Special Report. The Emerging Importance of Carbon Emission-Intensities and Scope 3 (Supply Chain) Emissions in Equity Returns

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1 Special Report The Emerging Importance of Carbon Emission-Intensities and (Supply Chain) Emissions in Equity Returns MAY 2015

2 Carbon Intensities & Summary ET Index Research has investigated the relationship between equity returns and carbon intensity. The results indicated that portfolios of low-carbon intensity stocks have outperformed portfolios of high-carbon intensity stocks, and that this outperformance is significant. This relationship is found to persist after controlling for other known risk factors. We find that using emissionintensities leads to the greatest outperformance of lowcarbon intensity over high-carbon intensity portfolios. As the quality of emissions data continues to improve, along with increasing environmental pressure on companies, ET Index Research will continue to monitor how the relationship between carbon intensities and stock returns continues to develop. Key Definitions Carbon intensity Greenhouse gas (GHG) emissions reported by companies in tonnes of CO2 equivalent (tco2e) are then normalised for company size by dividing by million USD of Revenue. This calculation provides an intensity metric in units denoted by tco2e/$m Revenue. ET Carbon Data - The carbon intensity database of ET Index is derived from an in-house analysis of the world s largest listed companies, representing approximately 85% of global market capitalization. Scope 1, 2 and 3 emissions - The ET Carbon Data analysis framework for gathering intensity data is based on the Greenhouse Gas Protocol, the most widely-used international accounting tool for GHG emissions. This protocol categorizes emissions into Scopes 1, 2 and 3: Scope 1 Emissions - All direct emissions. Scope 2 Emissions - Indirect emissions generated from the purchase of electricity. Emissions - All other indirect emissions, both upstream and downstream, such as distribution of goods, transportation of purchased goods, transportation of waste, disposal of waste, employee commuting, business travel or investments. emissions are usually the largest percentage of a company s total GHG emissions. In statistics, the is the ratio of the departure of an estimated parameter from its notional value to the standard error of the estimated parameter. In this report, the estimated parameter is the difference in returns between low-intensity and high-intensity portfolios. The notional value to which this return difference is compared is 0%. Statistically significant In this report statistical significance is reported at the standard 5% level. At this level a return difference is statistically different from 0% if its is greater than Return differences with this level of are highlighted in the tables below. This type of statistical significance means that, if the return difference is actually 0%, then we would only expect to observe such return differences with this level of absolute magnitude (of either positive or negative sign) 5% of the time. The same return difference is statistically positive if its is greater than This means that if the return difference were actually 0%, then we would only expect to see such large, positive return difference 5% of the time. Data Carbon intensities for 2267 stocks from 2008 to 2015 were obtained from the ET Carbon Data greenhouse gas emissions database. Series of weekly total returns, price-to-book ratios (PB), and market values (MV) were obtained from Reuters for each stock from January 2009 to March

3 Carbon Intensities & Method & Results To examine the effect of carbon intensity on stock returns, each week stocks were divided into equallyweighted portfolios with different characteristics. The difference in returns between these portfolios was then computed. To check for statistical significance, s were calculated from Newey-West standard errors. These standard error estimates correct for autocorrelation (correlation across time) and heteroskedasticity (changing volatilities) in the returns. To avoid look-ahead bias, all groupings were made using measures computed on the basis of the past week s information. The returns presented in the tables are annualised returns. First, to examine the effect of carbon intensity across the whole sample, stocks were sorted into four quartiles on the basis of their individual carbon intensities. This sorting was done using each of three intensity options: Scopes 1, 2 & 3 together, just Scopes 1 & 2, and just. The results of the whole sample analysis are presented in Table 1 (overleaf). In this and subsequent tables, refers to the return differential between the portfolios formed by the lowest intensity quartile and the highest intensity quartile. It can be seen that low-carbon intensity firms earn higher returns than high-carbon intensity firms. This return differential is positive across all three of the intensity options, and it is statistically significant for the and Scope 1, 2 & 3 intensity options. Figure 1 shows the performance of the lowest-intensity quartile against the highest-intensity quartile, when using intensities across the whole sample. It can be seen that the return differential between the low and highintensity portfolios has existed from the beginning of the sample period, and it has continued to increase right to the end of the sample period. Fig. 1 Performance of low-carbon versus high-carbon intensity portfolios, using intensities. 3

4 Carbon Intensities & Table 1 Whole sample carbon intensity return differences. Type 7.2% 2.80 Scope 1 & 2 4.8% 1.83 Scope 1, 2 & 3 5.4% 2.11 Conditional Tests Next, to examine if the intensity return differential continues to exist after controlling for known risk factors, each week stocks were first sorted into four quartiles on the basis of the value of a known financial metric in the previous week. Subsequently, each portfolio was sorted into quartiles on the basis of carbon intensity. The financial metrics used were price-to-book ratio (PB), a proxy measure for exposure to the value risk factor, and Market Value (MV), a proxy measure for exposure to the size risk factor. Table 2 (overleaf) presents the results for PB- and MV-controlled portfolios using intensities. Table 3 presents the same results using Scope 1 & 2 intensities, and Table 4 presents the results using Scope 1, 2 & 3 intensities. It can be seen that the intensity return differential is strongly positive and statistically significant even after controlling for size (MV). After controlling for value (PB), the effect remains positive for all PBquartiles, but is only statistically significant for the lowest quartiles. The Scope 1 & 2 intensity effect is also positive for all quartiles. But in contrast to the intensity effect, the Scope 1 & 2 intensity return differential is only statistically significant for two of the MV-quartiles, and one PB-quartile. The result for the combined Scope 1, 2 & 3 intensities is again positive for all quartiles, but only statistically significant for three MV-quartiles. To further examine the differences between and Scope 1 & 2 intensities, stocks were first sorted into Scope 1 & 2 quartiles and then subsequently sorted into quartiles. Sorts based on the reverse order, followed by Scope 1 & 2, were then conducted. The results are displayed in Table 5. It can be seen from Table 5 that after controlling based on intensities, Scope 1 & 2 intensities have no statistically significant relationship to returns. However, after controlling based on Scope 1 & 2 intensities, intensity still has a strongly positive and statistically significant relationship to returns in the 3rd and 4th Scope 1 & 2 intensity quartiles. Figure 2 and Figure 3 show the performance of the lowest and highest intensity portfolios for these 3rd and 4th quartiles of Scope 1 & 2 intensity. It can be seen that the intensity return differential for these quartiles develops in 2011 and 2012 for these quartiles. The return differential then continues to expand to the end of the sample in Conclusion Across the whole sample it has been found that there is a statistically significant return differential between low and high-carbon intensity stocks. This differential is greatest when intensities are used. The return differential is robust to controlling for size effects, and remains significant for stocks in the lowest and second lowest value quartiles. 4

5 Carbon Intensities & Additionally it has been shown that using intensities leads to a significant return differential after controlling for Scope 1 & 2 intensity, but the reverse is not true. Thus, the conclusions are as follows: 1. ET Index Research has found that there is a carbon intensity effect in the cross-section of equity returns from 2009 to This effect is strongest for intensities. Scope 1 & 2 intensities produce a weaker effect. 3. The effect is robust to controlling for size effects, and remains (with weaker statistical significance) after controlling for value effects. Additionally, it should be noted that as the carbon efficiency of companies becomes an increasingly well reported and analysed metric it can be expected that the returns of low-efficiency, carbon-intensive stocks will continue to suffer more and more. Possible evidence of a shift in this direction is provided by Figure 2 and Figure 3, where it can be seen that prior to 2011 there was no significant return differential between low and high intensity portfolios (after controlling for Scope 1 & 2 intensity). However, since 2011 the return differential has continued to grow. It will be interesting to continue to monitor the developing relationship between carbon intensities and equity returns. Table 2 intensity effect controlled by other risk factors. Panel A: controlled by MV MV Q1 Q1 Q2 Q3 Q4 50.1% 46.2% 41.7% 28.8% 21.3% 4.18 MV Q2 24.5% 26.5% 23.8% 17.8% 6.7% 2.11 MV Q3 19.8% 20.9% 16.1% 11.8% 8.0% 3.08 MV Q4 14.7% 16.5% 13.1% 6.9% 7.9% 2.73 Panel B: controlled by PB Q1 Q2 Q3 Q4 PB Q1 35.8% 29.7% 21.8% 17.4% 18.3% 2.37 PB Q2 22.5% 21.6% 22.9% 15.7% 6.8% 1.97 PB Q3 21.6% 26.8% 23.0% 17.6% 4.0% 1.39 PB Q4 23.2% 28.8% 20.9% 21.0% 2.2%

6 Carbon Intensities & Table 3 Scope 1 & 2 intensity effect controlled by other risk factors. Panel A: controlled by MV MV Q1 Q1 Q2 Q3 Q4 42.6% 44.0% 49.3% 30.6% 12.0% 2.95 MV Q2 25.1% 24.8% 25.8% 16.9% 8.2% 2.12 MV Q3 18.5% 18.5% 19.3% 12.0% 6.5% 1.70 MV Q4 14.9% 15.6% 13.4% 7.4% 7.5% 1.74 Panel B: controlled by PB PB Q1 Q1 Q2 Q3 Q4 24.2% 30.7% 29.9% 19.2% 5.0% 0.88 PB Q2 23.6% 22.5% 20.3% 16.4% 7.2% 2.30 PB Q3 20.9% 22.4% 26.5% 19.1% 1.8% 0.57 PB Q4 21.7% 26.4% 26.7% 19.1% 2.6% 0.90 Table 4 Scope 1, 2 & 3 intensity effect controlled by other risk factors. Panel A: controlled by MV MV Q1 Q1 Q2 Q3 Q4 43.9% 42.6% 50.6% 29.6% 14.4% 3.49 MV Q2 24.2% 24.6% 28.3% 15.6% 8.6% 2.41 MV Q3 19.2% 19.1% 19.0% 11.2% 8.0% 2.31 MV Q4 15.6% 14.8% 12.1% 8.7% 6.9% 1.54 Panel B: controlled by PB PB Q1 Q1 Q2 Q3 Q4 27.2% 31.3% 25.4% 20.0% 7.3% 1.20 PB Q2 21.6% 21.8% 23.6% 15.5% 6.1% 1.86 PB Q3 21.0% 23.8% 25.0% 19.0% 2.0% 0.68 PB Q4 23.1% 26.2% 23.8% 20.5% 2.7%

7 Carbon Intensities & Table 5 Scope 1 & 2 intensity vs intensity. Panel A: controlled by Scope 1 & 2 Scope 1 & 2 Q1 Scope 1 & 2 Q2 Scope 1 & 2 Q3 Scope 1 & 2 Q4 Q1 Q2 Q3 Q4 ( ) 23.5% 22.4% 22.3% 25.7% -2.2% % 28.1% 28.1% 21.7% -0.6% % 31.3% 30.9% 16.9% 11.5% % 15.5% 11.1% 17.7% 9.5% 2.20 Panel B: Scope 1 & 2 Intesnity controlled by Q1 Q2 Q3 Q4 Scope 1 & 2 Q1 Scope 1 & 2 Q2 Scope 1 & 2 Q3 Scope 1 & 2 Q4 (Scope 1 & 2 ) 24.4% 25.0% 26.0% 29.5% -5.2% % 26.0% 28.3% 28.2% 0.3% % 20.2% 24.2% 19.0% 1.0% % 19.7% 10.6% 16.6% 8.0%

8 Carbon Intensities & Fig. 2 Performance of low-carbon versus high-carbon intensity portfolios, using Intensities for stocks in the 3rd quartile of Scope 1 & 2 intensity. Fig. 3 Performance of low-carbon versus high-carbon intensity portfolios, using Intensities for stocks in the 4th quartile of Scope 1 & 2 intensity. 8