Abstract
Purpose
There is evidence that corporate social responsibility (CSR) practices predict higher firm value, but little evidence on which specific aspects of CSR drive this relationship. The purpose of this paper is to study this question in a sample drawn from 35 countries over 2003-2016.
Design/methodology/approach
The authors employ a research design that analyzes observational data with panel data methods including ordinary least squares, firm-random effects, and firm-fixed effects.
Findings
The authors find in a sample drawn from 35 countries over 2003-2016 an economically significant relationship between an overall CSR measure and firm value. The overall CSR score builds on data from Asset4 and is comprised of three indices for environmental, social, and corporate governance aspects of CSR. The authors find that the social index consistently predicts higher market value. The authors also show that the use of particular elements of CSR can lead to substantial omitted variables bias when predicting firm value. The results also suggest a similar bias in studies that focus on a single index, which captures a specific aspect of CSR, but omits the remaining aspects.
Research limitations/implications
The study is subject to limitations common to observational studies.
Practical implications
The authors find robust evidence that CSR predicts market value using a country-benchmarked overall CSR index. The power to predict firm value comes solely from the social dimension of this measure, which captures firm-level practices related to treatment of employees and stakeholder relations including those with customers and the broader community. Three elements drive the social index: customer/product responsibility, human rights, and employment quality. None of the remaining 12 elements significantly predicts firm vale in an empirical setting with firm-FE and extensive covariates. The authors also show that omitted aspects of CSR can easily lead to an omitted variable bias and that the magnitude of this bias is potentially greater with an OLS specification.
Social implications
Among the many dimensions of CSR, only a subset drives firm value. Policies that target to improve the CSR performance of firms adopt a broader definition of CSR.
Originality/value
The authors provide first-hand evidence on which specific aspects of CSR drive firm market value.
Keywords
Citation
Bajic, S. and Yurtoglu, B. (2018), "Which aspects of CSR predict firm market value?", Journal of Capital Markets Studies, Vol. 2 No. 1, pp. 50-69. https://doi.org/10.1108/JCMS-10-2017-0002
Publisher
:Emerald Publishing Limited
Copyright © 2018, Stevan Bajic and Burcin Yurtoglu
License
Published in Journal of Capital Markets Studies. Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial & non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licenses/by/4.0/legalcode
1. Introduction
The last decade has witnessed that corporate social responsibility (CSR) has become a significant theme in strategic business decisions (The Economist, 2008). In PwC’s (2014) 17th Annual Global CEO Survey, 75 percent of CEOs suggest that satisfying societal needs, beyond those of investors, customers and employees, and protecting the interests of future generations is important. A similar view emerges from the Edelman Trust Barometer (2014) suggesting that 84 percent of responding consumers believe that business can pursue its self-interest while doing good work for society. While the emphasis on CSR is shaping the relationship between companies and their stakeholders, there is a lack of agreement on the antecedents and consequences of CSR, and perhaps more importantly, a unified definition of CSR (Griffin and Mahon, 1997; Orlitzky et al., 2003; Margolis and Walsh, 2003; Margolis et al., 2009).
CSR is a complex and multifaceted concept and comprises a broad range of activities of the firm with its various stakeholders. While for some companies, the social dimension of CSR (e.g. the treatment of employees) is important, other companies may care more about their relationship with suppliers and expect them to meet certain standards. Still for some others, environmental aspects (e.g. control of emissions) may be more relevant. Such CSR activities involve that companies go beyond country-level statutory requirements in the provision of goods and services with a public character and in internalizing the externalities they create. CSR can benefit firms through various channels. CSR may improve, for example, brand value, and enhance reputational effects (Baron, 2001). Some CSR activities can make the firm more attractive to employees (Turban and Greening, 1997), increase productivity (McGuire et al., 1988; Waddock and Graves, 1997), contribute to smoother relationships with regulators, and help the firm meet the standards and expectations of its customers and thereby increase revenues (Teraji, 2009). Better CSR performance is also related to better stakeholder engagement and thereby reduce information asymmetries, agency problems, and other types of transaction costs. CSR can also be an insurance mechanism against reputational risks (Godfrey et al., 2009; Koh et al., 2014) and create intangible assets (Gardberg and Fombrun, 2006). This suggests that contracting with stakeholders takes place based on mutual trust and cooperation (Jones, 1995). However, some of these issues can be costly (Palmer et al., 1995), both in terms of direct costs (e.g. when expenditures for charitable donations or environmental protection increase) and so reduce profits. CSR activities can also reduce firms’ flexibilty by introducing additional constraints and thereby lead to lower operating efficiency, which contributes indirectly to the costs of the CSR activities (Claessens and Yurtoglu, 2013).
This paper builds on our previous work (Bajic and Yurtoglu, 2018) and suggests that observational CSR studies of whether CSR predicts higher shareholder value can be subject to omitted variable bias (OVB), which poses an important challenge to identification. While OVB is ubiquitous virtually in all studies that use observational research designs, its specific consequences in CSR research have not been studied extensively. Many studies of CSR use a single, specific CSR construct which is either not available (e.g. environmental disclosure) or not meaningful for firms in other industries (e.g. hazardous waste reduction). In their influential meta-analysis including 251 studies, Margolis et al. (2009) show that a substantial fraction of these studies use a specific CSR construct, which measures only a limited number of CSR practices. However, different aspects of CSR are often correlated. Firms with superior performance in one of these aspects, e.g., in reducing emissions, are likely to perform well also on other dimensions, e.g., reducing resources. A study, which analyzes the impact of only one of these aspects in isolation from other aspects may document a relationship between the included aspect and a measure of performance, however, the true driver of superior performance can be an omitted dimension of CSR. This raises concerns both for studies that use a broad measure of CSR and for studies that employ a specific measure. Using a broad measure of CSR raises the concern that the true driver(s) would remain hidden in the definition of the broad measure and using a specific measure might suggest a link between this measure and firm value due its correlation with other aspects omitted from the analysis. Both approaches can potentially deliver misleading policy recommendations.
We deal with this problem by using ESG measures of three different granularities. We first employ a broad measure of CSR, using data from ASSET4, reflecting firm-level choices and activities in dealing with ESG issues. One major advantage of using this broad index is that it captures the differences across many countries, but has sufficient commonality across countries to allow for generalization. Using this measure, we assess whether CSR affects firm market value (proxied by Tobin’s q) and how estimates from firm fixed effects (FE) or random effects (RE) with extensive covariates differ from pooled OLS results. In the second step, we analyze whether the components of this broad measure, comprised of environmental (E), social (S), and governance (G) indices matter for firm value. Then, in a third step, we employ 15 specific elements of these three ESG aspects using the same empirical setting. With the use of these three types of measures with increasing granularity, we document the following empirical regularities:
the broad ESG measure captures an economically and statistically significant impact of CSR on firm value;
the social aspect of this measure drives the relationship between CSR and firm value; and
only a small subset of the 15 specific elements of the broad CSR measure predict firm value.
In the next part, we present a brief literature review of the relationship between CSR and firm value. Section 3 describes our data sources and details the definitions of the employed variables. Section 4 develops our empirical strategy. Section 5 presents our results. Section 6 concludes.
2. The relationship between CSR and corporate financial performance (CFP)
The empirical literature on CSR, especially in the US corporate context is vast. Three influential papers survey this literature (Margolis and Walsh, 2003; Orlitzky et al., 2003; and Margolis et al., 2009) and report a significantly positive, albeit quite small effect of CSR on CFP[1]. A large fraction of these studies use measures of CSR that specifically focus on environmental performance and self-reported social performance. With third-party audits used to assess CSR, one obtains usually a weaker association between CSR and corporate performance.
The studies included in the above-mentioned surveys use substantially different empirical strategies. Earlier studies (e.g. Spicer, 1978; Aupperle et al., 1985; Spencer and Taylor, 1987) report pure associations of various measures of CSR and CFP. Other studies use a regression framework with limited controls for firm characteristics. These studies usually rely on cross-sectional data or cross-sectional methods (e.g. Waddock and Graves, 1997; Hillman and Keim, 2001) which gives rise to endogeneity concerns, including the potential for both reverse causation and OVB. Novel exceptions include Dowell et al. (2000) who analyze the environmental standards in a sample of US multinational companies using a RE specification. They report that adopting a single stringent environmental standard globally is associated with higher market valuations than adhering to local or US environmental standards. Berman et al. (1999) adopt a two-step GLS approach and identify which aspects of CSP matter for the firms in their sample. Garcia-Castro et al. (2010) employ panel data models using KLD data on US firms and show that CSR predicts higher performance in OLS equations, but not in FE specifications.
Sharfman and Fernando (2008) and El Ghoul et al. (2011) show that firms which display higher levels of CSR enjoy lower costs of equity capital. This findings is consistent with the notion that CSR performance can affect firm value by decreasing financial risk (Kim et al., 2014; Orlitzky and Benjamin, 2001). Cheng et al. (2014) document that firms with better CSR performance face significantly lower capital constraints and have easier access to finance. More recently, Liang and Renneboog (2018) report a positive relationship between CSR and firm value in a sample of 4,700 large, public companies. A positive relationship between CSR and firm value is also reported by Lins et al. (2017) who study the 2008-2009 financial crisis period.
We provide a brief overview of studies that focus on the relationship between CSR and firm value, but not covered in the above-mentioned surveys, in Table I.
The analysis of the validity of constructs used to proxy for CSR practices in prior research is limited. Waddock and Graves (1997) criticize a wide range of CSR constructs used in prior research (see the references therein) and suggest that one needs a multidimensional measure of CSR which should be meaningful for a wide range of companies. Dowell et al. (2000) and Margolis et al. (2009) express similar concerns on the validity of CSR measures. Bajic and Yurtoglu (2018) study the validity of CSR constructs based on Asset4 data. To the best of our knowledge, no other paper studies the extent to which the use of specific CSR constructs can lead to a bias in predicting firm value.
3. Data sources and ESG scores
3.1 Data
We use the following data sources. CSR data is from Thomson Reuters ASSET4, which is specialized in disseminating socially responsible investment analysis. Financial data come from the WRDS Compustat North America and Compustat Global databases. We substitute missing financial data from Datastream. Information on cross-listed firms, including the foreign exchange(s) they are listed and listing level comes from databases maintained at the Bank of New York (www.adrbny.com) and JP Morgan (www.adr.com). We translate the variables into US dollars using the exchange rates obtained from Bloomberg at the fiscal year end.
3.2 ESG scores
Environmental, social and governance scores are from the ASSET4 database of Thomson Reuters[2]. ASSET4 specializes in providing systematic ESG information to professional investors who integrate ESG data into their investment analysis. Economist (2013) estimates that investors representing more than $3.3 trillion assets under management make use of ASSET4 data. ASSET4 transforms more than 900 evaluation points per firm into 250 key performance indicators. These indicators are organized into 18 categories within four pillars: environmental performance, social performance, corporate governance and economic performance. In a year t, firms receive a z-score for each of the four pillars, based on all the information available in fiscal t−1. Therefore, by construction, ESG scores are lagged by one year. A firm’s performance in a pillar is benchmarked with all of the remaining firms, with the firms in the same country, or with the firms in the same business sector.
Environmental scores have three elements reflecting firm-level efforts to reduce resources and emissions as well as to increase performance in product innovation. Social scores use eight elements such as employment quality, health and safety, training and development, diversity, human rights, community, and product responsibility. Governance scores have five elements (board structure and functions, compensation policy, shareholder rights, and the firm’s vision and strategy). Table II details these individual elements and reports descriptive statistics.
We use the annual environmental, social and corporate governance scores to construct a composite CSR measure for every year and each firm. We follow the convention established by previous studies and assign equal weights to each of the scores[3]. We call this overall CSR measure ESG. Since disclosure requirements as well as the strength and quality of institutions vary across countries, we benchmark the CSR measures with the firms in the same country.
Table III shows that the resulting sample is an unbalanced panel of 23,803 firm-years with CSR data during 2003-2016 from 35 countries. The majority of the observations (10,748) are from the USA, Japan, and the UK, however, we also have a large sample from European countries (5,155). On average, we have slightly less than seven observations per firm. For our empirical analysis, we exclude all firms in financial and regulated industries, because they are likely to be subject to different rules and regulations. The majority of firms in our sample is active in manufacturing industries, about 20 percent are from energy and basic materials, 13 percent from IT, and the remaining ones are in healthcare and telecommunications.
4. Methodology
Next section details our empirical methods and Section 4.2 details control variables.
4.1 Empirical models
The natural logarithm of Tobin’s q is our primary dependent variable. We take logs to reduce the influence of high-q outlier firms. In our base specification, all variables are winsorized at 1-99 percentiles. We use two different econometric models. The first model, pooled OLS, has the following specification:
The second model, RE specification, adds fi, firm-RE to Model (1). In the FE specification, the firm effects are assumed to be fixed instead of random:
The FE model provides unbiased estimates even if the firm effects are correlated with other covariates, but imposes a cost because many aspects of ESG scores are sticky. With FE, we can study only aspects with substantial within-firm time variation.
We also employ models where we replace ESG with its indices (E, S, and G) included separately:
Similarly, we also estimate models that replace the E, S, and G aspects with 15 individual elements that constitute them:
In studies which focus on a single aspect, the coefficient on an index (or more often an element in this index) using variants of Model (3a or 3b) can reflect the effect of another omitted index (or also other neglected elements) and can potentially lead to OVB. Therefore, while it is appropriate to use Models (1) and (2) to estimate the relationship between a broad ESG measure and firm value, Models (3a) and (3b) are likely to yield biased coefficients when assessing which aspect(s) of ESG matters. To account for this potential bias, we employ two additional models in which we consider all indices (4a) and elements (4b) together:
4.2 Control variables
Many firm characteristics are potentially associated with both q and ESG. We therefore include the following extensive set of covariates to minimize OVB concerns. Firm size: ln (assets). Leverage: total debt/assets, because leverage can influence Tobin’s q by providing tax benefits, affecting bankruptcy risk and reducing free cash flow problems. Leverage is also mechanically related to q, since both variables use the same denominator; Growth prospects: we control for growth prospects using three year geometric growth rate of sales (or two-year growth if the three year growth rate is missing). Firms with attractive opportunities to innovate are likely to spend more on R&D than other companies, and earn monopoly rents from their innovations. These firms will have relatively high returns on capital that will be reflected in higher qs. Since some countries in our sample do not require the disclosure of R&D expenditures, we employ a dummy variable for firms with positive R&D expenditures and obtain similar results with the R&D/Sales ratio[4]. We control for profitability using EBIT/Sales. Capital intensity: we use the ratio of capital expenditures (Capex) to property, plant and equipment (PPE) and the ratio of PPE to sales (PPE/Sales); Liquidity: we include share turnover (annual average of daily shares traded over shares outstanding), the fraction of freely trading shares (Free float) as measures of share liquidity, since share prices may be higher for firms with more liquid shares. Risk: we use the standard deviation of monthly stock returns in year t as a measure of the total risk of the firm (Volatility). Cross-listing dummy: cross-listings may enhance liquidity, foreign investor interest, and also proxy for otherwise unobserved growth opportunities and governance effects (Doidge et al., 2007). To control for these effects we include a dummy for firms cross-listed in US (at any level). We employ a dummy for firms, which report negative equity, because firms with negative equity are close to bankruptcy, show signs of financial distress, and are usually excluded from samples in empirical work. Industry and country: factors such asset structure, accounting practices, government regulation, and industry concentration may vary across industries and countries. They may affect both ESG practices and firm valuation. To account for these differences, we include a set of industry dummies defined at the 2-digit SIC level and country dummies. Industry and country dummies drop out in the FE specification, but they are relevant for OLS and RE specifications.
Table IV reports the descriptive statistics of Tobin’s q and other covariates. Tobin’s q for the full sample is 1.35 with a standard deviation of 1.61. The average company has a growth rate of around 6.3 percent, a mean leverage of 21.8 percent, and Capex in the order of 15.3 percent of fixed assets. The sample consists of large and highly traded companies, which have a large investor base (mean free float=72.5 percent) and visible (~34 percent of them have a cross-listing in the USA). 45.5 percent of firms report R&D expenditures and a small fraction of them report negative equity. Overall, these statistics suggest that our sample contains mostly large, visible and liquid firms.
5. ESG scores and firm value
5.1 The impact of overall ESG scores on firm value
In Table V, we examine whether the overall ESG measure predicts Tobin’s q. Columns 1-3 report the coefficients from OLS, firm-RE, and firm-FE specifications of ln (Tobin’s q) on ESG. In columns 4-9 we study whether the environmental, social and governance indices predict firm value. In even (odd-)-numbered columns, we regress these three indices together (separately) on q[5]. All regressions use the full set of firm-level covariates, time, industry and country dummies (dropped for FE). The t-statistics use standard errors clustered on firm.
Most firm-level covariates capture significant coefficients with a sign consistent with theoretical considerations. Size has a highly significant negative coefficient in OLS, RE and FE specifications. The coefficient on Leverage is consistently positive and significant. Firms growing (Sales growth) and investing at higher rates (Capex/PPE) have higher qs. The measure of total firm risk (volatility) is negatively associated with q. The PPE/sales ratio captures a small and negative coefficient. The remaining covariates tend to capture significant coefficients in the OLS and firm-RE specifications, but not with firm-FE.
We obtain a positive and highly significant coefficient on the overall ESG score (β2=0.246) with OLS. With RE, ESG significantly predicts q (β2=0.107). (Untabulated) Breusch-Pagan tests strongly reject the absence of firm effects and imply that pooled OLS coefficients will be biased. At the same time Hausman tests strongly reject the equivalence of RE and FE models[6]. Thus, if the FE specification is correct, RE results will be biased. The median RE λ, indicating whether RE results are closer to pooled OLS (λ=0) or to FE (λ=1) is relatively high (λ≈0.75). With firm-FE, the coefficient on overall ESG drops to 0.064 and remains significant at the 5 percent level. Tobin’s q equations use 23,352 observations from 3,844 firms and explain 20 percent of the variation in q in the FE specification[7]. The coefficients have economically meaningful magnitudes. The coefficient on ESG in the FE specification implies that a one standard deviation increase in ESG predicts 6.6 percent higher Tobin’s q.
5.2 The impact of environmental, social, and governance scores on firm value
In columns (4)-(9) of Table V we focus on the three indices of the overall ESG measure. As noted before, different aspects of CSR correlate. Therefore, separate estimates of their effect on firm value can be biased due to omitting other aspects of CSR. To address this bias, we use two different approaches. We first estimate separate coefficients on the ESG indices, then we include all subindices together in a single regression. In this specification, the coefficient on each index indicates the contribution of the part of each index that is orthogonal to the other indices. We start with OLS equations and regress the social (S), environmental (E), and governance indices (G) separately on q (reported in even numbered columns) and then regress them together on q (reported in odd-numbered columns). When we regress the E, S, and G indices separately on q, we obtain highly significant coefficients on all of them (except for the G index in the firm-FE specification reported in column 8). In the OLS specification (column 4) all three aspects are highly significant and their coefficients are relatively large: the social index captures a coefficient of 0.188 (t-value=6.68), the coefficient on the environmental index is 0.145 (t-value=4.82), and the coefficient on the governance index is 0.141 (t-value=5.77). When we include all three aspects together in a single regression (column 5), the environmental aspect becomes insignificant, and the coefficients on the S and G indices drop in magnitude and lose some significance. In the remaining columns, we repeat the same exercise using firm-RE and firm-FE specifications and obtain qualitatively similar results. All three indices capture statistically and economically significant coefficients when regressed on firm value in isolation from other indices, but with the exception of the social aspect, fail to do so in the presence of the other indices.
The only aspect, which matters for firm value is the social aspect of the overall CSR measure. The other indices capturing environmental and governance aspects have no consistent predictive value. With OLS, RE or FE, none of the coefficients on these indices are significant, and the signs on the coefficients are mixed. This comparison suggests that omitting relevant aspects of CSR can lead to severe OVB bias and can falsely suggest that a specific aspect matters for firm value, while in fact, the significance is due to the omission of a relevant aspect of CSR.
5.3 The impact of specific CSR elements on firm value
In this section, we examine which individual elements that we used to define the E, S, and G indices predict firm value. These individual elements represent a much higher granularity than the indices they jointly form and accordingly capture much more specific dimensions of CSR. The environmental index has three elements, the social index has seven and the governance index consists of five different elements.
As noted before, there is a potential concern of OVB when a study focuses on one or few such aspects and omits the others. To show the consequences of omitting relevant aspects of CSR, we start focusing on a single element at a time and estimate separate coefficients on each of these elements. Then we include all elements together in a single regression. Table VI reports the results of this exercise. We report in columns 1, 3, and 5 the regression results when the elements are used separately[8] and in columns 2, 4, and 6, when all 15 elements are included together.
When we use the elements separately to predict Tobin’s q, 13 out of 15 elements are highly significant in the OLS specification (column 1). When they are included together, the number of significant elements drops to 5 and we observe a substantial decrease in the magnitudes of the coefficient estimates. Importantly, some of the coefficients capture negatively significant coefficients. For example, the “Product Innovation” element which is part of the environment index captures a coefficient of 0.040 (t-value=1.41) when included in isolation from the remaining elements (column 1). When it is regressed on Tobin’s q together with the remaining 14 elements, the coefficient estimate becomes -0.071 (significant at the 5 percent level). Similarly, the “Health and Safety” element that is part of the social index, has a coefficient of 0.092 (t-value=3.43) when used in isolation. This coefficient predicts higher Tobin’s q in the order of 9.6 percent for a one standard deviation increase. However, when we control for the remaining elements (column 2), the estimated coefficients drops to an insignificantly negative 0.044. These examples demonstrate that omitting the remaining aspects of CSR can overstate the importance of a specific CSR practice and can lead to misleading policy implications.
The remaining columns in Table V demonstrate similar effects with firm-RE and firm-FE specifications. We note the following differences to OLS results. Only 9 of the 15 elements are significant predictors of firm value when we use a firm-FE specification where each element is estimated in isolation from the remaining elements, suggesting the importance of controlling for unobserved but fixed firm-level characteristics. When all 15 elements are included together, only 4 of them remain significant, 1 of them capturing a significantly negative coefficient (Shareholder rights). All of the three significantly positive elements are part of the social index. With the firm-RE specification, 11 of the 15 elements capture significant coefficients when they are estimated separately. The number of significant elements drops to four when they are estimated together in a single firm-RE regression (one of these elements captures a negative coefficient). The three elements, which capture significantly positive coefficients belong to the social index and they also coincide with the significant elements from the firm-FE specification in column 6. We conclude that the use firm-RE and firm-FE specifications reduce but do not eliminate the potential for OVB when one focuses on a single CSR element.
These results highlight the need to use a broadly defined CSR measure to assess the importance of CSR, and to control for the rest of this overall index when assessing a particular aspect. Studies, which focus on a specific aspect of CSR may find an association between this aspect (say employee treatment or emission reduction) and firm value, but it is important to note that exclusion of other aspects of CSR can lead to misleading inferences. The results in Table V suggest that even firm-RE and firm-FE specification can fail to reduce this source of OVB. The findings of predictive value for a single dimension of CSR can be the observed as consequence of this bias.
6. Conclusions
Prior research provides evidence that CSR predicts firm market value. However, there is little evidence on which aspect(s) of CSR drives this result in a robust empirical setting with firm-FE and extensive covariates, including controls for other aspects of CSR. We seek here to begin to fill that gap.
We find robust evidence that CSR predicts market value using a country-benchmarked overall CSR index. The power to predict firm value comes solely from the social dimension of this measure, which captures firm-level practices related to treatment of employees and stakeholder relations including those with customers and the broader community. These results suggest that firms, in responding to investor pressure for better CSR; and investors, in assessing CSR, would do well to focus on the social aspect of CSR practices.
Three elements drive the social index: customer/product responsibility, human rights, and employment quality. None of the remaining 12 elements significantly predicts firm value in an empirical setting with firm-FE and extensive covariates. We also show that omitted aspects of CSR can easily lead to an OVB and that the magnitude of this bias is potentially greater with an OLS specification. When studying CSR, the approach of using a single construct, which omits a variety of other CSR aspects, is likely to work poorly.
Overview of studies on CSR and firm value
Measure of CSR | ||||||
---|---|---|---|---|---|---|
Study | Sample period | Dependent variable | Overall | Social | Environmental | Overview |
Albuquerque et al. (2014) | 2003-2011 | Firm value, firm risk, Tobin’s q | + | CSR is considered as an investment in customer loyalty. Empirically, CSR reduces systematic risk on average and more strongly for firms producing differentiated goods and when consumers’ expenditure share on CSR goods is small | ||
Bouslah et al. (2013) | 1991-2007 | Firm risk | + | + | + | Firm risk for S&P500 index constituents is positively affected by employee, diversity, and governance concerns. Community (Diversity) strengths negatively (positively) affect firm risk. As to non-S&P500 members, firm risk is positively affected by employee concerns and diversity strengths. However, firm risk of non-S&P500 members is negatively affected by Environment strengths |
Chava (2014) | 1992-2007 | Implied cost of equity | + | Investors demand significantly higher expected returns on stocks with environmental concerns compared to firms without such concerns. Lenders charge a significantly higher interest rate on bank loans issued to firms with these environmental concerns | ||
Dhaliwal et al. (2014) | 1992-2007 | Implied cost of equity | +a | Negative association between CSR disclosure and the cost of equity capital; this relationship is more pronounced in stakeholder-oriented countries. There is also evidence that financial and CSR disclosures act as substitutes for each other in reducing the cost of equity capital | ||
Dimson et al. (2015) | 1999-2009 | Firm value, Tobin’s q | + | + | + | Successful CSR engagements with US public companies experience positive abnormal returns. Firms with reputational concerns and higher capacity to implement changes are more likely to experience positive abnormal returns |
El Ghoul et al. (2011) | 1992-2007 | Implied cost of equity | + | + | + | Firms with better CSR rankings enjoy cheaper equity financing. Investment in improving CSR rating contributes substantially to reducing cost of equity. Participation in two “sin” industries, tobacco and nuclear power, increases firms’ cost of equity |
Flammer (2015) | 1997-2012 | Firm value | +a | One of the few papers using a quasi-natural experiment design (regression discontinuity design). The passage of “close-call” CSR-related shareholder proposals is similar to a random assignment of CSR to companies and leads to positive announcement returns and better accounting performance. The channels are higher labor productivity and sales growth | ||
Liang and Renneboog (2018) | 2002-2013 | Tobin’s q | +a | +a | +a | CSR performance is higher when dividends are high, leverage is high, cash flows and cash holdings are low, and when there is a high managerial pay-for-performance sensitivity. There is a positive relation between CSR investments and Tobin’s q (with instrumental variables) suggesting a causal link between good governance and high CSR and Tobin’s q |
During the 2008-2009 financial crisis, firms with high CSR intensity had stock returns that were four to seven percentage points higher than firms with low social capital. High-CSR firms also experienced higher profitability, growth, and sales per employee relative to low-CSR firms, and they raised more debt. The evidence suggests that the trust between a firm and both its stakeholders and investors pays off when the overall level of trust in corporations and markets suffers a negative shock | ||||||
Servaes and Tamayo (2013) | 1991-2005 | Firm value, Tobin’s q | + | CSR has a small, negative impact on market value for firms with low advertising intensity, and a positive impact for firms with high advertising intensity. There is no effect with a firm fixed effects specification | ||
Sharfman and Fernando (2008) | 2002-2002 | Cost of capital | +a | Firms benefit from better environmental risk management through a reduction in their cost of equity capital, a shift from equity to debt financing, and higher tax benefits which come with the ability to add more debt |
Notes: This table presents an overview of selected papers on the relationship between CSR and firm value, including the authors, the sample period, the independent variable, and the CSR data used. The two most widely recognized ESG data sets are KLD and Asset4. All studies use KLD data, except aIndicates the use of other sources of CSR data
CSR data
ESG measure | Description | Definition | Mean | SD | Min. | Max. |
---|---|---|---|---|---|---|
ESG | Overall CSR index | Equally weighted average of the environmental, social, and corporate governance indices | 0.526 | 0.242 | 0.003 | 1 |
E | Subindex: environment | Equally weighted average of the three elements comprising the environment index | 0.546 | 0.304 | 0.003 | 1 |
S | Subindex: social | Equally weighted average of the seven elements comprising the social index | 0.550 | 0.302 | 0.003 | 1 |
G | Subindex: corporate governance (CG) | Equally weighted average of the five elements comprising the CG index | 0.501 | 0.300 | 0.000 | 1 |
Resource reduction | Element 1: environment index | Measures a company’s management commitment and effectiveness toward achieving an efficient use of natural resources in the production process and reflects the capacity to reduce the use of materials, energy or water, and to find more eco-efficient solutions by improving supply chain management | 0.549 | 0.304 | 0.001 | 1 |
Emission reduction | Element 2: environment index | Measures a company’s management commitment and effectiveness toward reducing environmental emission in the production and operational processes. It reflects a company’s capacity to reduce air emissions (greenhouse gases, F- gases, ozone-depleting substances, NOx and SOx, etc.), waste, hazardous waste, water discharges, spills or its impacts on biodiversity and to partner with environmental organizations to reduce the environmental impact of the company in the local or broader community | 0.546 | 0.307 | 0.003 | 1 |
Product innovation | Element 3: environment index | Measures a company’s management commitment and effectiveness toward supporting the research and development of eco-efficient products or services. It reflects a company’s capacity to reduce the environmental costs and burdens for its customers, and thereby creating new market opportunities through new environmental technologies and processes or eco-designed, dematerialized products with extended durability | 0.516 | 0.306 | 0.028 | 1 |
Employment quality | Element 1: social index | Measures a company’s management commitment and effectiveness toward providing high-quality employment benefits and job conditions. It reflects a company’s capacity to increase its workforce loyalty and productivity by distributing rewarding and fair employment benefits, and by focusing on long-term employment growth and stability by promoting from within, avoiding lay-offs and maintaining relations with trade unions | 0.530 | 0.300 | 0.000 | 1 |
Health and safety | Element 2: social index | Measures a company’s management commitment and effectiveness toward providing a healthy and safe workplace. It reflects a company’s capacity to increase its workforce loyalty and productivity by integrating into its day-to-day operations a concern for the physical and mental health, well-being and stress level of all employees | 0.525 | 0.299 | 0.007 | 1 |
Training and development | Element 3: social index | Measures a company’s management commitment and effectiveness toward providing training and development (education) for its workforce. It reflects a company’s capacity to increase its intellectual capital, workforce | 0.558 | 0.300 | 0.002 | 1 |
Diversity and opportunity | Element 4: social index | Measures a company’s management commitment and effectiveness toward maintaining diversity and equal opportunities in its workforce. It reflects a company’s capacity to increase its workforce loyalty and productivity by promoting an effective life-work balance, a family friendly environment and equal opportunities regardless of gender, age, ethnicity, religion or sexual orientation | 0.523 | 0.310 | 0.009 | 1 |
Human rights | Element 5: social index | Measures a company’s management commitment and effectiveness toward respecting the fundamental human rights conventions. It reflects a company’s capacity to maintain its license to operate by guaranteeing the freedom of association and excluding child, forced or compulsory labor | 0.503 | 0.302 | 0.000 | 1 |
Community | Element 6: social index | Measures a company’s management commitment and effectiveness toward maintaining the company’s reputation within the general community (local, national and global). It reflects a company’s capacity to maintain its license to operate by being a good citizen (donations of cash, goods or staff time, etc.), protecting public health (avoidance of industrial accidents, etc.) and respecting business ethics (avoiding bribery and corruption, etc.) | 0.550 | 0.300 | 0.001 | 1 |
Customer/Product responsibility | Element 7: social index | Measures a company’s management commitment and effectiveness toward creating value-added products and services upholding the customer’s security. It reflects a company’s capacity to maintain its license to operate by producing quality goods and services integrating the customer’s health and safety, and preserving its integrity and privacy also through accurate product information and labeling | 0.537 | 0.307 | 0.001 | 1 |
Board structure | Element 1: CG index | Measures a company’s management commitment and effectiveness toward following best practice corporate governance principles related to a well-balanced membership of the board. It reflects a company’s capacity to ensure a critical exchange of ideas and an independent decision-making process through an experienced, diverse and independent board | 0.474 | 0.294 | 0.000 | 1 |
Compensation policy | Element 2: CG index | Measures a company’s management commitment and effectiveness toward following best practice corporate governance principles related to competitive and proportionate management compensation. It reflects a company’s capacity to attract and retain executives and board members with the necessary skills by linking their compensation to individual or company-wide financial or extra- financial targets | 0.478 | 0.300 | 0.000 | 1 |
Board functions | Element 3: CG index | Measures a company’s management commitment and effectiveness toward following best practice corporate governance principles related to board activities and functions. It reflects a company’s capacity to have an effective board by setting up the essential board committees with allocated tasks and responsibilities | 0.478 | 0.287 | 0.000 | 1 |
Shareholder rights | Element 4: CG index | Measures a company’s management commitment and effectiveness toward following best practice corporate governance principles related to a shareholder policy and equal treatment of shareholders. It reflects a company’s capacity to be attractive to minority shareholders by ensuring equal rights and privileges and by limiting the use of anti-takeover devices | 0.507 | 0.297 | 0.000 | 1 |
Vision and strategy | Element 5: CG index | Measures a company’s management commitment and effectiveness toward the creation of an overarching vision and strategy integrating financial and extra-financial aspects. It reflects a company’s capacity to convincingly show and communicate that it integrates the economic (financial), social and environmental dimensions into its day-to-day decision-making processes | 0.551 | 0.305 | 0.007 | 1 |
Notes: This table shows summary statistics and definitions of the overall CSR measure (ESG), its indices (Environmenal, Social and Corporate Governance), and the index elements from Asset 4
CSR data by country
ESG | Environmental | Social | Governance | ||||||||
---|---|---|---|---|---|---|---|---|---|---|---|
Period | N | Mean | Median | SD | Mean | SD | Mean | SD | Mean | SD | |
Australia | 2003-2016 | 1,397 | 0.508 | 0.483 | 0.211 | 0.467 | 0.282 | 0.422 | 0.288 | 0.620 | 0.253 |
Austria | 2003-2016 | 169 | 0.552 | 0.551 | 0.225 | 0.614 | 0.270 | 0.599 | 0.296 | 0.489 | 0.259 |
Belgium | 2003-2016 | 232 | 0.516 | 0.543 | 0.221 | 0.565 | 0.269 | 0.573 | 0.281 | 0.559 | 0.252 |
Bermuda | 2003-2016 | 117 | 0.474 | 0.451 | 0.303 | 0.521 | 0.298 | 0.457 | 0.291 | 0.445 | 0.305 |
Brazil | 2008-2016 | 408 | 0.559 | 0.571 | 0.179 | 0.684 | 0.278 | 0.593 | 0.269 | 0.316 | 0.221 |
Canada | 2003-2016 | 1,039 | 0.516 | 0.487 | 0.210 | 0.479 | 0.302 | 0.451 | 0.298 | 0.717 | 0.214 |
Cayman Islands | 2005-2016 | 82 | 0.400 | 0.316 | 0.234 | 0.398 | 0.245 | 0.394 | 0.249 | 0.467 | 0.275 |
China | 2009-2016 | 485 | 0.397 | 0.382 | 0.174 | 0.352 | 0.255 | 0.398 | 0.260 | 0.345 | 0.244 |
Denmark | 2003-2016 | 227 | 0.554 | 0.573 | 0.217 | 0.621 | 0.287 | 0.629 | 0.292 | 0.561 | 0.259 |
Finland | 2003-2016 | 262 | 0.538 | 0.560 | 0.222 | 0.629 | 0.282 | 0.656 | 0.295 | 0.559 | 0.263 |
France | 2003-2016 | 889 | 0.590 | 0.644 | 0.237 | 0.685 | 0.286 | 0.672 | 0.285 | 0.579 | 0.265 |
Germany | 2003-2016 | 800 | 0.563 | 0.604 | 0.249 | 0.618 | 0.296 | 0.600 | 0.304 | 0.442 | 0.266 |
Greece | 2003-2016 | 163 | 0.526 | 0.524 | 0.267 | 0.574 | 0.333 | 0.533 | 0.318 | 0.421 | 0.304 |
Hong Kong | 2003-2016 | 845 | 0.441 | 0.411 | 0.202 | 0.427 | 0.293 | 0.440 | 0.289 | 0.503 | 0.237 |
India | 2008-2016 | 506 | 0.536 | 0.523 | 0.194 | 0.597 | 0.277 | 0.597 | 0.291 | 0.398 | 0.255 |
Ireland | 2003-2016 | 141 | 0.501 | 0.480 | 0.265 | 0.485 | 0.292 | 0.512 | 0.303 | 0.640 | 0.271 |
Israel | 2003-2016 | 90 | 0.496 | 0.543 | 0.220 | 0.524 | 0.323 | 0.508 | 0.309 | 0.448 | 0.270 |
Italy | 2003-2016 | 391 | 0.552 | 0.588 | 0.254 | 0.613 | 0.311 | 0.575 | 0.328 | 0.548 | 0.276 |
Japan | 2003-2016 | 3,072 | 0.533 | 0.562 | 0.251 | 0.544 | 0.319 | 0.608 | 0.322 | 0.300 | 0.300 |
Jersey | 2005-2016 | 32 | 0.656 | 0.739 | 0.211 | 0.634 | 0.231 | 0.635 | 0.240 | 0.627 | 0.171 |
Korea | 2005-2016 | 416 | 0.539 | 0.616 | 0.224 | 0.592 | 0.353 | 0.628 | 0.330 | 0.131 | 0.136 |
Malaysia | 2009-2016 | 280 | 0.489 | 0.499 | 0.171 | 0.553 | 0.274 | 0.475 | 0.274 | 0.538 | 0.237 |
Mexico | 2003-2016 | 154 | 0.471 | 0.498 | 0.229 | 0.513 | 0.351 | 0.492 | 0.310 | 0.219 | 0.240 |
The Netherlands | 2003-2016 | 325 | 0.559 | 0.589 | 0.241 | 0.628 | 0.291 | 0.620 | 0.288 | 0.582 | 0.270 |
New Zealand | 2005-2016 | 165 | 0.451 | 0.408 | 0.214 | 0.356 | 0.283 | 0.372 | 0.285 | 0.461 | 0.282 |
Norway | 2003-2016 | 203 | 0.554 | 0.579 | 0.233 | 0.593 | 0.292 | 0.557 | 0.294 | 0.529 | 0.271 |
Portugal | 2003-2016 | 101 | 0.560 | 0.623 | 0.220 | 0.594 | 0.290 | 0.606 | 0.263 | 0.553 | 0.277 |
Singapore | 2005-2016 | 353 | 0.483 | 0.461 | 0.228 | 0.508 | 0.297 | 0.461 | 0.281 | 0.550 | 0.272 |
South Africa | 2009-2016 | 603 | 0.548 | 0.561 | 0.162 | 0.706 | 0.243 | 0.564 | 0.260 | 0.637 | 0.202 |
Spain | 2003-2016 | 423 | 0.608 | 0.660 | 0.223 | 0.688 | 0.285 | 0.669 | 0.271 | 0.563 | 0.250 |
Sweden | 2003-2016 | 430 | 0.571 | 0.610 | 0.213 | 0.620 | 0.286 | 0.639 | 0.287 | 0.519 | 0.254 |
Switzerland | 2003-2016 | 602 | 0.540 | 0.535 | 0.239 | 0.576 | 0.292 | 0.574 | 0.292 | 0.502 | 0.268 |
Taiwan | 2003-2016 | 725 | 0.463 | 0.450 | 0.235 | 0.485 | 0.331 | 0.557 | 0.309 | 0.216 | 0.240 |
The UK | 2003-2016 | 2,158 | 0.535 | 0.545 | 0.229 | 0.578 | 0.272 | 0.553 | 0.282 | 0.646 | 0.269 |
The USA | 2003-2016 | 5,518 | 0.528 | 0.466 | 0.294 | 0.527 | 0.291 | 0.522 | 0.297 | 0.546 | 0.279 |
Total | 2003-2016 | 23,803 | 0.526 | 0.525 | 0.242 | 0.550 | 0.302 | 0.546 | 0.304 | 0.501 | 0.300 |
Notes: This table presents the composition of the sample and the means, medians, and standard deviations of the overall ESG score and its Environmental, Social, and Governance components
Definitions and descriptive statistics of non-CSR variables
Variable | Definition | Mean | SD | Min. | Max. |
---|---|---|---|---|---|
ln (Tobin’s q) | Natural logarithm of ((BV debt+MV of common stock)/BV of assets) | 0.030 | 0.722 | −3.926 | 4.523 |
Size | Natural logarithm of total assets | 12.425 | 3.735 | 2.392 | 21.926 |
Leverage | Total debt/Total assets | 0.218 | 0.167 | 0.000 | 0.998 |
Sales growth | Sales growth rate (3 or 2-year growth rate (if 3 year missing)) | 0.063 | 0.264 | −0.942 | 1.967 |
EBIT/Sale | EBIT/Sales | 0.643 | 2.321 | −1.697 | 39.213 |
Capex/PPE | Capital Expenditures/(gross) fixed assets | 0.153 | 0.130 | 0 | 1 |
Share turnover | Annual average shares traded (daily) over outstanding | 1.558 | 0.987 | 0.000 | 5.294 |
PPE/Sales | PPE/Sales | 2.730 | 7.309 | −0.036 | 49.995 |
Stock volatility | SD of monthly stock returns in year t (annualized) | 0.300 | 0.142 | 0.010 | 1.500 |
Free float | Fraction of shares excluding locked-in shares such as those held by insiders, or governments | 0.725 | 0.236 | 0 | 1 |
Cross-listing dummy | Dummy, 1 if firm has a US cross-listing, 0 otherwise | 0.342 | 0.474 | 0 | 1 |
R&D dummy | Dummy, 1 if firm reports R&D expenditures, 0 otherwise | 0.455 | 0.498 | 0 | 1 |
Negative equity dummy | Dummy, 1 if firm reports negative equity, 0 otherwise | 0.037 | 0.189 | 0 | 1 |
Note: This table provides definitions of the covariates and descriptive statistics for the samples used in Tables V and VI
Overall ESG, its indices, and firm value
Indices included | |||||||||
---|---|---|---|---|---|---|---|---|---|
Separate | Together | Separate | Together | Separate | Together | ||||
OLS | RE | FE | OLS | RE | FE | ||||
(1) | (2) | (3) | (4) | (5) | (6) | (7) | (8) | (9) | |
ESG | 0.246*** (7.02) | 0.107*** (4.07) | 0.064** (2.15) | ||||||
Social index | 0.188*** (6.68) | 0.160*** (4.17) | 0.130*** (5.89) | 0.098*** (3.55) | 0.100*** (3.80) | 0.075** (2.40) | |||
Environmental index | 0.145*** (4.82) | −0.017 (−0.44) | 0.113*** (4.85) | 0.051* (1.74) | 0.093*** (3.44) | 0.057* (3.44) | |||
Corporate governance index | 0.141*** (5.77) | 0.077*** (2.99) | 0.045** (2.49) | 0.002 (0.11) | 0.015 (0.73) | −0.019 (−0.87) | |||
Firm size | −0.172*** (−22.56) | −0.180*** (−21.62) | −0.193*** (−10.23) | −0.170*** (−22.48) | −0.169*** (−21.63) | −0.182*** (−21.84) | −0.184*** (−21.71) | −0.193*** (−10.23) | −0.193*** (−10.25) |
Leverage | 0.333*** (6.11) | 0.282*** (6.56) | 0.272*** (5.50) | 0.327*** (6.00) | 0.325*** (5.96) | 0.278*** (6.49) | 0.279*** (6.52) | 0.268*** (5.45) | 0.267*** (5.43) |
Sales growth | 0.323*** (17.10) | 0.204*** (17.16) | 0.200*** (16.21) | 0.326*** (17.23) | 0.326*** (17.22) | 0.204*** (17.19) | 0.205*** (17.20) | 0.199*** (16.15) | 0.200*** (16.19) |
EBIT/Sale | 0.001 (0.56) | −0.000 (−0.23) | −0.000 (−0.17) | 0.000 (0.50) | 0.000 (0.49) | −0.000 (−0.31) | −0.000 (−0.31) | −0.000 (−0.21) | −0.000 (−0.19) |
Capex/PPE | 0.953*** (14.22) | 0.516*** (11.66) | 0.426*** (9.02) | 0.957*** (14.20) | 0.949*** (14.15) | 0.513*** (11.60) | 0.512*** (11.56) | 0.422*** (8.94) | 0.419*** (8.88) |
Turnover | 0.029*** (5.26) | 0.004 (1.22) | −0.001 (−0.31) | 0.029*** (5.28) | 0.028*** (5.18) | 0.004 (1.25) | 0.004 (1.24) | −0.001 (−0.30) | −0.001 (−0.27) |
PPE/Sale | −0.010*** (−11.90) | −0.002*** (−3.04) | −0.001 (−0.78) | −0.010*** (−11.76) | −0.010*** (−11.80) | −0.002*** (−3.11) | −0.002*** (−2.96) | −0.001 (−0.97) | −0.000 (−0.44) |
Volatility | −0.811*** (−17.42) | −0.274*** (−10.61) | −0.232*** (−8.53) | −0.806*** (−17.35) | −0.802*** (−17.24) | −0.272*** (−10.52) | −0.272*** (−10.52) | −0.230*** (−8.48) | −0.231*** (−8.49) |
Free float | −0.230*** (−6.78) | −0.023 (−0.86) | 0.024 (0.76) | −0.213*** (−6.33) | −0.223*** (−6.58) | −0.021 (−0.79) | −0.022 (−0.85) | 0.025 (0.77) | 0.025 (0.77) |
Cross-listing | 0.115*** (6.60) | 0.023* (1.77) | −0.001 (−0.04) | 0.115*** (6.57) | 0.112*** (6.40) | 0.022* (1.68) | 0.021* (1.67) | −0.001 (−0.05) | −0.001 (−0.08) |
Pos. R&D | 0.060*** (3.13) | 0.051*** (3.19) | 0.020 (1.10) | 0.062*** (3.21) | 0.067*** (3.47) | 0.051*** (3.18) | 0.050*** (3.12) | 0.020 (1.11) | 0.019 (1.06) |
Neg. equity | −0.281*** (−12.00) | −0.240*** (−14.49) | −0.240*** (−13.77) | −0.279*** (−11.98) | −0.282*** (−12.04) | −0.238*** (−14.39) | −0.238*** (−14.39) | −0.239*** (−13.67) | −0.238*** (−13.64) |
Time dummies | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes |
Industry dummies | Yes | Yes | – | Yes | Yes | Yes | Yes | – | – |
Country dummies | Yes | Yes | – | Yes | Yes | Yes | Yes | – | – |
Observations | 23,352 | 23,352 | 23,352 | 23,352 | 23,352 | 23,352 | 23,352 | 23,352 | 23,352 |
Firms | 3,844 | 3,844 | 3,844 | 3,844 | 3,844 | 3,844 | 3,844 | 3,844 | 3,844 |
R2 (range) | 0.456 | 0.404 | 0.200 | (0.454-0.456) | 0.456 | (0.402-0.406) | 0.406 | (0.199-0.201) | 0.201 |
Notes: OLS, firm random effects (RE), and firm fixed effects (FE) regressions of ln (Tobin’s q) on ESG (its subindices) and control variables for 2003-2016. All variables are winsorized at 1 percent and 99 percent. t-values (in parentheses) use firm clusters. Significant results (at 5 percent level or better) are in italic. *,**,***Significant at 10, 5 and 1 percent level, respectively (suppressed for constant term)
Aspects of ESG and firm value
Subindices included | ||||||
---|---|---|---|---|---|---|
OLS | RE | FE | ||||
Separate | Together | Separate | Together | Separate | Together | |
(1) | (2) | (3) | (4) | (5) | (6) | |
Social index | ||||||
Training and development | 0.154*** (6.01) | 0.033 (1.00) | 0.063*** (3.56) | −0.014 (−0.61) | 0.036* (1.82) | −0.022 (−0.92) |
Customer/Product responsibility | 0.075*** (3.03) | −0.005 (−0.17) | 0.085*** (4.99) | 0.049*** (2.78) | 0.081*** (4.41) | 0.057*** (3.03) |
Human rights | 0.171*** (6.82) | 0.110*** (4.05) | 0.102*** (5.40) | 0.064*** (3.24) | 0.074*** (3.54) | 0.045** (2.13) |
Health and safety | 0.092*** (3.43) | −0.044 (−1.41) | 0.019 (1.06) | −0.050** (−2.55) | −0.004 (−0.22) | −0.053** (−2.56) |
Employment quality | 0.182*** (7.66) | 0.130*** (4.89) | 0.114*** (7.04) | 0.089*** (5.21) | 0.092*** (5.23) | 0.076*** (4.19) |
Diversity and opportunity | 0.111*** (4.34) | −0.020 (−0.63) | 0.075*** (3.94) | 0.007 (0.32) | 0.050** (2.31) | −0.002 (−0.07) |
Community | 0.116*** (4.49) | −0.002 (−0.06) | 0.063*** (3.66) | 0.004 (0.18) | 0.048** (2.55) | 0.008 (0.40) |
Environmental index | ||||||
Resource reduction | 0.189*** (6.77) | 0.191*** (4.57) | 0.110*** (5.19) | 0.043 (1.46) | 0.081*** (3.34) | 0.019 (0.64) |
Product innovation | 0.040 (1.41) | −0.071** (−2.22) | 0.048** (2.49) | −0.019 (−0.86) | 0.044** (2.08) | −0.007 (−0.29) |
Emission reduction | 0.126*** (4.42) | −0.085* (−1.94) | 0.115*** (5.16) | 0.034 (1.16) | 0.103*** (4.05) | 0.054* (1.76) |
Corporate governance index | ||||||
Shareholder rights | 0.119*** (5.24) | 0.087*** (3.60) | −0.005 (−0.31) | −0.016 (−1.02) | −0.036** (−2.19) | −0.042** (−2.47) |
Vision and strategy | 0.137*** (4.85) | −0.013 (−0.36) | 0.093*** (4.49) | 0.021 (0.89) | 0.073*** (3.08) | 0.020 (0.79) |
Compensation policy | 0.053** (2.44) | −0.009 (−0.40) | 0.032** (2.32) | 0.025* (1.77) | 0.024* (1.67) | 0.026* (1.78) |
Board structure | 0.076*** (3.33) | 0.049* (1.94) | 0.009 (0.57) | 0.007 (0.42) | −0.004 (−0.25) | 0.001 (0.04) |
Board functions | 0.043* (1.82) | −0.049* (−1.75) | −0.006 (−0.34) | −0.026 (−1.43) | −0.022 (−1.16) | −0.031 (−1.58) |
Time dummies | Yes | Yes | Yes | Yes | Yes | Yes |
Industry dummies | Yes | Yes | Yes | Yes | – | – |
Country dummies | Yes | Yes | Yes | Yes | – | – |
Observations | 23,352 | 23,352 | 23,352 | 23,352 | 23,352 | 23,352 |
Firms | 3,844 | 3,844 | 3,844 | 3,844 | 3,844 | 3,844 |
R2 (range) | (0.432-0.464) | 0.463 | (0.402-0.414) | 0.412 | (0.208-0.218) | 0.218 |
Notes: OLS, firm random effects (RE), and firm fixed effects (FE) regressions of ln (Tobin’s q) on aspects of ESG and control variables for 2003-2016. All variables are winsorized at 1 and 99 percent. t-values (in parentheses) use firm clusters. Significant results (at 5 percent level or better) are in italic. *,**,***Significant at 10, 5 and 1 percent level, respectively (suppressed for constant term)
Notes
The mean effect size emerging from the surveys suggests a partial correlation coefficient (accounting for the impact of employed covariates), which is around 0.13.
Many prior papers use the KLD (Kinder, Lydenberg, and Domini) database to study the link between CSR and firm value. This database provides CSR data only for large US companies and is not available on an international basis.
Prior studies mostly use equal weighting (see e.g. Hillman and Keim, 2001, Waldman et al., 2006; Cheng et al., 2014). Waddock and Graves (1997) criticize equal weights.
This is true both when we use a smaller sample with reported R&D/Sales and when we replace missing values with zeros.
The coefficients reported in in odd-numbered columns come from three separate regressions. To save space, we report the coefficients on the covariates obtained when using the social score. We present the range of R2s obtained. The coefficient estimates from separate regression are available upon request.
For RE, p-values for Breusch-Pagan test for presence of firm effects and Hausman test for differences in coefficients between RE and FE are both p=0.000.
We report the within R2 for FE, the overall R2 for RE, and the adjusted-R2 for pooled OLS specifications.
Similar to Table V, columns 1, 3 and 5 summarize coefficients from 15 distinct regressions. The full results of element specific regressions are available upon request.
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Further reading
Barnett, M.L. and Salomon, R.M. (2006), “Beyond dichotomy: the curvilinear relationship between social responsibility and financial performance”, Strategic Management Journal, Vol. 27 No. 11, pp. 1101-1122.
Cheung, Y.L., Tan, W., Ahn, H.-J. and Zhang, Z. (2010), “Does corporate social responsibility matter in Asian emerging markets?”, Journal of Business Ethics, Vol. 92 No. 3, pp. 401-413.
Choi, T.H. and Jung, J. (2008), “Ethical commitment, financial performance, and valuation: an empirical investigation of Korean companies”, Journal of Business Ethics, Vol. 85 No. 1, pp. 447-463.
Graves, S.B. and Waddock, S.A. (2000), “Beyond built to last … stakeholder relations in ‘built-to-last’ companies”, Business and Society Review, Vol. 105 No. 4, pp. 393-418.
Kline, P. (2000), Handbook of Psychological Testing, Routledge, London and New York, NY.
McWilliams, A. and Siegel, D. (2001), “Corporate social responsibility: a theory of the firm perspective”, Academy of Management Review, Vol. 26 No. 1, pp. 117-127.
Makni, R., Francoeur, C. and Bellavance, F. (2009), “Causality between corporate social performance and financial performance: evidence from Canadian firms”, Journal of Business Ethics, Vol. 89 No. 3, pp. 409-422.