To Disclose or Not to Disclose Climate-Change Risk in Form 10-K: Does Materiality Lie in the Eyes of the Beholder?

 

To Disclose or Not to Disclose Climate-Change Risk in Form 10-K: Does

Materiality Lie in the Eyes of the Beholder?

Ella Mae Matsumura University of Wisconsin–Madison

Wisconsin School of Business ellamae.matsumura@wisc.edu

Rachna Prakash University of Mississippi Patterson School of Accountancy

rprakash@olemiss.edu

Sandra C. Vera-Muñoz University of Notre Dame Mendoza College of Business

sveramun@nd.edu

We gratefully acknowledge the helpful comments and suggestions of Brett Cantrell, Shuping Chen, Lisa Gaynor, Brian Goodson, Eric Hirst, Steve Kachelmeier, Bill Kinney, Bob Lipe, Uday Murthy, Mark Nelson, Zoe-Vonna Palmrose, Jaime Schmidt, Marcy Shepardson, Holly Skaife, Deb Wenger, and workshop participants at the University of Texas –Austin 2016 Fall Research Conference, the Lynn Pippenger School of Accountancy at the University of South Florida, and the University of Cincinnati. We are also very grateful to Stephannie Larocque for generously sharing her cost-of-equity program with us. Professor Vera-Muñoz gratefully acknowledges financial support by the Notre Dame/Deloitte Center for Ethical Leadership, KPMG through the Department of Accountancy, and the Business Information Center, University of Notre Dame.

   

To Disclose or Not to Disclose Climate-Change Risk in Form 10-K: Does Materiality Lie in the Eyes of the Beholder?

ABSTRACT

We examine the relation between managers’ decisions whether to disclose climate-change risk (CCR) in Form 10-K and firm risk. Ambiguity about the materiality of CCR and the SEC’s inconsistent enforcement of CCR disclosures cause uncertainty about whether disclosing CCR is mandatory or voluntary. We hand-collect data over a seven-year period from about 3,000 Form 10-K filings of S&P 500 firms on whether they disclosed CCR. We use SASB’s Materiality Map™ _{to proxy for report users’ judgments of the materiality of CCR. We find that the cost of}

equity (COE) of disclosing firms is 21.3 bps lower than the COE of non-disclosing firms. More importantly, we find that for firms where report users judge CCR as material, the COE of disclosers is 49.1 bps lower than that of non-disclosers. In contrast, we find no association between disclosing CCR and COE for firms where report users judge CCR as not material.

Keywords: Regulation S-K; risk assessment; voluntary disclosure; mandatory disclosure; enforcement; Sustainability Accounting Standards Board’s (SASB) Materiality Map™_{; cost of equity capital; self-selection.}

“We recommend that the Commission now move to promote and enforce mandatory and meaningful disclosures of the material effects of climate change on issuers, and also that the SEC work to provide more industry-specific guidance on how to account for climate risk.”

(Former Secretaries of the Treasury H. M. Paulson, R. E. Rubin, and G. P. Shultz, Comment Letter to the SEC, 1/20/16)

I. INTRODUCTION

Federal securities regulation and case law uphold managers’ affirmative duty to disclose all material information in their firms’ Securities and Exchange Commission (SEC) filings (SEC 2016; Sommer Report 1977). Yet, managers’ decisions whether to disclose climate-change risk (CCR) in Form 10-K are confounded by two key institutional factors.1 _{First, there is little} consensus on whether CCR is a material risk to the firms (Hulac 2016; Coburn and Cook 2014). Second, federal CCR disclosure regulation has been inconsistently enforced across firms (GAO 2016, 21; Gelles 2016). We argue that these factors, along with managers’ unobservable

evaluations of the costs and benefits of disclosing versus not disclosing CCR, create ambiguity about whether disclosing CCR in Form 10-K is voluntary or mandatory. This, in turn, hinders investors’ ability to discern whether managers who choose to not disclose CCR are deliberately trying to conceal useful but adverse information, or are instead acknowledging that CCR is not a material risk. This complex institutional context raises a fundamental empirical question: Are managers’ decisions whether to disclose CCR associated with firm risk, as measured by the cost of equity capital?

Regulation S-K requires firms to disclose in their SEC filings “the most significant factors that make an investment in the registrant speculative or risky” (Regulation S-K, Item 503(c), SEC 2004). The 2010 SEC interpretive guidance clarifies Regulation S-K and specifies

1 _{In the interest of brevity, from this point onward “in Form 10-K” is generally implied whenever we refer to} managers’ decision to disclose CCR, and “users” refers to stakeholders who use Form 10-K to make their decisions.

that if managers assess CCR as material to the firm, then they are mandated to disclose it (SEC 2010).2 _{Yet, according to analysts, “for investors interested in managing the economic risks of} climate change, the SEC is among the least helpful places to look” (Hulac 2016). On one hand, if managers perceive that CCR disclosure regulation is strongly enforced but choose to not

disclose, then they likely assess CCR as not material. Alternatively, managers may assess CCR as material but choose to not disclose it if they perceive that regulation is weakly enforced and conclude that the costs of disclosing CCR exceed the benefits. Thus, if managers choose to not disclose CCR, then it is difficult for the market to reliably infer managers’ assessments of the materiality of CCR for the firm. The lack of consensus about whether CCR is material to the firm, and the SEC’s inconsistency in enforcing disclosure of material CCR provide the primary motivation for our inquiry on the association between managers’ decisions whether to disclose CCR and firm risk.

The importance of our inquiry is threefold. First, firms’ failure to disclose material CCR in 10-K filings may leave investors, who are looking for information to assess and reduce risks in their portfolios, exposed to potentially significant losses (McCann 2016; Olson and Viswanatha 2016; Newlands 2015). We discuss a recent example of CCR related to the concept of stranded assets. The United Nation’s 2015 Paris Agreement set a worldwide goal to curb greenhouse gas (GHG) emissions to keep global temperatures from rising more than 2° C (3.6° F) above pre-industrial levels.3 To achieve this goal, scientists estimate that three-quarters of the fossil fuel reserves, including oil, gas, and coal, will need to stay in the ground (i.e., stranded).4

2_{For a detailed discussion of the guidance, see Shorter (2013).} 3 _{Source: http://bigpicture.unfccc.int/#content-the-paris-agreemen}

4 _{Statement by Christiana Figueres, Executive Secretary, United Nations Framework Convention on Climate Change} (available at: http://unfccc.int/files/press/statements/application/pdf/20140204_ipieca.pdf).

If fossil fuel companies are required to leave a significant bulk of their reserves (i.e., their assets) stranded, then their valuations could take a deep dive. This is the key argument invoked by ExxonMobil’s shareholders in a recently filed class-action lawsuit against the firm. The lawsuit alleges that shareholders suffered financial losses after paying inflated prices for the firm’s stock, even though the firm knew that the value of its oil reserves was significantly less than what it disclosed. Exxon publicly represented that none of its assets were stranded because the impacts of climate change, if any, were uncertain and far off in the future (Hasemyer 2016). Yet, in its 10-K filings in 2017, Exxon wrote off 3.3 billion barrels of oil equivalents which the company deemed as stranded (Smith 2017). Further, in a recent nonbinding resolution led by Exxon’s two largest shareholders, Vanguard Group and BlackRock, Inc., 62 percent of shareholders called for the company to disclose more open and detailed analyses of the risks posed by climate change regulation. The proposal also pushes Exxon to conduct a climate “stress test” to measure how new energy technologies to reduce GHG emissions could impact the value of its oil assets (Cardwell 2017; Olson 2017).

Second, our inquiry is important because mainstream investment analysts’ decisions to buy, sell, or hold a security are increasingly influenced by sustainability disclosures (SASB 2016, 2). In a 2015 CFA Institute survey of 1,325 institutional investors, 73 percent of respondents indicated that they take environmental, social, and governance (ESG) issues into account in their investment analyses and decisions. The top reason investors incorporate ESG-related information in their decisions is to determine whether a company is adequately managing risk (CFA Institute 2015). Relatedly, BlackRock, Inc. has urged investors to incorporate climate change in their investment decisions and to make climate-proof portfolios a key consideration for

all asset owners (BlackRock Investment Institute 2016).5 Notably, 52 percent of shareholder proposals in proxy filings in 2015 related to environmental and social issues (EY 2015).

Finally, our inquiry regarding the capital-market effects of mandating disclosure of material CCR in SEC filings is important in light of recent global trends towards increasingly requiring such disclosures. These trends include, among others, the European Union’s (EU) recent mandate (European Parliament 2014/95/EU) on ESG disclosures and the ESG disclosure guidance developed by the World Federation of Exchanges (WFE 2015). These global trends highlight the need to better understand the association between disclosing CCR and firm risk.

We hand-collect 2,996 firm-year observations of S&P 500 firms’ choices whether to disclose CCR for 2008 to 2014. We obtain our sample from the intersection of the S&P 500 index firms and the Ceres, SASB, and CDP databases.6 We collect our sample firms’ decision to disclose CCR from the Ceres database. A majority of the firms in our sample voluntarily report CCR through the CDP climate change survey. Therefore, we control for this voluntary disclosure by including firms’ decision to participate in the survey. Because users’ judgments of CCR materiality are industry-specific (Khan, Serafeim, and Yoon 2016), we use SASB’s Materiality Map™_{, an industry-based classification of CCR materiality.}

To proxy for firm risk, we construct a composite implied cost of equity (COE) measure using the median of the following four measures suggested by the accounting and finance literatures: Easton’s price earnings growth (PEG) model (2004), Gebhardt, Lee, and

5 _{In addition, corporate board responsibility for climate change has increased from 67 percent to 95 percent from} 2010 to 2015, according to a 2015 climate change report from CDP (CDP 2015, 6).

6 _{Ceres is a coalition of investors, companies, and public interest groups whose mission is to build a sustainable} global economy. In 1997, Ceres launched the Global Reporting Initiative (GRI), which has been widely adopted as the standard for sustainable reporting worldwide. The first year of data availability in Ceres is 2008. See

http://ceres.org/about-us/who-we-are. We provide details on SASB in Appendix A. CDP (formerly Carbon Disclosure Project) is a nonprofit that surveys the world’s largest companies by market capitalization on various sustainability topics. Its advisers consist of a network of 827 institutional investors representing over $100 trillion in assets under management. See https://www.cdp.net/en.

Swaminathan (2001) (GLS), Claus and Thomas (2001) (CT), and the price-earnings ratio. Our analyses using propensity score matching and doubly robust regressions offer two important results. First, even after controlling for firms’ decisions to voluntarily disclose CCR in the CDP survey, we find a negative association between disclosing CCR and COE. Specifically, our doubly robust regression results indicate that the COE of disclosing firms is significantly lower, by 21.3 bps, than the COE of non-disclosing firms.

More importantly, and central to our materiality prediction, we find that, in industries where users judge CCR as material, the COE of disclosing firms is 49.1 bps lower than the COE of non-disclosing firms. In contrast, we find that disclosing vs. not disclosing CCR is not

significantly associated with the COE for firms in industries where users judge CCR as not material. We conduct several robustness tests to assess the sensitivity of our main results and our inferences are unchanged.

We contribute to and extend in several ways the growing literature on capital-market implications of voluntary and mandatory sustainability disclosures. First, most of the extant research examines disclosures that are either unambiguously mandatory (Kravet and Muslu 2013), or unambiguously voluntary (Dhaliwal et al. 2011). Unlike prior research, we examine a setting where there is considerable ambiguity as to whether CCR is a mandatory or voluntary Form 10-K disclosure.

Second, recent studies urge researchers to examine interactions between mandatory and voluntary disclosures (Beyer, Cohen, Lys, and Walther 2010; Heitzman, Wasley, and

Zimmerman 2010). Our study extends Matsumura, Prakash, and Vera-Muñoz (2014), who find a negative association between firm value and carbon emission levels. They also find a higher median market value for firms that disclose their carbon emissions to the CDP voluntarily than

for non-disclosing firms. Our study further contributes to the literature by examining the risk relevance of disclosing CCR in 10-K filings, incremental to voluntary CCR disclosures to CDP. Our findings lend support to the concerns that managers’ failure to disclose CCR imposes additional risk on firms, but only in industries where users judge CCR as material. Our results also extend those of Khan et al. (2016), who find a positive association between sustainability investments and future abnormal stock returns, but only in firms that have strong ratings on material sustainability issues.

Finally, our study sheds light on the SEC’s recent call for public comment on whether certain Regulation S-K disclosure requirements need to be updated to better serve the needs of investors and registrants (SEC 2016). The materiality principle is intended to balance investors’ need for information to make informed decisions, without being burdened with excessive information, against the cost to registrants of providing information. Our findings provide evidence that disclosing CCR is associated with lower COE, but only when users judge CCR to be material.

The remainder of this paper is organized as follows. The next section discusses

institutional background on CCR, while section III reviews the research literature and develops our hypotheses. Sections IV and V describe our research design and provide the results of hypotheses tests, respectively. The last section briefly summarizes the findings and discusses the study’s limitations and implications for research and practice.

II. INSTITUTIONAL BACKGROUND ON CLIMATE-CHANGE RISK

According to Item 503(c) of Regulation S-K, a registration statement filed with the SEC must contain a discussion of the most significant factors that make the offering speculative or risky (SEC 2004). In addition, Form 10-K filings must also include this information, and 10-Q

filings must set forth any material changes to the risk factors described in the annual filings. The 2010 SEC interpretive guidance clarifies Regulation S-K and specifies that companies are expected to disclose CCR that can materially affect registrants’ business operations and financial performance (SEC 2010). Climate-related risks include those related to the transition to a lower-carbon economy (e.g., policy, legal, technology, reputation, and market changes to address mitigation and adaptation requirements related to climate change); and risks related to the physical impacts of climate change (e.g., due to floods, rising sea levels, and water availability, with direct damage to assets and indirect impacts from supply chain disruption) (SEC 2010).

Despite the growing importance of CCR to investors’ understanding of a company’s performance (Deloitte & Touche LLP 2016; Gelles 2016; UBS 2012), a recent study that

examines CCR disclosures of the 20 largest publicly traded U.S. companies in their 2012 through 2014 Form 10-K filings finds that most companies reported little or no information on CCR (InfluenceMap 2015). For example, GE did not disclose in its 10-K filings the risk that climate change poses to its supply chain (e.g., water shortages, severe weather patterns), despite having more than 130 manufacturing facilities in 40 countries (InfluenceMap 2015, 2).7 _{Further, Boeing}

failed to mention CCR in its 10-K filings, even though its 2014 annual report stated that, “costs incurred to ensure continued environmental compliance could have a material impact on our results of operations, financial condition or cash flows” (Olson and Viswanatha 2016).

In a high-profile case analogous to the ExxonMobil case, Peabody Energy privately projected a devaluation of its coal reserves as a result of passage of regulations to curb emissions from the combustion of coal. However, the company withheld this information from investors,

7 _{Many firms disclose CCR outside of documents filed with the SEC through voluntary disclosure initiatives or in} response to non-SEC regulatory requirements (Walter 2010). In addition to CDP, other voluntary channels include corporate sustainability reports through the Global Reporting Initiative (GRI), corporate websites, and social media.

choosing instead to state in its 2011 through 2014 10-K filings that “it was not possible to reasonably predict the impact that any such laws or regulations may have on [Peabody’s] results of operations, financial condition or cash flows” (New York Attorney General 2015). Although Peabody eventually agreed to fully disclose in its 10-K filings the potential impact of climate change regulation on the value of its coal reserves, investors suffered millions of dollars in losses as the company’s shares dropped from $1,000 in 2011 to around $4 four years later, and it filed for bankruptcy in April 2016.

III. THEORY AND HYPOTHESES DEVELOPMENT

According to federal securities laws, materiality is “the cornerstone” of the corporate disclosure system and serves as a “standard for determining whether a communication (filed or otherwise) omits or misstates a fact of sufficient significance that legal consequences should result” (Sommer Report 1977, 320). In Basic, Inc. v. Levinson (485 U.S. 224 (1988)), the Supreme Court upheld the definition of materiality as laid out in TSC Industries, Inc. v. Northway, Inc. (426 U.S. 438, 439 (1976)), further clarifying that to fulfill the materiality

requirement there must be “a substantial likelihood that disclosure of the omitted fact would have been viewed by the reasonable investor as having significantly altered the 'total mix' of

information made available.”

Heitzman et al. (2010, 111) state that “materiality defines the threshold between the important and the trivial.” Drawing on both federal securities regulation and case law, Heitzman et al. (2010) assert that if a given item meets a materiality threshold, then managers have an affirmative duty to disclose it in the firm’s SEC filings. Regulation S-K articulates the non-financial statement disclosure requirements under both the Securities Act and the Exchange Act (SEC 2016). Both of these Acts require registrants to disclose information deemed necessary by

the Commission, in the public interest, or for the protection of investors (SEC 2016, 23928).8 The 2010 SEC interpretive guidance requires registrants to apply existing materiality rules, consistent with the Supreme Court’s definition of materiality and case law, to guide their CCR disclosure decisions.

Cost of Equity Effect: Materiality and Enforcement of CCR Disclosures

Notwithstanding the existing regulation, managers’ decisions whether to disclose CCR are complicated due to two key institutional factors. First, there is little consensus, even across firms within the same industry, on whether climate change is a material risk to firms (Hulac 2016; Coburn and Cook 2014).9, 10 For instance, Wells Fargo has not been disclosing CCR in its 10-K filings, even though the company includes detailed GHG emissions data in its corporate social responsibility report. Second, the SEC has not consistently enforced regulations on CCR disclosure. Therefore, managers’ perceptions of SEC enforcement of these disclosures likely vary along a continuum from weak to strong. As Figure 1 shows, managers’ ultimate CCR disclosure decisions are the observable outcome of their unobservable assessments of the materiality and SEC enforcement of CCR disclosures, as well as their evaluations of the costs and benefits of disclosing versus not disclosing CCR. We use Figure 1 to guide our discussion and motivate our hypotheses.

| Insert Figure 1 about here |

8 _{Although the initial materiality determination is management’s, this judgment is subject to challenge or question} by the Commission or in the courts (Sommer Report 1977, 332). To determine whether information is material, courts evaluate whether the “likelihood exists that the event is reasonably likely to occur” (Schwartz and Mussio 2007). If a firm determines that a trend, demand, commitments, event, or uncertainty is unlikely to occur, then the firm has no duty to disclose (Wallace 2008, 307).

9 _{In fact, disagreements regarding CCR materiality surfaced in the SEC commissioners’ 3-2 vote on the 2010} interpretive guidance. One dissenting commissioner did not believe that the guidance “will result in greater availability of material, decision-useful information geared toward the needs of the broad majority of investors” (Casey 2010).

Disclosing Material CCR is Mandatory

Due to disclosure requirements laid out by federal securities laws, disclosing information in regulatory filings may signal that managers assess the information as material. A recent study finds that mining-related citations and injuries of firms that disclose mine safety records in SEC filings are significantly lower than those of non-disclosing firms (Christensen, Floyd, Liu, and Maffett 2016). The authors reason that investors and other stakeholders might perceive

managers’ decisions to disclose mine safety records as an implicit signal that managers assess this information as material. Importantly, these records are already publicly available through the Mine Safety and Health Administration’s (MSHA) website. Further, SEC filings broadcast mine safety records to a wide range of interested parties at a low incremental acquisition cost—even if investors are not explicitly looking for them.

There are at least two mechanisms to compel firms’ disclosure of material information. First, the SEC ensures that firms are providing mandatory disclosures by periodically reviewing firms’ SEC filings and issuing comment letters if the filings are deficient. Research shows that the SEC’s comment letter review pressures companies to disclose material firm-specific risks in their SEC filings (Johnson 2010; Bozanic, Dietrich, and Johnson 2015). Recent research also documents lower bid-ask spreads and higher earnings response coefficients following SEC comment letter resolution (Johnston and Pettachi 2015). Second, stakeholders continue to pressure firms—via a flurry of shareholder resolutions—and to demand the SEC to enforce disclosures of material CCR (EY 2015; Coburn and Cook 2014; Gelles 2016; Hulac 2016; Ceres 2007). As discussed earlier, ExxonMobil’s shareholders recently filed a class-action lawsuit against the firm due to its refusal to disclose its oil reserves as stranded assets (Hasemyer 2016).

Based on the above discussion, if managers assess CCR as material to the firm and view the regulation regarding these disclosures as strongly enforced (e.g., through the SEC’s periodic review of registrants’ filings), then they will comply with mandatory disclosure under Regulation S-K (see Figure 1, box 5). Disclosing (not disclosing) signals that managers assess climate change as a material (not material) risk to the firm. Therefore, we expect that firms disclosing CCR will have higher COE than non-disclosing firms to compensate investors for material CCR. Managers View Disclosing Material CCR as Essentially Voluntary

Despite mounting pressure from regulators and investors, managers may perceive SEC regulation as weakly enforced. Although the SEC issued interpretive guidance on reporting CCR, related legislation on cap-and-trade that registrants had anticipated was ultimately not enacted. This led some public companies to view enforcement of CCR disclosures in general as a lower priority for the Commission (GAO 2016, 21).11 _{Indeed, the SEC has issued only a small number}

of CCR-related comment letters (Coburn and Cook 2014, 5). In 2010 and 2011 combined, the SEC issued only 49 comment letters specifically addressing these disclosures, while they issued only three such comment letters in 2012 and none in 2013 (Coburn and Cook 2014, 5). Some parties have interpreted the lack of CCR-related SEC comment letters as indicative of the SEC not enforcing CCR disclosure regulation (Gelles 2016).

If managers assess CCR as material to the firm but perceive the regulation regarding these disclosures as weakly enforced, then they will view disclosing material CCR as essentially voluntary. This will likely trigger an analysis of the benefits versus the costs of disclosing

11 _{According to the SEC staff, the priorities of the Commission changed after the 2010 Guidance was issued. As a} result, the Commission’s Investor Advisory Committee, which was charged with making recommendations regarding climate-related disclosures as part of its overall regulatory mandate, was disbanded shortly after the Guidance became effective. Instead, the SEC’s priorities and limited resources moved to the Dodd-Frank Act and the JOBS Act (GAO 2016, 21; Cheney 2012).

material CCR (see Figure 1, boxes 3 and 4). The costs of disclosing CCR include the deleterious effects of revealing proprietary information (Verrecchia 1983) and CCR-related supply chain risk. The benefits of disclosing CCR include avoiding potential climate change-related lawsuits (McCann 2016; Olson and Viswanatha 2016; Hasemyer 2016).12 Thus, if managers conclude that the perceived benefits of disclosing material CCR outweigh the perceived costs, then they will choose to disclose (see box 4). Otherwise, managers will choose to not disclose, even if they assess CCR as material (Figure 1, box 3).

If managers view disclosing material CCR as essentially voluntary, consistent with the voluntary disclosure literature (Healy and Palepu 2001; Botosan 2000, 1997; Verrecchia 1983), a perceived benefit of disclosure is a potential decrease in the firm’s COE. Research on voluntary disclosures of corporate social responsibility (CSR) reports documents that firms that issue CSR reports experience a decrease in their COE if the firms show superior CSR performance

(Dhaliwal et al. 2011). Voluntary disclosures are also used to reduce potential regulatory intervention (Blacconiere and Patten 1994). If managers view disclosing material CCR as essentially voluntary, then disclosing (not disclosing) signals that managers view the benefits of disclosing as greater (lower) than the costs of disclosing (boxes 4 and 3, respectively). Based on these arguments, we expect that firms that disclose material CCR will have a lower COE than non-disclosing firms.

Disclosing Nonmaterial CCR is Voluntary

Much like boxes 3 and 4 in Figure 1, boxes 1 and 2 reflect the results of managers

evaluating the perceived benefits of disclosing relative to the perceived costs of disclosing if they

12 _{Managers’ decisions whether or not to disclose CCR may be unrelated to their assessments of the materiality of} CCR. For example, a decision to not disclose may be due to the fact that the firm has neither the resources nor the systems in place to measure and report on CCR and its effects on a firm’s operations and cash flows. As discussed in Section IV, we control for these other factors to rule them out as alternative explanations for our findings.

assess CCR as not material to the firm. Disclosing (not disclosing) implicitly signals that managers view the benefits of disclosing as greater (lower) than the costs of disclosing (boxes 2 and 1, respectively). Again, consistent with the voluntary disclosure literature (Healy and Palepu 2001; Botosan 2000, 1997; Verrecchia 1983), a perceived benefit of disclosure is a potential decrease in the firm’s COE. Based on these arguments, we expect that firms that disclose CCR will have a lower COE than firms that do not disclose CCR.

The above competing arguments lead to our first hypothesis:

H1: The COE of firms that disclose CCR in Form 10-K is different from the COE of firms that do not disclose CCR in Form 10-K.

Our hypothesis may not obtain if the market considers that firms’ voluntary CCR disclosures through non-SEC mechanisms are sufficiently informative to investors.

Alternatively, the market may view CCR disclosures as mandatory but boilerplate in nature (Merkl-Davies and Brennan 2007). In both cases, managers’ decision to disclose CCR may provide no incremental information to investors about firm risk. In addition, if CCR is a diversifiable risk (Sharpe 1964; Lintner 1965), then there will be no association between disclosing CCR and COE.

The above discussion highlights the importance, both theoretically and empirically, of recognizing that disclosing firms may be systematically different from non-disclosing firms. Both economic theory (Akerlof 1970) and voluntary disclosure theory (Beyer et al. 2010) posit that, if disclosure is voluntary, then managers choose to disclose when the benefits of disclosing outweigh the costs of disclosing. This underscores the importance of correcting for self-selection when estimating disclosure models. Therefore, using data from disclosing firms to draw

inferences about non-disclosing firms without adjusting for the systematic differences between them can give rise to biased coefficients, and thus, erroneous conclusions.

Inter-Industry Materiality Differences

Our first hypothesis examines the association between investors’ inferences regarding managers’ CCR materiality assessments (which are unobservable), their CCR disclosure decisions (which are observable), and firms’ COE. Both the SEC and the FASB recognize that materiality is context specific, varying greatly with the nature of business. The Sommer Report (1977, 340) specifically discusses differences in materiality of information across industries and states that “… disclosures material to one industry should not be required for other industries as to which they are not applicable.” We draw on prior research examining the differences in materiality of information across different types of firms to probe deeper into the association between managers’ decisions whether to disclose CCR and firm risk.

Cheng, Liao, and Zhang (2013) find that smaller reporting companies that chose to continue disclosing certain non-financial information in SEC filings after a mandatory-to-voluntary regime shift by an SEC rule experienced an increase in market illiquidity. However, the increase in illiquidity was even larger for firms that discontinued disclosing this information. The authors argue that the association between the choice to disclose and market illiquidity depends on the materiality of the potentially reduced information. They further reason that material information provided in firms’ SEC filings may be especially useful to smaller reporting companies’ investors because, relative to larger firms, these companies have a poor information environment, including lower analyst following and media coverage. The findings from Cheng et al. (2013) point to the important role of the materiality of nonfinancial disclosures for smaller companies’ investors, but do not address the materiality of such disclosures for investors of larger companies.

Christensen et al. (2016) examine reporting requirements in mining companies. The Dodd-Frank Act of 2010 requires mining companies to disclose in Form 10-K their mine health and safety records, information which is uniquely material to this industry. The authors find a lower incidence of mining-related citations and injuries for disclosing firms relative to non-disclosing firms, even though these records are already publicly available elsewhere. The authors reason that investors may perceive managers’ decisions to disclose mine safety records in SEC filings as an implicit signal of that information’s materiality. In addition, disclosing reduces investors’ cost of gathering this information.

To our knowledge, the Khan et al. (2016) study is the first to examine inter-industry differences in the materiality of ESG issues for investors. Using the newly-available SASB Materiality Map™_{, they hand-map sustainability investments to independent ratings of firms’} ESG performance (specifically, KLD ratings) to measure investments on material and immaterial ESG issues for each of their sample firms across 45 industries.13 _{Importantly, SASB’s}

Materiality Map™ _{relies on the Supreme Court’s definition of materiality. Khan et al. (2016)} report that firms with strong ratings on material ESG issues have better future accounting performance than firms with inferior ratings on the same issues. In contrast, firms with strong ratings on immaterial ESG issues do not outperform firms with poor ratings on these same issues. Further, firms with strong ratings on material ESG issues and concurrently poor ratings on immaterial ESG issues have the best future accounting performance. The authors conclude that materiality guidance enhances the informativeness of ESG data for investors.

13 _{KLD statistics (currently available in the MSCI database in WRDS) provide firm-level ratings on an array of over} 50 sustainability issues and rank firms’ performance on those issues. This database and SASB’s Materiality Map™ are discussed further in the next section.

The above studies indicate that the relationship between firms’ decisions whether to disclose CCR and COE will likely vary depending on report users’ judgments regarding the materiality of CCR across industries. Based on these arguments, our next hypothesis examines the role of materiality on the association between disclosing CCR and COE:

H2: The association between disclosing CCR in Form 10-K and COE is stronger for firms where users judge such disclosures as material than for firms where users judge such disclosures as not material.

IV. RESEARCH DESIGN Sample and Data

We obtain our sample from the intersection of the S&P 500 index firms and the Ceres and CDP databases for the period 2008 to 2014. In order to minimize changes in our sample over this period we use firms that were included in the S&P 500 index on December 31, 2008. We hand-collect data on whether or not firms disclose CCR in Form 10-K from Ceres’ SEC sustainability disclosure search tool.14 _{The tool searches the text of SEC annual filings of S&P}

500, Russell 3000, and FT Global 500 firms and identifies the relevant issue of the disclosure (e.g., climate change risk, water risk). We choose 2008 as the initial year of our analyses because Ceres’ database provides SEC filings starting in fiscal year 2008. The last year of our analyses is 2014 because that is the last year for which CDP climate change data are publicly available.15

To proxy for CCR materiality based on users’ judgments, following Khan et al. (2016) we use SASB’s Materiality Map™ to identify the materiality of CCR on an industry-by-industry basis. To identify whether an issue is judged to be material for companies in a given industry, SASB gathered input from a panel of over 200 industry experts and SASB staff. The panel scored

14 _{Available at http://ceres.org/resources/tools/sec-sustainability-disclosure.}

15 _{Although 2014 is the last year for which CDP climate change data is publicly available, we are able to obtain data} for 2015 from Ceres. In robustness tests we examine the sensitivity of our results to extrapolating the firms’ participation in the CDP survey for 2015 using 2014 data.

sustainability issues based on three components: evidence of investor interest, evidence of financial impact, and forward-looking impact (see Appendix A for further details). We use the Materiality Map™ _{scoring on two sustainability issues directly related to CCR, namely (1) GHG} emissions, and (2) environmental and social impacts on assets and operations, to classify each sample firm as in an industry where users judge CCR as either material or not material to investors.

We collect data on our sample firms’ participation in the CDP climate survey to control for voluntary disclosures of CCR information through channels other than the SEC filings. The CDP survey elicits voluntary information on, for example, climate change risks and

opportunities, carbon emissions in metric tons, emission reduction targets, and managerial compensation. CDP does not mandate independent assurance on the data.

Table 1 provides our sample selection criteria. We start with all S&P 500 firms available in the Ceres and CDP databases from 2008 to 2014. The result is 3,226 firm-year observations (496 unique firms). We lose 227 firm-year observations for which we are unable to calculate our COE measure. This is because we exclude firms with negative book value of equity or negative earnings forecasts for years one and two, or we are unable to obtain analyst forecasts for these firms. The sample is further reduced by three observations for unavailable Compustat data, resulting in a final sample of 2,996 firm-year observations (465 unique firms) for Hypothesis 1 tests. We further exclude 49 firm-year observations that are missing a 4-digit SIC code needed to match with SASB’s industry codes for user-based materiality classification. Thus, our final sample for Hypothesis 2 tests consists of 2,947 firm-year observations (458 unique firms).

Descriptive Statistics

Figure 2, Panel A provides the percentage of firms that disclosed CCR information and the percentage of firms that participated in the CDP climate survey from 2008 to 2014. In 2008, less than half of the firms (46.2 percent) disclosed CCR information. Notably, that percentage increased almost ten percentage points from 2008 to 2009, and a further five percentage points in 2010. These increases make intuitive sense, as the years coincide with the issuance of the SEC’s 2010 interpretive guidance on climate change disclosures, which became effective in February 2010. There was a steady growth in the percentage of firms disclosing CCR until 2012, but the growth then tapers off. In 2014, almost two-thirds of the firms disclosed CCR information. Figure 2, Panel A also shows growth in the firms’ participation in the CDP climate survey, from 58 percent in 2008 to 67 percent in 2014.

Figure 2, Panel B shows percentages of firms that disclosed CCR, partitioned by user-based (SASB) materiality. From 2008 to 2014, the number of CCR disclosers for both the material and not-material groups grew by 20 percentage points. Over the same period, the

percentages of CCR disclosers are consistently higher, by an average of 20 percentage points, for the material-CCR group relative to the not-material-CCR group.

| Insert Figure 2 about here |

Panel A of Table 2 shows that, averaged over our sample period, 60 percent of the firms disclosed CCR and 65.2 percent participated voluntarily in the CDP climate survey. Further, while 40.5 percent both responded to the CDP climate survey and disclosed CCR (cell 4), about 15 percent neither responded to the CDP climate survey nor disclosed CCR (cell 1). Notably, almost 25 percent responded to the CDP climate survey but chose to not disclose CCR (cell 3).16

16 _{The null hypothesis of independence between disclosing CCR information in Form 10-K and participation in the} CDP climate survey is rejected (Chi-square = 9.634; p < 0.01).

This is counter-intuitive, since these firms have voluntarily committed scarce resources to respond to the CDP survey (and some firms also provided independent assurance on this information), and yet they chose to not disclose CCR. Panel B of Table 2 shows materiality as judged by users (i.e., based on SASB’s panel of experts), partitioned by whether firms disclosed CCR. Averaged over the seven-year period, the majority of firms in our sample (61.4 percent) belong to industries where users judge CCR as not material.

| Insert Table 2 about here |

Table 3 shows the sub-samples of firms that participated in the CDP climate survey (Panel A) and those that did not participate (Panel B), partitioned by users’ materiality judgments and by whether firms disclosed CCR. Notably, both panels show that the majority of firms disclosed CCR, regardless of whether they participated in the CDP climate survey.

| Insert Table 3 about here | Empirical Models and Variable Definitions

As discussed earlier, using data from disclosing firms to draw inferences about non-disclosing firms without adjusting for the systematic differences between them can give rise to biased coefficients, and thus, erroneous conclusions. This is likely the case in Griffin, Lont, and Sun (2017), who use the GHG emissions of the disclosing firms to estimate the GHG emissions of the non-disclosing firms. This method incorrectly treats the non-disclosing firms as if they were identical to the disclosing firms, thus assuming away self-selection. Thus, Griffin et al.’s puzzling finding—the market penalizes firms that choose to voluntarily disclose their GHG emissions—runs counter to both economic and voluntary disclosure theories and leaves

unanswered the question, “why would firms choose to voluntarily disclose their GHG emissions if they are penalized by the market for the act of disclosing?”

Following Matsumura et al. (2014), we correct for self-selection using propensity score matching to compare the COE of the firms that disclose CCR with the COE of non-disclosing firms (H1). Further, we examine the COE differences between disclosers and non-disclosers after partitioning by user-based CCR materiality judgments based on SASB’s panel of experts (H2). Implied COE is the internal rate of return that equates the current stock price to the present value of all expected future cash flows to equity. This rate is an ex-ante estimate of the COE, given market expectations about future growth. Specifically, the value of the firm at time t is expressed as:

1

where Ptis the market value of common equity on the date of the earnings forecast at time t from the daily CRSP files, FCFEt+iis free cash flow to equity at time t + i, and reis the implied COE.

We rely on prior accounting and finance research (e.g., Hail and Leuz 2009; Hann, Ogneva, and Ozbas 2013) to estimate the implied COE. COE, our measure of implied COE, is a composite COEconstructed using the median of four measures: Easton’s (2004) price earnings growth (PEG) model, Gebhardt et al. (2001) (GLS), Claus and Thomas (2001) (CT), and the price-earnings ratio.17_{The four models differ in the assumptions made to forecast expected} future cash flows. We follow Hann et al. (2013) in operationalizing these models.

Following prior research, we use median analyst forecasts as our proxy for FCFE.

Analyst forecasts for year 1 correspond to the fiscal year that ends after the forecast date. That is, if the first-year analyst forecast (year 1 in I/B/E/S) is for the previous year because the earnings

17 _{This is consistent with prior research that aggregates various measures to calculate a composite COE measure} (see, e.g., Hail and Leuz 2009). Aggregating across measures reduces the idiosyncratic errors that may be present in any single measure.

for the previous year have not yet been announced, we do not use that forecast. Instead, we use the second-year forecast, which is the forecast for the current fiscal year, as the year 1 forecast. In residual earnings models such as CT and GLS that require an estimate of book value, we use the book value at the end of the prior year (beginning of current year). Since the first forecast is only for part of the year, we discount only for the proportionate number of days remaining through the year end.

Prior studies retain only one earnings forecast per year (e.g., Hail and Leuz 2009; Hann et al. 2013). Unlike these other studies, we retain all earnings forecasts made during the year for each firm to calculate the COE numbers used in our composite measure. Prior research shows that analyst forecasts tend to exhibit an upward bias earlier in the fiscal year, but are then revised downwards over the year, and finally exhibit a downward bias at earnings announcement

(Richardson, Teoh, and Wysocki 2004). Such biases in analyst forecasts can lead to systematic biases in COE calculations (Easton and Sommers 2007). Using all available forecasts reduces this bias as well as any errors that may arise in the COE measure from errors in the retained forecast. We take the median of all the COE numbers for each measure for each firm-year. We then take the median across the four measures to calculate our composite COE measure for each fiscal year for each firm. In robustness analyses we also aggregate the four measures using their means, rather than medians, to calculate the composite COE.

Propensity Score Matching

We use propensity score matching (Rosenbaum 2005) to compare the COE of the firms that disclose CCR with the COE of the non-disclosing firms. We use the probit model in Equation (1) to calculate the propensity scores:

DISC_10K =



0 +



1BETA +



2BM +



3SIZE +



4FI/PI +



5ROA +



6EXCH

+



7STRNG +



8CNCRN +



9CDP +



(1)

where DISC_10K is an indicator variable that is coded 1 if the firm discloses CCR information in Form10-K in year t, and 0 otherwise. All independent variables, discussed below, are measured contemporaneously.

We match the disclosers with the non-disclosers on the Fama-French three factors: market beta (BETA), book-to-market ratio (BM), and firm size (SIZE). BETA is the correlation between firm-specific returns and market returns. We use monthly returns for the firm and the CRSP value-weighted index for the market returns. We calculate betas using returns for the five years prior to and including fiscal year t, but require a minimum of ten months of data. For firm-years with fewer than ten months of data, we substitute the mean beta for the firm as the beta for that fiscal year.18 Following Francis, Nanda, and Olsson (2008), we predict a positive association between BETA and DISC_10K. We control for firm growth by including the firm’s book-to-market ratio (BM), measured as the book value of common equity divided by the market value of common equity at the end of the fiscal year. Because larger firms are more likely to provide more environmental disclosures (Stanny 2013; Matsumura et al. 2014), we include the log of firms’ total assets as our proxy for SIZE.

International product market interactions affect environmental disclosures (Matsumura et al. 2014; Khanna, Palepu, and Srinivasan 2004; Stanny and Ely 2008), and EU firms with higher proportions of international sales are more likely to provide CCR disclosures. Therefore, to control for international product market interactions, we include annual pre-tax foreign income as a proportion of total pre-tax income (FI/PI) and expect a positive coefficient for this variable.

Consistent with prior research that documents a positive association between firm performance and disclosures (e.g., Miller 2002), we expect a positive coefficient on our measure of firm performance, ROA, measured as income before extraordinary items divided by total assets.

Firms choose the exchange on which to list their securities and this choice is a function of both firm-level characteristics and the exchange’s listing requirements, including disclosure requirements (Corwin and Harris 2001). Therefore, we also match firms on the stock exchange (EXCH) on which they trade. In general, larger and older firms are more likely to list on the NYSE, but since the vast majority of our sample firms (80 percent) are listed on the NYSE (the remaining firms trade on NASDAQ) and are likely to be among the largest global firms, we do not predict a sign on EXCH.

Empirical evidence indicates that firms that are more environmentally proactive are more likely to disclose environmental information (Matsumura et al. 2014). Thus, similar to

Matsumura et al. (2014), we control for the firms’ environmentally proactive performance ratings, measured as STRNG, and for their environmentally damaging actions ratings, measured as CNCRN, to proxy for the firms’ environmental performance. We collect environmental performance ratings data using the KLD database. Consistent with prior research (Cho et al. 2012; Matsumura et al. 2014) we do not aggregate STRNG and CNCRN because KLD’s proactive dimensions are distinct from the damaging dimensions. Similar to Matsumura et al. (2014), we expect a positive coefficient for STRNG, and do not predict a sign for CNCRN. If the KLD score is missing for an observation, we set it equal to zero.

To address the possibility that firms may be providing CCR information through channels other than Form 10-K, we include an indicator variable, CDP. If, according to CDP, the firm participated in the CDP climate survey and the response is publicly available in that year (i.e.,

CDP response status is AQ, AQ(L), or AQ(SA)), then we code the firm as 1, and 0 otherwise.19 To test H2, we classify each sample firm as in an industry where users (i.e., SASB’s panel of experts) judge CCR as either material (coded = 1) or not material (coded = 0).

V. RESULTS Descriptive Statistics

Table 4 provides summary statistics for the variables in Equation (1). We winsorize all continuous variables at the one percent level on both tails of the distribution. Panel A of Table 4 shows that the mean (median) COE is 8.14 percent (8.05 percent).20 _{The firms’ mean (median)}

BETA is about 1.15 (1.07), which is consistent with the relatively low risk of S&P 500 firms in general. The firms’ mean (median) BM is 0.522 (0.423), indicating that on average, the firms are healthy and have growth opportunities. For a few firms, foreign income represents a large proportion of their total income. The mean FI/PI is 30.2 percent, although the median is only 12.1 percent. The first three quartiles of the EXCH variable are 1. This reflects the composition of our sample, whereby 2,417 firm-years (80.7 percent) trade on NYSE (coded = 1), and 19.3 percent trade on NASDAQ (coded = 3) (untabulated).21 _{The mean STRNG and CNCRN is 1.021}

and 0.454, respectively. Finally, about 65 percent of the firms participated in the CDP climate survey and allowed their responses to be publicly available.

Panel B of Table 4 shows summary statistics and univariate tests for the variables in

19 _{CDP uses the following response status legend: AQ: Answered the survey; AQ(L): Answered the survey late;} AQ(SA): Answered the survey but the company is a subsidiary or has merged; NP: Answered the survey but the response is not publicly available; IN: Information provided; DP: Declined to participate; NR: No response; X: the company did not fall into the CDP sample that year.

20

Damodaran (2015) estimates an average risk premium of 2.62 percent over the 2008−2014 period for S&P 500 firms using the dividend discounting (DD) model, and 5.50 percent using the free cash-flows-to-equity (FCFE) approach. With an average risk-free rate of 2.60 percent over this period, this translates into a COE of 5.22 percent and 8.10 percent for the DD and FCFE approaches, respectively.

21 _{Two-thirds of the firms listed on the NYSE disclose CCR information in Form 10-K; in contrast, 37 percent of the} firms listed on NASDAQ disclose this information in Form 10-K.

Equation (1), partitioned by whether the firms disclose or do not disclose CCR (DISC_10K = 1 and DISC_10K = 0, respectively). In general, except for FI/PI, the disclosers are significantly different from the non-disclosers. Both the mean and median COE are significantly higher for the disclosers than for the non-disclosers (p < 0.05 and p < 0.10, respectively). Although both the mean BETA and BM are higher for the disclosers (p < 0.05), the median BETA is not

significantly different between disclosers and non-disclosers. The significantly higher mean BETA and BM for the disclosers suggests that, in general, these firms are riskier on these

dimensions and therefore may have a higher COE than the non-disclosers. The mean and median SIZE are significantly higher for the disclosers than for the non-disclosers (p = 0.00). Contrary to expectation, the mean and median ROA are higher for the non-disclosers than for the disclosers (p = 0.00). Taken together, our univariate results reinforce the importance of correcting for self-selection. That is, as discussed earlier, using data from the disclosing firms to draw inferences about the non-disclosing firms, without first correcting for these differences, will likely lead to biased coefficients and thus, erroneous conclusions.

Panel C of Table 4 shows summary statistics for the variables in Equation (1), partitioned by user-based (SASB) materiality judgments. The median COE is higher for firms in the material CCR group than those of firms in the not-material CCR group, but the difference in means is not significant. The material CCR firms also have higher BM and are larger than the not-material CCR firms, but have lower ROA. Further, material CCR firms also have higher STRNG and CNCRN scores.

| Insert Table 4 about here |

Table 5 presents correlation coefficients for the variables in Equation (1). The tables show Pearson and Spearman rank correlations below and above the diagonal, respectively. COE

is positively correlated with both DISC_10K (mandatory disclosure) and CDP (voluntary disclosure) (p < 0.10). Further, COE is correlated with all the other variables in our regression model (p < 0.01 or better), except FI/PI. The signs for all the correlations are as expected, except for the positive correlation between COE and SIZE (Spearman rank = 0.243; p < 0.01). This result is consistent with Dhaliwal et al. (2011) and may be due to our sample firms (drawn from the S&P 500 index), which are among the largest in the world.22DISC_10K is significantly correlated with both STRNG and CNCRN, consistent with our descriptive statistics in Panels B and C of Table 4. Interestingly, the correlation between DISC_10K and CDP, although highly significant, is small (0.057, p < 0.01).

| Insert Table 5 about here | Hypothesis 1 Tests

Table 6 presents the results of Equation (1) matching the firms that disclose CCR in Form 10K (DISC_10K = 1) with those that do not (DISC_10K = 0) on various firm-level

characteristics (Panel A), and our tests of H1 to examine the COE effect of disclosing vs. not disclosing CCR after propensity score matching (PSM) (Panel B). Panel A shows that, of the total 2,996 firm-year observations, we are able to match 2,966 observations: 1,770 disclosers matched with 1,196 non-disclosers. We are unable to match 30 disclosers. Before matching, the two groups of firms were significantly different on all but one of the firm characteristics included in Equation (1) (see Table 4, Panel B). After matching, only four firm-level variables remain significantly different between the two groups, BM and SIZE (at p < 0.05), and STRNG and CDP (at p < 0.01) (Table 6, Panel A, Covariate Balance).

| Insert Table 6 about here |

22 _{See also Easton (2007) for a discussion of assessing the validity of COE measures using associations or} correlations with other known risk factors, such as BETA and SIZE.

Panel B of Table 6 shows the t-tests of differences in the COE of matched disclosers versus non-disclosers. The difference in COE is positive and significant (p < 0.05); that is, the COE of the disclosers is higher than the COE of non-disclosers before matching. However, after matching, the COE for the disclosers is lower than that of the non-disclosers, but the difference is not statistically significant (p > 0.10).

As discussed above, even after propensity score matching, our matched sample is

significantly different on four dimensions. Further, the standard errors from the PSM may not be unbiased. Therefore, to remove any residual misspecification that may remain after matching, we estimate a doubly robust regression (Imbens and Wooldridge 2007), clustering the standard errors on firm identifier (Permno). Panel C of Table 6 shows that the difference in COE between the DISC_10K = 1andthe DISC_10K = 0firms is negative and significant (p < 0.05): the COE of disclosers is approximately 21.3 bps lower than the COE of the non-disclosers, thus rejecting our null hypothesis (H1) of no difference between the COE of disclosers and non-disclosers. Hypothesis 2 Tests

Our tests of H2 examine the role of CCR materiality, as judged by users (i.e., SASB’s panel of experts), on the association between disclosing CCR and COE. The PSM results in Table 7, Panel A show that the matched sample for the material CCR firms has differences along the three risk dimensions, BETA, BM, and SIZE, as well as the two environmental performance measures, STRNG, and CNCRN. We are able to match 1,095 firm-year observations (out of the total 1,138): 809 disclosers to 286 non-disclosers. We are unable to match 43 disclosers.

Panel B of Table 7 shows the tests of differences in COE between matched disclosers and non-disclosers, partitioned by user-based (SASB) materiality. For the matched sample of the material CCR firms (SASB_MTRL=1), the COE of DISC_10K = 1 firms is lower than the COE of

DISC_10K = 0 firms, but the difference is not significant (p > 0.10). However, the doubly robust regression results in Panel C show that, for the material CCR group, the difference in COE between the disclosers and non-disclosers is negative and significant (p < 0.05): the COE of disclosers is 49.1 bps lower than the COE of non-disclosers.

Next, we discuss the results for the not-material CCR firms (SASB_MTRL=0). Panel A of Table 7 shows that the matched sample of 1,793 firms, 912 disclosers and 881 non-disclosers, differs along three dimensions after matching: BETA, ROA, and STRNG. We are not able to find matches for 16 disclosers. Panel B of Table 7 shows that, for the not-material CCR group of matched firms, the COE of disclosers is higher than the COE of non-disclosers, but the difference is not statistically significant (p > 0.10). Similarly, the doubly-robust regression results (Panel C, Table 7) show no statistical difference in the COE of disclosers versus non-disclosers for the not-material CCR group. Taken together, our results support H2.

| Insert Table 7 about here |

In summary, our H1 results are consistent with lower COE for firms that disclose CCR, compared to firms that do not disclose CCR. In addition, our H2 results indicate that disclosing CCR is associated with lower COE only for firms in industries where users judge CCR as material. For firms where users judge CCR as not material, we find no association between disclosing CCR and COE. Overall, our results indicate that, on average, investors impose a risk premium on firms that do not disclose CCR in their 10-K filings. However, after partitioning the sample on materiality of CCR from the users’ perspective, we find that this risk premium exists only for firms where users judge CCR as material.

Sensitivity and Robustness Tests

Prior research finds that firms with better corporate governance have higher firm value and stock returns (Gompers, Ishii, and Metrick 2003). To control for the effects of corporate governance on COE, we construct a variable, CGOV, to proxy for firms’ climate-change governance measures. We obtain corporate governance data from Bloomberg on three separate dimensions: Does the firm have: (1) a climate change policy; (2) a climate change committee; and (3) incentives tied to climate change management? We code each dimension as equal to one if the firm answers “yes,” and zero otherwise. We add the scores on the three questions to construct the CGOV variable.23 _{Tables 8 and 9 show our results for the full sample, and broken}

down by materiality, respectively. Our doubly robust regression results are consistent with our main results. After matching on all firm-level variables, including corporate governance, we find a negative association between disclosing CCR and COE for the full sample (Table 8, Panel C), and for firms where users judge CCR as material (Table 9, Panel C).

We also test H1 and H2 after including industry fixed effects in our models (untabulated). We use the Fama-French five-industry classification for industries. Although we are able to find matches for more observations for the full sample, we are unable to match on six of the nine firm-level variables. Our results remain unchanged. The COE coefficient for the full sample in the doubly robust regression shows that the COE for disclosers is 18.3 bps lower than the COE for non-disclosers (p < 0.05). Our results after partitioning on user-based materiality judgments also remain unchanged. For firms in the CCR material group, the COE of disclosers is 73.7 bps lower than the COE of non-disclosers, and the difference is significant (p < 0.01). In contrast, for

23_{The breakdown of the scores (untabulated) for our 2,996 observations is: 0 (42 percent), one (16 percent), two (24} percent) and three (18 percent).

firms in the CCR not-material group, we find no significant difference in the COE of disclosers versus non-disclosers.

Although our hand-collected data on firms’ CCR disclosures includes 2015, the time period for our main analyses ends in 2014 because we do not have 2015 data on firms’

participation in the CDP climate survey. However, firms’ participation in the survey is sticky; that is, once a firm participates in the CDP survey, it is likely to continue to do so in subsequent years. In our sample period, less than 10 percent of the firms change their reporting status from one year to the next. In addition, the correlation between CDP reporting status in 2013 and 2014 is 0.85 (p < 0.01). Consequently, we test H1 and H2 by extrapolating firms’ CDP reporting status for 2015 using CDP 2014 data (untabulated). Our sample size increases to 3,395 firm-year observations (i.e., an increase of 399 observations relative to our main results), of which we are able to match 3,376 observations (2,045 disclosers to 1,331 non-disclosers). The results from the doubly robust regressions are stronger relative to our main results. The COE of disclosers is 24.4 bps lower than that for non-disclosers (p < 0.01). For firms in the material CCR group, we are able to match 927 disclosers with 316 non-disclosers. The doubly robust regression results show that the COE for the disclosers is 54.6 bps lower than the COE for non-disclosers, and this difference is significant (p < 0.01). For firms in the not-material CCR group, the difference in COE between disclosers and non-disclosers is not significant.

In our next sensitivity analyses, we look at changes in whether CCR is disclosed in 10-K’s (untabulated). The results of these analyses need to be interpreted with caution since only about 5 percent of our sample firms (i.e., about 155 observations) change their disclosure practices. We find that firms which start disclosing CCR experience a decline in COE, but the coefficient is not statistically significant. However, firms that stop disclosing CCR experience an

increase in COE for the full sample and for firms where users judge CCR as material (p < 0.05). Our results are not significant for non-material CCR firms.

Next, instead of matching on firm performance using ROA, we match on whether a firm suffered a loss during the year (untabulated). We include an indicator variable equal to 1 if the firm reported negative income before extraordinary items during the year, and 0 otherwise. Our results are inferentially similar to our main results. Finally, we calculate implied COE as the average of the four COE measures, instead of the median of the four measures (untabulated). Our results are inferentially similar to our main results.

VI. CONCLUSION

We examine the association between managers’ decisions whether to disclose CCR in Form 10-K and firm risk, as measured by COE, a composite implied cost of equity measure using the median of four measures suggested by the accounting and finance literatures. We exploit two key institutional factors that are central to, and motivate our research question: (1) there is little consensus on whether CCR is material to the firms; and (2) the SEC has

inconsistently enforced federal regulation to disclose CCR across firms. These factors, along with managers’ unobservable evaluations of the costs and benefits of disclosing versus not disclosing CCR create uncertainty about whether the requirement to disclose CCR is voluntary or mandatory. This hinders investors’ ability to disentangle whether managers’ failure to disclose CCR is either deliberately intended to conceal useful but adverse information, or an

acknowledgement that CCR is not a material risk.

Using a hand-collected sample of 2,996 firm-year observations of S&P 500 firms’ choices of whether to disclose CCR for years 2008 to 2014, we examine the difference in COE for firms that disclose versus those that do not disclose CCR. We also collect data on the firms’

voluntary participation in the CDP climate survey to control for voluntarily CCR disclosures.We find that the COE of disclosers is significantly lower, by 21.3 bps, than the COE of

non-disclosers. This indicates that, on average, investors consider CCR to be a material risk and impose a risk premium on non-disclosers.

Next, we examine whether the relation between disclosing CCR and COE is different for firms where users judge CCR to be material versus firms where users do not judge CCR to be material. We find that, for firms where users judge CCR as material, the COE is 49.1 bps lower for disclosers relative to non-disclosers. In contrast, we find that disclosing vs. not disclosing CCR is not associated with the COE for firms where users judge CCR as not material.

Our findings highlight the importance of incorporating both the materiality of disclosures and the strength of the regulatory enforcement of these disclosures in studies that examine

mandatory disclosures and investors’ inferences based on the disclosures. In our setting, although regulation unambiguously mandates disclosing material CCR, the uncertainty surrounding both the materiality of CCR and the strength of the regulatory enforcement result in investors

appearing to interpret managers’ decisions to disclose CCR as voluntary rather than mandatory. As either the ambiguity regarding materiality of CCR is resolved or the SEC’s enforcement of the regulation changes, future research could exploit the changes to disentangle the effects of enforcement from materiality on choice to disclose CCR.

Our findings also support the argument that equity investors are increasingly factoring CCR into their investment decisions, and point to the greater impetus to disclose CCR. The higher COE for non-disclosing firms–limited to firms where users consider CCR to be material– also underscores the need for managers to assess the materiality of CCR more carefully because disclosing CCR is beneficial only for firms where users judge this information as material. Also,

our results suggest that investors may be able to look past managers’ efforts to “greenwash” because we do not find any COE benefits of disclosing CCR for firms where users do not judge CCR to be a material risk.

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Cost-of-Equity Effects of Decision to Disclose Climate-Change Risk in Form 10-K:

Breakdown of Sample by User-Based (SASB) Materiality Judgments

Panel A: Probit Regression Model for Propensity Score Matching

a

 

SASB_MTRL = 1 (Material)

SASB_MTRL = 0 (Not

Material)

D.V. is DISC_10K

Estimates

Covariate Balance

Estimates

Covariate Balance

Variable Coeff Z-stat

DISC_10K = 1

DISC_10K

= 0 t-stat Coeff Z-stat

DISC_10K = 1

DISC_10K

= 0 t-stat

BETA 0.1147 1.29 1.1356 1.1820 -1.77 * 0.1329 ** 2.22 1.1835 1.1182 2.34 **

BM -0.0471 -0.34 0.6029 0.5065 5.54 *** -0.2841 *** -2.92 0.4795 0.4798 -0.02

SIZE -0.1434 *** -3.62 9.9000 9.5936 4.87 *** 0.1751 *** 6.64 9.8489 9.8532 -0.07

FI/PI 0.1964 * 1.89 0.2173 0.2227 -0.23 0.0035 0.06 0.3563 0.3779 -0.82

ROA -0.2484 -0.27 0.0387 0.0389 -0.06 -0.6083 -1.17 0.0602 0.0659 -1.89 *

EXCH -0.5255 *** -7.69 1.1162 1.0890 1.24 -0.2142 *** -5.82 1.3224 1.3092 0.39

STRNG -0.0151 -0.38 1.0952 0.9703 1.89 * 0.0624 ** 2.28 1.1272 1.2445 -1.87 *

CNCRN 0.4945 *** 8.26 0.8826 0.7553 2.17 ** 0.2564 *** 4.06 0.2763 0.2818 -0.19

CDP -0.1504 -1.45 0.6514 0.6700 -0.79 0.0288 0.42 0.6897 0.7061 -0.76

n (Total) 1,138 1,809

n (DISC_10K = 1) 809 912

n (DISC_10K = 0) 286 881

n (Matched) 1,095 1,793

Pseudo-R2 0.1837 0.0683

 

Breakdown of Sample by User-Based (SASB) Materiality Judgments

a

Panel B: Difference in COE of Propensity-Score-Matched Firms

b

 

SASB_MTRL = 1 (Material)

SASB_MTRL = 0 (Not Material)

DISC_10K

= 1

DISC_10K

= 0

Diff.

t-stat

DISC_10K

= 1

DISC_10K

= 0

Diff.

t-stat

Pre-matching 0.0821 0.0828

-0.0007

-0.39

0.0835 0.0802

0.0033

2.98 ***

Post-matching

0.0814

0.0845

-0.0031

-1.12

0.0833

0.0824 0.0009

0.54

Matched n

809

286

912

881

Panel C: Doubly Robust Regression Estimates of COE

SASB_MTRL = 1 (Material)

SASB_MTRL = 0 (Not Material)

Coefficient

Z-stat

c

_Coefficient

_Z-stat

c

DISC_10K

-0.00491** -2.08

0.00673

0.68

Matched n

1,095

1,793

 

*, **, *** Denote significance at p < 0.10, < 0.05, and < 0.01, respectively.

a _{We match firms that disclose climate-change risk (DISC_10K = 1) with firms that do not (DISC_10K = 0),using nearest neighbor algorithm. We estimate the}

following probit model separately for firms where users assess CCR to be material from firms where users assess CCR to be not material. DISC_10K = 0 + 1BETA + 2BM + 3SIZE + 4FI/PI + 5ROA + 6EXCH + 7STRNG + 8CNCRN + 9CDP +  (1) For variable definitions see Appendix B.

b _{After matching our disclosing (DISC_10K = 1) and non-disclosing (DISC_10K = 0) firms using the propensity scores calculated in Panel A, we examine the}

difference in the COE between these two groups of firms. COE is the composite cost of equity constructed using the median of four measures, namely: Easton’s PEG model (2004), Gebhardt et al. (2001) (GLS), Claus and Thomas (2001) (CT), and the price-earnings ratio.

Cost-of-Equity Effects of Decision to Disclose Climate-Change Risk in Form 10-K

After Controlling for Corporate Governance

Panel A: Probit Regression Model for Propensity Score Matching

a

D.V. is DISC_10K

Estimates Covariate

Bal

Variable Coeff

Z-stat

DISC_10K = 1

DISC_10K = 0

t-stat

BETA

0.1364

***

2.84

1.1601 1.1496

0.56

BM

-0.1410

*

-1.85

0.5351 0.4766

4.53 ***

SIZE

0.0524

**

2.44

9.8780 10.0560

-3.84 ***

FI/PI

-0.0034

-0.08

0.3002 0.3125

-0.70

ROA

-0.7730

*

-1.78

0.0508 0.0565

-2.71 ***

EXCH

-0.2942

***

-9.44

1.2245 1.2133

0.54

STRNG

-0.0110

-0.48

1.1452 1.3490

-4.23 ***

CNCRN

0.4612

***

11.54

0.6488 0.6259

0.64

CDP

-0.1960

***

-2.98

0.6728 0.7125

-2.57 ***

CGOV

0.1652

***

5.58

1.3305 1.3869

-1.41

n (Total)

2,996

n (

DISC_10K

= 1)

1,791

n (

DISC_10K

= 0)

1,196

n (Matched)

2,987

Pseudo-R

2

0.1143

Panel B: Difference in COE of Propensity-Score-Matched Firms

b

DISC_10K = 1

DISC_10K = 0

Diff.

t-stat

Pre-matching

Post-matching

0.0822

0.0821

0.0801

0.0842

0.0021

-0.0021

2.40

-1.45

**

Matched n

1,791

1,196

After Controlling for Corporate Governance

Panel C: Doubly Robust Regression Estimates of COE

Coefficient

Z-stat

c

DISC_10K

-0.00197**

-2.14

Matched n

2,987

*, **, *** Denote significance at p < 0.10, < 0.05, and < 0.01, respectively. a_{We match firms that disclose climate-change risk (}

DISC_10K = 1) with firms that do not (DISC_10K = 0),using the probit model below. We use the nearest neighbor matching algorithm.

DISC_10K = 0 + 1BETA + 2BM + 3SIZE + 4FI_PI + 5ROA + 6EXCH + 7STRNG + 8CNCRN

+ 9CDP +10CGOV +  (1)

We report covariate balance means and Z-stats to test how equal (balanced) the disclosing and non-disclosing firms are for each covariate after matching.

For variable definitions see Appendix B. b

Using the propensity scores from the probit regressions in Panel A, we match our disclosing firms (DISC_10K = 1) with the non-disclosing firms (DISC_10K = 0). This table provides the difference in COE for our matched firms, i.e., the average effect on the disclosing firms, using the nearest neighbor matching algorithm. COE is the composite cost of equity constructed using the median of four measures, namely: Easton’s PEG model (2004), Gebhardt et al. (2001) (GLS), Claus and Thomas (2001) (CT), and the price-earnings ratio.

Cost-of-Equity Effects of Decision to Disclose Climate-Change Risk in Form 10-K:

Breakdown of Sample by Users’ Based (SASB) Materiality Judgments after Controlling for Corporate Governance

Panel A: Probit Regression Model for Propensity Score Matching

a

SASB_MTRL = 1 (Material)

SASB_MTRL

=

0

(Not

Material)

D.V. is

DISC_10K

Estimates Covariate

Bal

Estimates Covariate

Bal

Variable Coeff

Z-stat

DISC_10K = 1

DISC_10K

= 0

t-stat

Coeff

Z-stat

DISC_10K = 1

DISC_10K

= 0

t-stat

BETA

0.1209

1.35

1.1330

1.1891 -2.18 **

0.1345 **

2.20

1.1296

1.1431

-0.57

BM

0.0253

-0.18

0.6012

0.5437

3.03 ***

0.2642 *** -2.68

0.6032

0.5011

5.69 ***

SIZE

0.1534

***

-3.82 9.9072

9.6452

4.08 ***

0.1574 ***

5.89

9.9206 9.6938 3.97 ***

FI/PI

0.1956

*

1.90 0.2214

0.2243 -0.13

0.0058 -0.11

0.2235 0.2579 -1.54

ROA

0.3743

-0.41 0.0391

0.0480 -2.77 ***

0.8319 -1.57

0.0357 0.0370 -0.38

EXCH

0.5098

***

-7.40 1.1146

1.1024

0.54

0.2122 ***

-5.76

1.1143 1.1014 0.62

STRNG

0.0350

-0.87 1.1171

1.1134

0.05

0.0116 0.41

0.9525 1.0032 -0.84

CNCRN

0.4900

***

8.17 0.9244

0.8415

1.37

0.2780 ***

4.34

0.7745 0.7077 1.23

CDP

0.2697

**

-2.15 0.6549

0.6817 -1.15

-0.1965 ** -2.42

0.6526 0.7541 -4.81 ***

CGOV

_0.0904

_*

_{1.68 1.3037}

_{1.3463 -0.68}

_{0.1972 ***}

_5.36

n

(Total) 1,138

1,809

n

(DISC_10K = 1)

820

909

n

(DISC_10-K = 0)

286

881

n (Matched)

1,106

1,809

Breakdown of Sample by Users’ Based (SASB) Materiality Judgments after Controlling for Corporate Governance

Panel B: Difference in COE of Propensity-Score-Matched Firms

b

SASB_MTRL =

1

(Material)

SASB_MTRL =

0

(Not Material)

DISC_10K

= 1

DISC_10K

= 0

Diff.

t-stat

DISC_10K

= 1

DISC_10K

= 0

Diff.

t-stat

Pre-matching 0.0818 0.0827 -0.0009 -0.52

0.0833 0.0798 0.0035

3.29 ***

Post-matching 0.0812 0.0865 -0.0053 -1.78 *

0.0830 0.0820 0.0010 0.63

Matched n

820

286

909

881

Panel C: Doubly Robust Regression Estimates of COE

SASB_MTRL =

1

(Material) SASB_MTRL

=

0

(Not Material)

Coefficient

Z-stat

c

_Coefficient

_Z-stat

c

DISC_10K

-0.0052* -1.73

0.0008

0.82

Matched n

1,106

1,790

*, **, *** Denote significance at p < 0.10, < 0.05, and < 0.01, respectively. a

We match firms that disclose their CCR in their 10-K reports, DISC_10K = 1, with firms that do not, DISC_10K = 0,using the nearest neighbor algorithm. We estimate the following probit model separately for firms where users judge CCR to be material from those where it is not material:

DISC_10K = 0 + 1BETA + 2BM + 3SIZE + 4FI_PI + 5ROA + 6EXCH + 7STRNG + 8CNCRN + 9CDP +10CGOV +  (1) We report covariate balance means and t-statistics to test how equal (balanced) the disclosing and non-disclosing firms.

For variable definitions see Appendix B. b

Using the propensity scores from the probit regressions in Panel A, we match our disclosing firms (DISC_10K = 1) with the non-disclosing firms (DISC_10K = 0). This table provides the difference in COE for our matched firms, i.e., the average effect on the disclosing firms, using the nearest neighbor matching algorithm. COE is the composite cost of equity constructed using the median of four measures, namely: Easton’s PEG model (2004), Gebhardt et al. (2001) (GLS), Claus and Thomas (2001) (CT), and the price-earnings ratio.

c