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07/14/2010

Are All Components of ESG Scores Equally Important?


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Our research questions whether all aspects of responsible investing are equally important for stock analysis. Can the different aspects of ESG performance—that is, performance in environmental and social sectors and corporate governance, as well as operations in “sin” areas—be combined for stock analysis? Our research is geared toward investment practitioners, and we therefore concentrate on stock returns (the main parameter affecting the performance of investment managers) and ROE (return on equity, which is arguably the most important parameter of corporate performance and stock quality). 

We find that overall ESG scores have a predictive and positive association with subsequent total stock returns and financial performance measured by ROE, and this result holds even after controlling for the sector effect. The three component subscores have different impact, with corporate governance scores being the best predictor of medium to long run (three- to five-year) stock returns. The social scores have a greater positive impact on ROE. We also find that the ESG factors have stronger predictive power in the mid- and small-cap range. Our results indicate that investment managers can add alpha by incorporating these extrafinancial factors into their investment process.

Throughout the past two decades it has often been asked how “social” or “responsible” investing affects investment performance. The initial reasoning was that the costs associated with responsible investing would lower a firm’s profit margins and reduce the investment opportunity set for investors. The results, however, have been mixed. Statman (2000) reported that the Domini Social Index, an index of socially responsible stocks, did better than the S&P 500 and that socially responsible mutual funds did better than conventional mutual funds from 1990–98. But the differences in their risk-adjusted returns were not statistically significant. Vermeir et al. (2005) showed that returns after integrating socially responsible factors were insignificantly better than traditional benchmarks, indicating there is no cost involved in integrating sustainability and social responsible practices into an investment policy. Waddock and Graves (2000) found that socially responsible companies have the same performance, both financially and in terms of investment returns. Jiao (2009) found that firms with good stakeholder management skills tend to earn premium valuations. Their definition of stakeholder management, however, includes both environmental parameters and other social factors like community, diversity, employees, and products. Some research indicates that there is an optimal holding horizon for responsible investing; Shank (2005), for example, found that the market positively valued the most socially responsible firms not over the medium term of three years, but rather over longer time horizons like five years.

Much of the research has focused on one component of responsible investing. Gompers et al. (2003) analyzed corporate governance practices and found that for the period 1990–99, firms with strong shareholder rights had risk-adjusted stock returns 8.5% higher per annum than firms with weaker shareholder rights. La Porta et al. (2002) found that poor shareholder protection is penalized with lower valuations. Masulis et al. (2007) found that acquiring firms with better corporate governance have higher abnormal announcement returns. Derwall et al. (2005) focused exclusively on the environmental element of social responsibility and showed that from 1995–2003, a portfolio of stocks ranked high for eco-efficiency outperformed after adjusting for market risk, investment style, and industry effects. Gottsman and Kessler (1998) showed that environmentally screened stocks had returns and risk-adjusted returns similar to other stocks in the S&P 500. Brown (2007) made a case for analyzing the environmental friendliness of a firm during stock selection. Orlitzky (2005) showed that corporate social performance is positively related to corporate financial performance, but corporate environmental performance is not as highly correlated with financial performance.

Some researchers have analyzed the reasons for the link between corporate governance and stock returns. John et al. (2008) found that corporate risk taking and firm growth rates are positively related to the quality of investor protection. Core et al. (2006) found that firms with weak shareholder rights exhibit significant operating underperformance. Waddock and Graves (1997) showed that companies with superior social records have higher returns on equity than other firms. Ferreira and Laux (2007) established a link between corporate governance and stock price efficiency, and demonstrated that bad corporate governance practices—e.g., takeover restrictions—impede information flow to stock prices.

Over the years, responsible investing has broadened to include shareholder rights and corporate governance issues, environmentally friendly policies, and other social issues (like like community involvement, diversity and employee issues, product safety, international humanitarian concerns), as well as operations in controversial areas like the military, gambling, tobacco, and so on. Most of the research has analyzed the impact of specific areas of responsible investing—namely corporate governance, environmental factors, social factors, presence in sin areas—as factors affecting stock returns. Belu and Manescu (2000) provide evidence for a persistently positive link between corporate social responsibility and the economic performance of companies using ROA (return on assets) as a dependent variable. Our research builds upon the existing empirical work by asking the following important questions: Are all aspects of responsible investing equally important for stock analysis? Can the different aspects of ESG performance be combined for stock analysis? We also analyze ROE as a dependent variable, since investment managers often use it as an indicator of a firm’s business performance.

METHODOLOGY AND SAMPLE

We used the KLD STATS database for information on companies regarding strengths and weaknesses in the four broad areas of responsible investing: corporate governance, environmental impact, social practices, and presence in sin areas. We quantified the company’s performance in each area by assigning it a component subscore (number of strengths in that area minus number of concerns in that area). We then aggregated all four subcomponents into an overall score. Scoring is implicitly an equally weighted process, giving equal weight to every strength or weakness, and again giving equal weight to performance in each sub-area of responsible corporate behavior. We believe this equal weighting process precludes a subjective bias, that is, the assumption that an area is more or less important. The three component subscores—(a) corporate governance, (b) environmental impact, and (c) social practices—and the overall score (the sum of these three subcomponent scores and absence from sin score) are the four independent variables, and we analyze their impact on stock returns and financial performance as measured by ROE.

The KLD STATS database is an annual database with data as of December 31 for each year, but the file is not actually released until the middle of February. Therefore, all analysis has been done with dependent variables from the end of February onward to ensure there is no look-ahead bias. The analysis was done with the KLD sample for the years 1995–2006. The 1995–2000 files had data on companies in either the S&P 500 or Domini 400, leading to a sample size of around 650. The 2001 file had data for any company in the S&P 500, Domini 400, or Russell 1000, while the 2002 file also included data for companies in the KLD Large Cap Social index. The sample size in 2001 and 2002 was around 1,100. The 2003 and later files also included most of the Russell 2000 companies, leading to a sample size of around 3,000.

The KLD sample size was fairly constant in the initial years of 1995–2000, and the percentage of companies with a value of zero in every single data field was also fairly constant at around 4% of the sample. We noticed that the percentage of companies with a value of zero in every single data field (i.e., zero in all the strengths and weaknesses in all the subcomponent areas) increased suddenly in 2001 and 2003 (to around 21% of the sample), i.e., in the same years when the KLD overall sample size also increased substantially, first from ≅ 650 to ≅ 1,100 and then to ≅ 3,000. As a data check, we analyzed the companies which were newly introduced into the KLD sample between 2001 and 2003 (years of sizeable increase in sample size) to identify how many of the new names in the sample had zero in all data fields in the year of introduction and also what happened to them in subsequent years. We sought to understand the potential overlap between new names in the sample and names with a value of zero in all data fields. We found that around 35% of the new names in the sample had a value of zero in every single data field during the year of introduction and more of these names gradually had their data fields populated by nonzero numbers in each subsequent year. Also, around 90% of the sample names with a value of zero in every single data field were newly introduced to the sample that year. There is a strong overlap between companies newly introduced to the sample and companies with zero in all data fields. This led us to consider the possibility that the value of zero in all data fields, in cases of companies newly introduced to the sample, could be a proxy for inadequate data and not truly a value of zero. We therefore did our statistical analysis both including and excluding such companies from the sample. Since the results were virtually identical, we are only reporting the results that exclude companies with a value of zero in all data fields.

The dependent variables considered for analysis in the entire KLD sample were stock returns and return on equity over the subsequent one, three, and five years. These time periods overlap with the common investment horizons of investment managers—short-, medium-, and long-term. We conducted and report our analysis year-wise for rolling one, three, and five years within the period February 1996 (starting the return analysis point for the 1995 KLD database file) through February 2008. We have seen the market cycle between value and growth, large cap and small cap, and high- and low-beta stock outperformance during this 12-year period. By conducting our analysis on a rolling year-by-year basis, we feel that a consistent result over time is effectively controlling for well-known factors like the value, size, and market effect. In addition, all statistical analyses were done for the overall sample, and then performed controlling for factors like the sector effect (hence effectively controlling for the beta effect) and size (market capitalization) effect.

Investment managers are constrained by their investment philosophy and client guidelines. This means that an investment manager may be restricted to only a value or growth focus, certain market-capitalization ranges, or certain sectors. By analyzing whether our results hold over time, in both value and growth markets, and different market capitalizations and sectors, we feel confident that our results apply to investment managers with different investment philosophies and client guidelines

Stock returns and ROE were analyzed for up to five years, meaning that we used data until the end February 2008. We used a two- and three-group classification of the companies:

  • Two group classification: good = scores of ≥, else bad
  • Three group classification: good, neutral, bad, with three definitions of neutral:

  1. neutral = score of 0, good = score of > 0, bad = score of < 0
  2. neutral = score of -1, 0, +1, good = score of > 1, bad = score of < -1
  3. neutral = middle 1/3 of scores, good = top 1/3 of scores, bad = bottom 1/3 of scores1

To calculate the component subscore we take the number of strengths in that area minus the number of weaknesses in that area.2 The sin score is calculated as:

sin score = 0 - presence in number of sin areas

Like the other component subscores, sin scores are positively measured, meaning a higher score is better. The best possible scenario would be presence in zero sin areas, leading to a sin score of zero. We find the overall score by using the formula below.

overall score = E + S + G + sin score

where:

E = environmental impact subscore

S = social impact subscore

G = corporate governance subscore

Size or market capitalization is a well-known factor that has an impact on stock returns. Therefore, we analyzed whether the predictive power of the ESG factors vary by market capitalization. The three market capitalization buckets were (a) greater than $ 9 billion, (b) $5–9 billion, and (c) between $250 million and $5 billion. We excluded micro-cap companies with market capitalization below $250 million since they tend to have outlier properties.

RESULTS

Our initial analysis was conducted using the two-way grouping. We calculated the average total stock return and ROE for good and bad companies, and used the t-test to see if the difference in mean was statistically significant. The results are reported in Tables I and II.

Table I: Impact of Overall ESG Score on Subsequent Total Stock Return
Impact of Overall ESG Score on Subsequent Total Stock Return

* The difference is statistically significant.

During the sample period 1995–2006, good companies had higher returns in 42% of the one-year time periods, 55% of the rolling three-year time periods, and 63% of the rolling five-year time periods. This indicates that superior returns to good companies generally accrue over the longer three to five years. The superior returns of the good companies were more consistent in the late 1990s and in the early years of this decade.

Table II: Impact of Overall ESG Score on Subsequent ROE

Impact of Overall ESG Score on Subsequent ROE

* The difference is statistically significant.

The numbers in Table II above show that good companies almost always have better financial performance. This is evidenced by higher return on equity, and this holds across different time horizons. The extent of outperformance, however, is not always statistically significant.

Table III: Impact of Overall ESG Score on Subsequent Total Stock Return, By Sectors
Table III: Impact of Overall ESG Score on Subsequent Total Stock Return, By Sectors
 

Table IV: Impact of Overall ESG Score on Subsequent Return On Equity, By Sectors
Table IV: Impact of Overall ESG Score on Subsequent Return On Equity, By Sectors

In a majority of sectors, good companies have higher average long-term stock returns and higher average ROE across different time horizons.

We next analyzed the impact of the component subscores, namely corporate governance, environment, social, and sin scores on the subsequent one-, three-, and five-year total returns, and the one-, three-, and five-year return on equity.

We used multivariate regression analysis with the model form:

dependent variable = intercept + α environment + β social + µ corporate governance + ∞ sin + €

where:

The dependent variables are the one-year return, three-year return, five-year return, one-year ROE, three-year ROE, or five-year ROE. € denotes the statistical “error,” capturing any other possible independent variables.

We ran the regressions separately for each of the database years from 1995–2006. Our conclusions are based on the sign and statistical significance of the coefficients α, β, µ, and ∞. The results are reported in tables V and VI below.

Table V: Impact of the Component Subscores on Stock Return

Table V: Impact of the Component Subscores on Stock Return
 

Table VI: Impact of the Component Subscores on ROE

Table VI: Impact of the Component Subscores on ROE
 

The main conclusions from the results in Tables V and VI are that corporate governance scores usually have a positive and often statistically significant impact on subsequent three- and five-year returns. Environment scores tend to be associated with subsequently higher one-, three-, and five-year returns, though the effect is usually not statistically significant. Social scores, on the other hand, lead to higher subsequent ROE across the different time horizons, and the effect is statistically significant in most years. Sin scores were the only subcomponent that did not have a clear impact on any of the dependent variables—stock returns and ROE. Therefore, sin scores have been ignored in all subsequent analysis.

For each sample year, we analyzed the performance of good and bad companies within each of the ten GICS (Global Industry Classification Standard) sectors. We did this for the dependent variables of one-, three-, and five-year stock returns and ROE. We constructed 2 x 2 frequency tables (GICS sectors and years) to conclude whether, after controlling for the sector effect, good companies usually do better in terms of stock returns and return on equity. The table below has data for twelve one-year returns and ROE, eleven three-year returns and ROE and eight five-year returns and ROE.

Table VII shows in each cell the percentage of years that good companies outperformed bad companies in the same sector in terms of the dependent variables (stock returns or ROE). ; e.g., the top-left cell reads that in 75% of sample years good companies in the consumer discretionary sector had higher one-year stock returns than bad companies.

Table VII: Impact of Overall ESG Score on Subsequent Total Stock Return & ROE, By Sectors

Table VII: Impact of Overall ESG Score on Subsequent Total Stock Return & ROE, By Sectors
 

Table VII shows that even after controlling for the sector effect, good companies overwhelmingly outperform in terms of having higher stock returns and ROE over different holding horizons.

The Effects of ESG Factors on Total Return and ROE, with a Three-Way Classification

Up until now the statistical analysis was done with a two-way grouping. We next tested the hypothesis that there is a cost to being good. In that case there would probably be a neutral zone where the cost of being good would be roughly equal to the benefit. We therefore did a three-way classification, the three categories being good, neutral, and bad. We worked with the three alternate definitions of neutral mentioned above.

We calculated the average stock returns and ROE of each group for each database year (for the subsequent one, three, and five years) and then took the average for all the years. For example, we calculated the average return of good companies for each one-year period from 1995–2006, and then reported the mean of these means.

Table VIII: Average Stock Returns, When Neutral = 0
Table VIII: Average Stock Returns, When Neutral = 0

The highest returns in each time horizon are in bold.

Table VIII shows that with the overall score, neutral always had the highest return. In case of the corporate governance scores, good had the highest return over three and five years, while neutral did best over the short run one-year period. The difference in average returns between the good and bad groups was economically significant over the medium to long run. The results are surprising for the environment score, where the bad companies outperformed slightly over three and five years. We did not see any clear pattern with the social score.

We did a similar analysis for each of the 10 GICS sectors. The summary table below shows the percentage of sectors in which that group of companies (good, neutral, or bad) had the highest stock returns.

Table IX: Highest Stock Returns, when Neutral = 0
Table IX: Highest Stock Returns, when Neutral = 0
 

Controlling for the sector effect, we see clear results for the corporate governance scores, where in the majority of sectors good companies had the highest return. With social scores, good companies do best over a medium to long term time period.

We conclude that among the subcomponents, corporate governance scores had the greatest predictive power over subsequent stock returns, and the impact of high scores can be seen in longer-term returns of three to five years.

Table X: Average ROE, when Neutral = 0
Table X: Average ROE, when Neutral = 0

The highest ROE in each time horizon are in bold.

The summary table below shows the percentage of sectors where good, neutral, and bad had the highest ROE.

Summary Table 1

The results show that companies with high overall score and social scores have higher subsequent ROE in different time horizons.

Neutral = Score of -1, 0, +1

Table XI: Average Stock Returns When Neutral = -1, 0, +1
Table XI: Average Stock Returns When Neutral = -1, 0, +1

The highest returns in each time horizon are in bold.

With the overall score and the social score, we do not see any clear pattern. The results were surprising for the environment score—bad companies did best. We see clear results with the corporate governance score, where good companies had the highest return over one, three, and five years by a large margin.

Table XII: Average ROE When Neutral = -1, 0, +1
Table XII: Average ROE When Neutral = -1, 0, +1

 The highest ROE in each time horizon are in bold.

With the overall and social scores, good companies always had the highest ROE. For the environment scores, good companies also tended to have higher ROE. The results were surprising for the corporate governance scores—bad companies had the highest ROE. It is important to note that a minority of companies (≅ 1%) had good corporate governance and environment scores, rendering this definition of neutral difficult to interpret and draw conclusions from.

Neutral = Mid One-Third of companies, with the scores sorted

Table XIII: Average Stock Returns When Neutral = Middle One-Third of Scores
Table XIII: Average Stock Returns When Neutral = Middle One-Third of Scores 
The highest returns in each time horizon are in bold.

With the corporate governance score, companies in the good category had the highest return over three and five years by a large margin. For the environment scores we also see that the good or neutral companies always had the highest return. It is important to note the granularity within the scores, particularly for the corporate governance and environment scores, which leads to almost two-thirds of the sample being in the neutral category. This definition also makes time series comparison more difficult because the same score can have different classifications in different years. Therefore, this definition of neutral is difficult to implement as an investment strategy.

Summary Table 2
 

After controlling for the sector effect, the results are very clear for the corporate governance scores where good companies outperformed in 50% or more of the sectors in all time periods. For the Environmental scores, the good or neutral companies had the highest return in the most sectors. With the overall scores, neutral companies did best in the highest number of sectors over the three- to five-year period.

Table XIV: Average ROE When Neutral = Middle One-Third of Scores
Table XIV: Average ROE When Neutral = Middle One-Third of Scores

The highest ROE in each time horizon are in bold.

Note: We did the analysis year-wise to get the overall average for each sector. In some years a sector might have only two scores and hence we could not divide the sector data into three groups and put N/A for that year in our calculations.

For overall and social scores, good companies had the highest average ROE. In an overwhelming majority of sectors, companies with good overall and social scores had the highest ROE. We therefore see a clear association between high overall and social scores and subsequent financial performance in terms of ROE.

Summary of Overall results from Three-Way Classification

We find the definition of neutral = -1, 0, +1 is too broad and leaves few companies in the good category. The definition of neutral = middle one-third is difficult to implement since the granularity in score often leads to a very high percentage to be categorized as neutral. This definition also makes time series comparisons more difficult. Therefore, the definition of neutral = score of 0 is the most meaningful three-way classification.

We can conclude that the corporate governance scores have the maximum information content regarding stock returns—good companies overwhelmingly have the highest stock return. This is true for the overall sample and after controlling for the sector effect. Overall scores and social scores, on the other hand, have a clear effect subsequent ROE, making it higher. Companies with good overall and social scores always have the highest ROE.

The conclusions from the three-way classification are consistent with those from the earlier analysis using continuous scores and the two-way classification of scores—good corporate governance scores have the strongest impact on subsequent stock returns, particularly over the medium to long term. Good overall scores and social scores have the strongest impact on subsequent ROE.

Impact of the Overall and Subcomponent Scores, after controlling for Size Effect

Size or market capitalization is a well-known factor for stock returns. We analyzed whether the predictive power of the ESG factors varies by market capitalization or holds after controlling for size effect. The three market capitalization buckets used were:

(a) greater than $ 9 billion large cap

(b) between $ 5 and $ 9 billion mid cap

(c) between $ 250 million and $ 5 billion small cap.

We excluded the micro-cap companies since they tend to have outlier effects. We only used the definition of neutral = 0.

Table XV: Impact on Stock Returns
Table XV: Impact on Stock Returns
The highest returns in each time horizon are in bold.

Controlling for the size factor, we find that the corporate governance scores and overall scores have the greatest predictive ability on subsequent stock returns. Both these scores have stronger predictive ability as we go down the market capitalization range.

Table XVI: Impact on ROE
Table XVI: Impact on ROE
The highest ROE in each time horizon have been bolded.

The impact of overall score and the social scores are very strong for medium to long term ROE, across all market capitalization groups.

Therefore, our main result—that corporate governance scores are predictive of medium to long term returns, while overall and social scores are predictive of medium to long run ROE—holds true even after controlling for the size effect.

MAIN CONCLUSIONS

ESG scores have predictive power over total stock returns and financial performance measured by ROE. Good companies, defined as those having more strengths than weaknesses in the various ESG fields, tend to have higher medium to long run (three- to five-year) returns and ROE. These results hold even after controlling for the sector effect.

Among the subcomponents of the overall ESG score, corporate governance scores are the best predictor of stock returns, and the predictive power of the corporate governance scores was highest over the longer three- to five-year horizons. Even controlling for the sector effect, corporate governance scores had the highest predictive power for stock returns in the medium to long run, followed by the overall ESG score. This indicates that all subcomponents of overall ESG scores are not equal, and corporate governance practices are most important for stock returns. The social scores have a greater positive impact on subsequent operational results in terms of ROE. The same predictive relationship continues even after controlling for the well-known size effect.

Our results indicate that the business practices of a company in areas like corporate finance, environmental and social practices, as well as whether or not the company operates in controversial/ sin areas, are important considerations from an investment perspective. The corporate governance practices are particularly important for shareholder returns, while social practices are an important predictor of financial performance in terms of ROE. Investment managers can add alpha by incorporating extra-financial factors like the overall ESG score and, more specifically, the corporate governance practices into their investment process.

REFERENCES

Belu, Constantin. and Cristiana Manescu. June 2009. “Strategic Corporate Social Responsibility and Economic Performance.” working Paper, University of Gothenburg. 

Brown, Alan. October 2007 . “An Investment perspective on Climate Change.” Schroders. 

Core, John, Wayne Guay, and Tjomme Rusticus. April 2006. “Does Weak Governance Cause Weak Stock Returns? An Examination of Firm Operating Performance and Investors Expectations.” Journal of Finance,Vol LXI, No 2. 

Derwall, Jeroen, Nadja Guenster, Rob Bauer, and Kees Koedijk. November 2005. “The Eco-Efficiency Premium Puzzle.” Financial Analysts Journal, Vol.61, No. 2. 

Ferreira, Miguel and Laux, Paul. April 2007. “Corporate Governance, Idiosyncratic Risk, and Information Flow.” Journal of Finance,Vol. 62, No 2. 

Gompers, Paul, Joy Ishii, and Andrew Metrick. 2003. “Corporate Governance and Equity Prices.” Quarterly Journal of Economics, Vol.118, No. 1. 

Gottsman, L., and J. Kessler. Fall 1998. “Smart Screened Investments: Environmentally Screened Equity Funds that Perform like Conventional Funds.” Journal of Investing, Vol. 7, No. 3. 

Jiao, lloydk. 2009. “Stakeholder Welfare and Firm Value.” working paper, Rensselaer Polytechnic Institute. 

John, Kose, Lubomir Litov, and Barnard Yeung. August 2008. “Corporate Governance and Risk Taking.” Journal of Finance,Vol. 63, No. 4. 

La porta, Rafael, Florencio Lopez-De-Silanes, Andrei Shleifer, and Robert Vishny. June 2002. “Investor Protection and Corporate Valuation.” Journal of Finance,Vol LVII, No 3. 

Masulis, Ronald, Cong Wang, and Fei Xie. August 2007. “Corporate Governance and Acquirer Returns.” Journal of Finance,Vol 62, No 4. 

Orlitzky, Marc. Fall 2005. “Payoffs to Social and Environmental Performance.” Journal of Investing, Vol. 14, No. 3. 

Shank, Todd, Daryl Manullang, and Ronald Hill. Fall 2005. “Is it Better to be Naughty or Nice?Journal of Investing, Vol. 14, No. 3. 

Statman, Meir. October 2000. “Socially Responsible Mutual Funds.” Financial Analyst Journal, Vol. 56, No. 3. 

Vermeir, Wim, Eveline Van De Velde, and Filip Corten. Fall 2005. “Sustainable and Responsible Performance.” Journal of Investing, Vol. 14, No. 3. 

Waddock, Sandra, and Samuel Graves. 1997. “The Corporate Social Performance—Financial Performance Link.” Strategic Management Journal, Vol. 18, No. 4. 

Waddock, Sandra, Samuel Graves, and Renee Gorski. 2000. “Performance Characteristics of Social and Traditional Investments.” Journal of Investing, Vol 9, No.2.

–Indrani De, CFA, and Michelle R. Clayman, CFA


1 Note that the granularity in scores meant that in some instances the majority of companies were in the neutral category, since all companies with the same score have to be in the same category. This is particularly true for the subcomponent scores. For example, in the case of the corporate governance scores, around 55% of the companies were in the neutral category. In the case of the environmental scores, around 68% of the companies were in the neutral category

2 The strengths and weaknesses analyzed by KLD in the various component areas are listed in the appendix.

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