Abstract
Using a new dataset of environmental, social, and corporate governance company ratings for the European market, this article examines whether socially responsible stock selection adds or destroys value in terms of portfolio performance. From 2004 to 2012, we find the following: (i) Negative screens excluding unrated stocks from a representative European stock universe allow investors to significantly outperform a passive investment in a diversified European stock benchmark portfolio. (ii) Additional negative screens based on environmental and social scores neither add nor destroy portfolio value, when cut-off rates are not too high. In contrast, governance screens can significantly increase portfolio performance under similar conditions. Thus, investors in the European stock market can do (financially) well while doing (socially) good. (iii) Because of a loss of diversification, positive screens can cause portfolios to underperform the benchmark. This implies that investors should concentrate on eliminating the worst firms. (iv) Our results are robust along several dimensions, namely, choice of performance measure, time, test parametrisation, portfolio weighting scheme, approximation of the risk-free rate, and consideration of transaction costs.
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Notes
One might also argue that monitoring, relevant for implementing SRI screens, negatively affects investment performance. However, for institutional investors, the corresponding costs are negligible because ESG company ratings are provided by specialised rating agencies against payment of relatively small fees.
For the exceptions France, Ireland, Sweden, and Japan, Renneboog et al. (2008b) show that SRI can lead to significant underperformance.
The fact that SRI funds gradually converge to conventional funds is also supported by a subsample factor analysis performed by Renneboog et al. (2008b).
Derwall et al. (2011) review the results of the most influential studies in this area and also provide a short list of studies covering markets other than the US and Europe.
Exclusionary investing is also typical for ‘green investors’ that eliminate polluting firms from their portfolios (see Heinkel et al. 2001).
For a long time, the Sharpe ratio was thought to be inadequate if returns deviate from a normal distribution. However, recent research highlights that the measure has a decision-theoretic foundation for a wide range of (skewed and fat-tailed) non-normal distributions (see Schuhmacher and Eling 2011, 2012).
In general, corporate governance can be defined as the design of institutions that induces or forces management to internalise the welfare of the investors (see Tirole 2001). Thus, it addresses the conflicts of interests between investors and managers that are well-known from classic principal-agent theory (see Laffont and Martimort 2002).
Kempf and Osthoff (2007) and Hong and Kacperczyk (2009) obtain data on social responsibility from KLD Research & Analytics, Wimmer (2013) uses the ASSET4 database of Thomson Reuters, Velde et al. (2005) use ratings from the research firm Vigeo, and Brammer et al. (2006) base their study on data from the Ethical Investment Research Institute Services (EIRIS). We cannot use these sources in our study because they do not provide a coverage of the European stock market that is comparable to the one offered by Sustainalytics.
The environmental score is built by analysing the subtopics operations, supply chain, and products & services. Social (Governance) scores are constructed using indicators concerning the themes employees, supply chain, customers, and community & philanthropy (business ethics, corporate governance, and public policy).
The Equator Principles describe ‘a risk management framework ... for determining, assessing and managing environmental and social risk in projects and is primarily intended to provide a minimum standard for due diligence to support responsible risk decision-making’ (see www.equator-principles.com).
This project reflects ‘a global system for companies and cities to measure, disclose, manage and share vital environmental information’ (see www.cdp.net).
The information presented in the preceding paragraphs stems from internal documents supplied by Tamara Hardegger at Sustainalytics.
The STOXX 600 represents large, mid and small capitalisation companies across 18 countries of the European region: Austria, Belgium, Denmark, Finland, France, Germany, Greece, Iceland, Ireland, Italy, Luxembourg, the Netherlands, Norway, Portugal, Spain, Sweden, Switzerland and the United Kingdom.
The 6 months requirement is introduced because some of our used unbiased estimators (e.g., for kurtosis) require certain minimum numbers of observations. It reduces the actual constituent list of 947 companies by 55.
These percentages are obtained as follows: For each stock, we count the number of changes in the ratings and divide them by the total number of observation periods. The average of the resulting numbers is then multiplied by 100 to yield the stated frequencies.
Nonetheless, we analyse their performance impact in a robustness check in the "Other Robustness Checks" section.
One could alternatively compute the time averages of cross-sectional correlations. However, both approaches yield very similar results.
All correlation coefficients are significant at conventional significance levels (1, 5 and 10 %) when the classic correlation test described in Kanji (2006, p. 38) is applied.
Since 2014 Sustainalytics covers all companies of the STOXX 600. However, Sustainalytics does not backfill prior data when a company is added to the research universe. Thus, our analysis is only based on information that was available to investors when the investment decisions were made.
Note that the relatively large finance weight occurs because FactSet uses the term finance to group banks, insurance companies and related sectors.
In detail, they show that portfolios of firms with high environmental scores significantly outperformed portfolios with low scores in terms of alpha performance. Similar approaches are used by the studies cited in the following two paragraphs.
Note that identical Sharpe ratio differences do not imply identical p values. Different cut-offs lead to different portfolio return characteristics that can induce a higher or lower standard error of the difference estimator.
In line with Gompers et al. (2003), these results are not driven by size or book-to-market effects because correlations between our ESG scores and these measures are insignificant. Thus, the performance of the governance screen is not caused by reducing the investment universe to stocks with low market capitalisation or high book-to-market ratios. For details on these effects see Liew and Vassalou (2000) and Artmann et al. (2012). However, it is important to note that there may be a relation to other factors not covered by our study. In this respect, a more detailed analysis that requires the construction of sophisticated multifactor models for the European market would be an interesting topic for future research.
In order to make a more profound statement for the European market, the calculation of cost of capital estimates using state-of-the-art techniques is required. However, this is beyond the scope of this article and is left for future research.
Note that we also implemented all measures carried together in the studies of Eling and Schuhmacher (2007) and Schuhmacher and Eling (2011, 2012). However, their outcomes provide similar conclusions. For full transparency, the source codes for our performance measure calculations are available upon request.
In contrast to the Sharpe ratio, no comparable state-of-the-art procedures for testing performance differences are available for the alternative performance measures. Thus, we are restricted to a mere descriptive analysis.
Alternatively, we could follow Bauer et al. (2005), Kempf and Osthoff (2007) and Renneboog et al. (2008b) by subdividing our sample in two or more periods of equal length and repeating our calculations within those subsamples in order to analyse the persistence of relative portfolio performance. We could also use a rolling-window approach instead of the growing-window approach. However, results are similar.
Note that similar arguments hold for the other years after 2009. The corresponding magnified graphs are available from the authors upon request.
We do not analyse the effects of a best-in-class approach—a certain type of popular positive screen assuring that a resulting portfolio is balanced across industries (see Kempf and Osthoff 2007). This is because it cannot be applied for some of the portfolio sizes we use. Additionally, forcing all industries to be represented in a portfolio may lead to the inclusion of low-rated stocks in an otherwise high-rated ESG portfolio and thus be in conflict with the ethical goals of a socially responsible investor.
As the results of these robustness checks do not provide any additional valuable insights, we concentrate on verbally summarising their main implications. Detailed results are available upon request.
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The author thanks an anonymous reviewer for highly valuable comments and suggestions. Special gratitude goes to Dirk Söhnholz (Veritas Investment GmbH) and Hauke Hess (Pall Mall Investment Management GmbH) for financial support and assistance in the data preparation process, respectively.
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Auer, B.R. Do Socially Responsible Investment Policies Add or Destroy European Stock Portfolio Value?. J Bus Ethics 135, 381–397 (2016). https://doi.org/10.1007/s10551-014-2454-7
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DOI: https://doi.org/10.1007/s10551-014-2454-7