (0.0042) −0.1044* (0.0268) −0.0961* (0.0417) CAPINTENS 13 0.0984* (0.0368) −0.1618* (0.0006) 0.0852 (0.0711) 0.0402 (0.3954) −0.0603 (0.2015) 0.0526 (0.2658) 0.3107* (0.0000) INDRANK 14 −0.0482 (0.3072) −0.5011* (0.0000) −0.4631* (0.0000) −0.4387* (0.0000) −0.0928* (0.0492) −0.0334 (0.4802) −0.0759 (0.1081) 8 9 10 11 12 13 14 FP 1 EP 2 ED 3 lagED 4 SIZE 5 ROA 6 CFO 7 SALESG 8 1.0000 LEV 9 −0.0319 (0.5003) 1.0000 CONCERN 10 0.1276* (0.0067) −0.0437 (0.3546) 1.0000 INSTOWN 11 0.0494 (0.2961) −0.0586 (0.2149) 0.1197* (0.0110) 1.0000 AGE 12 0.0206 (0.6625) 0.2213* (0.0000) 0.1248* (0.0081) −0.2770* (0.0000) 1.0000 CAPINTENS 13 0.1470* (0.0018) 0.1639* (0.0005) 0.1215* (0.0099) −0.0053 (0.9111) 0.2837* (0.0000) 1.0000 INDRANK 14 0.0451 (0.3399) −0.0692 (0.1425) 0.3414* (0.0000) 0.1496* (0.0015) −0.0704 (0.1360) −0.1381* (0.0033) 1.0000

## Table VII

Estimation results of 3SLS (environment performance = revised RANK)

Equation (4) Equation (5) Equation (6)
Variables FP RANK ED
RANK 0.000142 (0.000370) −0.130*** (0.0126)
lagED 0.000357 (0.00151) −1.324*** (0.130)
SALESG 0.532** (0.222)
SIZE −0.174*** (0.0329) 5.149*** (1.017)
ROA 6.473*** (0.809)
CFO 6.640*** (0.712)
INSTOWN −0.00122 (0.00253) −0.104 (0.203)
INDRANK −0.00290 (0.00408) 7.005*** (0.318)
FP 10.87*** (3.118)
LEV 14.35 (15.12)
CAPINTENS −52.35 (69.55) 1.491 (23.28)
CONCERN 8.209*** (2.519) −3.693*** (0.898)
AGE 1.384*** (0.233)
INDUSTRY Included Included Included
Constant 1.943*** (0.449) 297.7*** (23.70) 25.85* (13.93)
Observations 450 450 450
R2 0.644 0.799 0.533

## Table AII

Estimation results of OLS, 2SLS, and 3SLS (EP = revised RANK)

OLS (Equation (4)) OLS (Equation (5)) OLS (Equation (6)) 2SLS (Equation (4)) 2SLS (Equation (5)) 2SLS (Equation (6)) 3SLS (Equation (4)) 3SLS (Equation (5)) 3SLS (Equation (6))
Variables FP RANK ED FP RANK ED FP RANK ED
RANK 0.000570 (0.000536) −0.0855*** (0.00987) 0.000140 (0.000374) −0.132*** (0.0129) 0.000142 (0.000370) −0.130*** (0.0126)
lagED −0.000177 (0.00165) −0.650*** (0.142) −1.92e-05 (0.00153) −0.636*** (0.142) 0.000357 (0.00151) −1.324*** (0.130)
SALESG 0.660*** (0.228) 0.562** (0.225) 0.532** (0.222)
SIZE −0.183*** (0.0384) 5.884*** (1.037) −0.165*** (0.0334) 4.249*** (1.099) −0.174*** (0.0329) 5.149*** (1.017)
ROA 6.015*** (0.841) 6.408*** (0.821) 6.473*** (0.809)
CFO 7.341*** (0.749) 6.709*** (0.722) 6.640*** (0.712)
INSTOWN −0.000569 (0.00258) 0.0462 (0.222) −0.00115 (0.00256) 0.0411 (0.222) −0.00122 (0.00253) −0.104 (0.203)
INDRANK −0.00971* (0.00559) 7.808*** (0.330) −0.00326 (0.00413) 7.819*** (0.330) −0.00290 (0.00408) 7.005*** (0.318)
FP 9.512*** (2.684) 12.66*** (3.415) 10.87*** (3.118)
LEV 9.009 (16.70) 8.948 (16.73) 14.35 (15.12)
CAPINTENS −34.69 (71.00) 1.479 (23.12) −44.49 (71.41) −0.756 (23.72) −52.35 (69.55) 1.491 (23.28)
CONCERN 10.79*** (2.587) −5.593*** (0.836) 10.83*** (2.591) −3.722*** (0.914) 8.209*** (2.519) −3.693*** (0.898)
AGE 1.460*** (0.249) 1.533*** (0.255) 1.384*** (0.233)
INDUSTRY Included Included Included Included Included Included Included Included Included
Constant 1.543*** (0.561) 255.3*** (25.21) 1.527 (13.31) 1.865*** (0.455) 252.5*** (25.32) 34.81** (14.77) 1.943*** (0.449) 297.7*** (23.70) 25.85* (13.93)
Observations 450 450 450 450 450 450 450 450 450
R2 0.661 0.810 0.555 0.644 0.809 0.532 0.644 0.799 0.533

Notes: Revised RANK, revised green ranking. It ranges from 1 to 500, calculated based on revised overall green scores; LagED, prior year’s environmental disclosure score, i.e. environmental disclosure score of 2011 obtained from 2011 green rankings; SALESG, sales growth, measured by change in sales divided by beginning of period sales; SIZE, firm size, measured as natural logarithm of total assets (\$ millions); ROA, return on assets, measured as net operating income divided by beginning period total assets; CFO, cash flow from operations, measured as liquidity, measured as net cash ﬂow from operating activities divided by beginning of period total assets; INSTOWN, institutional ownership, retrieved from MSN money website; INDRANK, industry rank, obtained from 2012 Newsweek’s green rankings; FP, firm value, measured as market capitalization plus debt and preferred shares, divided by beginning of period total assets; LEV, leverage ratio, measured as total debt divided by total assets (Clarkson et al., 2011); CAPINTENS, capital intensity, measured as capital expenditures divided by beginning of period total assets; CONCERN, environmental concern score, calculated as the difference between environmental total concern score and environmental total strength score from KLD; AGE, equipment age is net property, plant and equipment divided by annual depreciation, which assumes all ﬁrms use straight line depreciation; INDUSTRY, dummy variables, used to control for industry fixed effect. The Table reports the OLS, 2SLS, and 3SLS estimation results as a comparison when EP is measured by revised ranks. The 3SLS results enhance the OLS and 2SLS results because it provides more consistent and efficient estimation than OLS and 2SLS. More discussions can be found in Section 5. In total, 19 industries (see Table III) are included in the model with one industry dropped as a control group. Standard errors are in parentheses. *p<0.1; **p<0.05; ***p<0.01

## Notes

1.

The Newsweek’s green rankings compares the actual environmental footprints, management (policies, programs, initiatives, controversies), and reporting practices of big companies. Newsweek collaborated with leading environmental research providers, Trucost and Sustainalytics, to assess each company’s environmental footprint, management of that footprint, and transparency to create the most comprehensive rankings available. Truecost is a leading research company “specializes in quantitative measurements of environmental performance and holds the most extensive data available on corporate environmental impacts.” More details can be found at the company’s website: www.trucost.com. Sustainalytics is an organization dedicated to providing ESG research and services for a variety of clients with broad academic and work experience. More details can be found at the company’s website: www.sustainalytics.com

2.

Given that industries have different life cycles and business models, they may have different environmental policies. We added industry dummy variables to control for industry effect.

3.

Newsweek magazine launched the first green ranking report in 2009, providing green scores for a list of top 500 largest US companies as measured by revenue, market capitalization, and number of employees. 2010s green rankings include top 500 US companies. Both 2009 and 2010 green rankings provide only green score but not disclosure score for each US company on the list. Newsweek also changed its partners in 2011. Due to lack of disclosure score reported on these two earlier years’ green rankings and change of methodology, it is not appropriate to use these two years’ green data. Newsweek did not issue green rankings in 2013. Newsweek changed its research partners when it collaborated the 2014 and 2015 green rankings. Due to the change of research partners, the methodologies used for computing green scores and disclosure scores are quite different from green rankings released in previous years, thus the comparison between 2012 and years beyond becomes meaningless. The environmental data are limited to only two years: 2011 and 2012 green rankings from Newsweek.

4.

Newsweek changed its research partners in 2014, as well as research methodology. Thus, the most recent two years of green rankings, i.e. 2014 and 2015, would not be appropriate to be included in this study.

5.

In our simultaneous equation model, only environmental disclosure (ED) measure used two years of data: 2011 and 2012. Environmental performance (EP) used the 2012 green scores.

6.

The green ranking report is normally issued with a one-year lag, so the financial performance and other control variables are measured using 2011 data.

7.

Available at: www.trucost.com (accessed July 2, 2014).

8.

Available at: www.sustainalytics.com (accessed July 2, 2014).

9.

Because error terms in three equations are correlated with each other, 3SLS overcomes the inconsistency presented in OLS and inefficiency shown in 2SLS, thus more accurate results are expected from the 3SLS model (Wooldridge, 2006).

Table AI

Table AII

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## Acknowledgements

The authors gratefully acknowledge the insightful comments from two anonymous reviewers. The authors also benefited greatly from comments and suggestions from participants at the 2013 AAA Annual Meeting and from participants and discussant at the 2015 AAA Midwest Region Meeting. The authors sincerely appreciate the invaluable comments and suggestions from Editor Haiyan Zhou and other editors at the Asian Review of Accounting 2016 International Accounting Symposium.

## Corresponding author

Lucy Wenxiang Lu can be contacted at: wlu@fsmail.bradley.edu