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Accepted with revisions for Journal of Industrial Ecology – DO NOT CITE ORDISTRIBUTE.

Do conventional and sustainability investment fundsdiffer in their environmental impacts? – Acomparison by means of Input-Output Life CycleAssessment

Thomas Koellner1) 2), Sangwon Suh3) 4), Olaf Weber1) 2, Corinne Moser5) and RolandW. Scholz1)

1) Swiss Federal Institute of TechnologyDepartment of Environmental ScienceNatural and Social Science Interface (ETH-NSSI)ETH-Centre HAD F2CH-8092 Zurich, Switzerland

thomas.koellner@env.ethz.chTel: 0041 (1) 632 63 11Fax: 0041 (1) 632 10 29

2) GOE m.b.H, Zurich, Switzerland

3) Department of Bio-Based Products, College of Natural Resources, University ofMinnesota, USA.

4) Institute of Environmental Sciences (CML), Leiden University, The Netherlands.

5) Care Group AG, Zurich, Switzerland

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Abstract

This study is to compare equity funds, which are managed according to sustainability goals,

with conventionally managed funds with respect to their environmental impacts. The basic

motivation for this study was the conjecture that overlap in the portfolios of sustainability

funds and conventional equity funds can be very large. In addition, the sector allocation of

both types of funds is generally very similar, because portfolio managers follow the chosen

benchmark to minimize risk. These two effects can result in no differentiation between the

two types of funds in terms of their environmental impact and damage (null hypothesis). The

goal of the study is to comparatively assess the environmental impact of portfolios of 26

investment funds. We selected 13 sustainability funds and 13 conventional funds, which are

managed according to the benchmark MSCI World. The study applies Input Output Life

Cycle Assessment (IO-LCA) in combination with a simulation of company-specific

environmental performance. The environmental impact is evaluated per functional unit for

each fund, which is the risk-adjusted financial performance. The statistical analysis showed

that the analyzed sustainability funds performed better with respect to environmental impact

assessment but worse in economic risk adjusted performance (RAP) over the period 2000-

2004. In 2004, however, the RAP of the selected sustainability funds showed a better

performance. Both samples considerably overlap for the environmental and economic

parameter. The results suggest that the environmental impact of sustainability funds in the

sample is slightly less than that of conventional funds.

Keywords: Socially responsible investments, SRI, funds, sustainability, impact assessment,

ethical, ecological performance, Input-Output Life Cycle Assessment

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Introduction

Investors, both private and institutional, are beginning to integrate socio-economic and

ecological criteria into their investment decisions (Kasemir et al. 2001). The supply of

investment funds in the ‘green’ and ‘socially responsible’ investment sectors has increased

correspondingly. In Europe, 313 sustainability funds were available in 2003 (SRIcompass

2005). Equity and bond funds serving this rapidly growing segment of global capital markets

range from ethical funds to eco-efficiency funds to sustainability funds. Only sustainability

funds take simultaneously ethical, socio-economic, and ecological aspects into account. The

term socially responsible investment, or SRI, is used widely for this asset class; we avoid this

misleading term, because in reality, what is labeled SRI also includes environmentally

responsible investments (for further discussion see also O’Rourke 2003).

Due to increasing demand on stock markets such sustainable investments increase the

price per share and thus the market capitalization of companies rated sustainable.

Consequently, it is easier to increase equity capital through release of new shares at a higher

price. In addition, cost of equity and cost of loan capital can be reduced (Aslaksen and

Synnestvedt 2003; Heinkel et al. 2001; Barnea et al. forthcoming).

Currently, fund managers of sustainability funds can mainly contribute to sustainable

development through three mechanisms. First, through sustainability rating and

communication with the rated companies, they can directly push the company management

towards more sustainable practice. Second, representing shareholders, the fund manager can

influence companies by proxy voting according to sustainability issues at shareholder

meetings (Monks et al. 2004). Third and most important, they construct the portfolios of

stocks and bonds based on negative screenings–e.g., no alcohol, no weapons, no nuclear

power–or positive screenings–e.g., best practice environmental management, low emissions

(Jayne and Skerratt 2003).

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However, managers of sustainability funds are restricted by several side constraints,

which limit their degree of freedom in portfolio construction. In general, they construct

sustainability funds in a way to be comparable to a conventional investment fund. They often

choose conventional indices (e.g., S&P 500, DJGI, MSCI, Fortune 500) as a starting

investment universe from which to select appropriate stocks for their portfolio. In addition,

they often rebuild the sector allocation of the chosen index in order to arrive at a risk structure

comparable to conventional funds. The motivation to approximate conventional funds comes

from the fund managers’ assumption that their target investors expect financial return and

sector allocation similar to conservative investments..

The result of these factors is that the portfolios of sustainability funds can be more

similar to those of conventional funds than one would expect. Hawken (2004) found that

more than 90% of the companies of the conventional index Fortune 500 are included in the

cumulative portfolio of 399 sustainability investment funds. In other words, by mere chance

every conventional fund portfolio can contain stocks that were rated as sustainable. While

every conventional fund can contain stocks that are rated sustainable, the only difference

between sustainable and conventional funds is relative stock weightings in the portfolio. What

then, compared to conventional ones, is the value added of constructing sustainability fund

portfolios? This question has been intensively investigated in terms of the financial

performance of funds (Statman 2000; Plantinga and Scholtens 2001; Bauer et al. 2005;

Schröder 2003) and indices (Cerin and Dobers 2001). A comprehensive assessment of

sustainability funds, however, should also focus on their ecological and socio-economic

performance (for a complete framework for sustainability ratings of investment funds see

Koellner et al. 2005). Accordingly, Dillenburg (2003) discussed how to assess the total social

impact of funds, and Hallerbach (2004) suggested a multi-criteria decision framework to

measure the different attributes of a SRI portfolio. Nevertheless, until now an operational

method for assessing the socio-economic and ecological performance of stock portfolios has

been missing.

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The main goal of our paper is to develop a metrics for the ecological performance of

investment funds being an important aspect of sustainability. The method is based on

environmental ratings of the companies found in the portfolios and Input-Output Life Cycle

Assessment (IO-LCA), which allows the environmental impact (e.g., emission of greenhouse

gases in tons) of a $1000 investment into a specific equity fund to be evaluated based on its

industry allocation.

We develop our thesis as follows. We explain the methodology applied, especially

the calculation of environmental performance based on environmental ratings and IO-LCA.

IO-LCA is used because it provides comprehensive information on the environmental impact

of industries. Then, the results for the economic and environmental performance for 13

conventional funds and 13 sustainability funds, both managed according to the benchmark

MSCI are presented and statistically compared. As a prerequisite, we investigate the overlap

of the portfolios of conventional funds and sustainability funds with cluster analysis. Finally,

we discuss the results with respect to their significance and methodological problems and

research opportunities.

Method

Sector allocation and financial performance for selected funds

Out of an extensive list of sustainability funds–based on listings in the category ethical funds

in the Bloomberg database and from other databases (SRIcompass.org and Morningstar)–we

have selected all sustainability equity funds in German speaking countries, that are managed

according to sustainability and ecological criteria and use the index MSCI World as a

benchmark. This index is maintained by the Morgan Stanley Capital International and is

composed of 1549 companies of developed countries. To compare the 13 sustainability funds

with conventional equity funds, we have randomly selected 13 conventional funds also

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managed according to MSCI World from the Bloomberg database (see Annex 1 for fund

names and basic information).

For each equity fund, we requested the total portfolio from the fund company,

including all stock names and the proportion of each stock. Every fund company was

cooperative, but it was not possible to receive the portfolio composition for one effective day

(in fact, it was between August 31, 2004 and December 1, 2004). To assess whether the

sustainability funds and the conventional funds could be separated into two clusters based on

their portfolios (name of each stock and its individual weight in the fund’s portfolio,) we

performed a cluster analysis (squared Euclidian distances calculated with the Ward method in

SPSS 11 from SPSS Inc. Chicago).

We compiled an extensive database with information on 3538 companies in terms of

their sector and industry membership listed in Annex 2 according the Global Industry

Classification System (GICS) (Anonymus 2005). The data for the companies were extracted

from a set of indexes (MSCI World, MSCI Europe, MSCI Small Cap, DJ Stoxx

Sustainability, DJ Sustainability indexes, FTSE4 Good Europe 50 Index) we received from

Thomson Financials and the Bloomberg database. Using this as our base, the sector and

industry allocation of each fund was calculated.

In order to compare the financial performances of conventional and sustainability

funds, we have selected the relative return of the fund portfolio

�

RP , volatility

�

σ P , and risk-

adjusted performance RAP.

�

RP is calculated as

�

RP =NAVt − NAVt−1

NAVt−1

Equation 1

where NAV is the net asset value at time t. Volatility

�

σ P is calculated as the standard

deviation of RP . In addition, the risk-adjusted performance RAP was calculated with the

EnCorr Analyzer, according to Modigliani and Modigliani (1997). It compares performances

after properly adjusting the portfolio return for risk and is calculated as

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RAP = (RP − Rf ) ⋅σ I

σ P− f

+ Rf

Equation 2

where

�

RP − Rf is the excess return of the portfolio in comparison to a risk-free return;

�

Rf ,

�

σ P − f is the excess return; and

�

σ I , the volatility of the excess return of Index I. For the

calculation of the RAP, the MSCI World Total Return Index (USD, Bloomberg Ticker

NDDUWI Index) was used as benchmark. The risk-free rate was 4.21% (Bloomberg January

14th, 2005, function CRP). All RAP values were calculated per annum based on monthly data

and the arithmetic mean of the data.

All financial performance data of the selected funds were received from the

Bloomberg database for three periods (1/2004-12/2004, 1/2002-12/2004, and 1/2000-

12/2004), because the due to difference in sector allocation funds are expected to perform

differently in the three periods of stock market development. We compared the sustainability

funds with the conventional funds with respect to differences in the means of the financial

performance, using a t-test with SPSS 11.

Mean environmental ratings of equity funds

To quantify and compare the environmental performance of conventional and sustainable

fund portfolios, we have two data sources. One source is environmental ratings for the

companies in the portfolios and the other is the environmental impact and damage of the

portfolio based on its industry allocation, which is calculated with Input-Output Life Cycle

Assessment. We distinguish environmental impacts (e.g., emission of greenhouse gases in

metric tons and energy used in GJ) from environmental damages (e.g., human health damage

in Ecoindicator points), because the former is often reported in corporate environmental

reports and the latter gives a very comprehensive overall measure. The Ecoindicator method

is a widely used impact assessment practice in the framework of Life Cycle Assessment

(Pennington et al. 2004; Goedkoop et al. 1998).

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The environmental ratings r were obtained from the SIRI Group (provided by

CentreInfo, Freiburg, Switzerland) for 413 companies in the MSCI World index. These

covered 37% of the 1131 companies found in the portfolios of the 26 equity funds

investigated. Specific criteria of the rating done by the SIRI Group include the availability of

public reports on environmental issues as well as the scope of environmental principles,

policies, and management systems. For each of the assessment criteria up to eleven indicators

are defined and assessed based on existing information (e.g., existence of environmental

report, yes-no). The results are transformed into a value ranging from 1 to 10. In addition,

environmental data, including activities that are controversial in terms of environmental

pollution (e.g., oil spills) and products, which are beneficial to the environment or lead to a

reduced environmental impact, are evaluated. All these data are aggregated into one rating

between 1 (very bad) and 10 (very good). The ratings for the 413 companies are distributed

normally with a mean of 5.31 and standard deviation of 1.92.

In order to compare of the conventional funds with the sustainability funds, we

pooled the 13 conventional portfolios into one pooled portfolio funds and the 13 sustainability

funds into another portfolio of funds. We then tested the equality of the means of the

environmental ratings of the two funds of funds with a t-test and the equality of variance with

a Levene’s test. The hypothesis is that the mean environmental rating of the pooled portfolios

of sustainability funds is better and the standard deviation of the ratings is more narrow,

because companies with bad ratings are omitted.

Assessment of the environmental impacts and damage of an investment in anequity fund using Input-Output Life Cycle Assessment

The challenge, in assessing the environmental impact and damage of investment funds, is the

large number of companies in the portfolios. For the 26 portfolios investigated here, we

would need to assess 1131 companies. Given the present data quality of environmental

reporting on emissions and resource use, this would not be possible. We, therefore, develop

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the method such that no physical inventory data need to be gathered. We used the Input-

Output Life Cycle Assessment (IO-LCA) to assess fund portfolios in terms of absolute

environmental impacts and damage. The method combines economic Input-Output tables and

Life Cycle Assessment (Joshi 1998; Hendrickson et al. 1998; Suh and Huppes 2002; Lenzen;

Suh 2004b). For theoretical background on Input-Output economics refer to Suh (2005b).

With this method, we can base the assessment of a company on their industry membership

(see Annex 2) and monetary information from publicly available sources. Although it is clear

that the large number of companies currently cannot be assessed individually based with a

LCA, we did include company specific ratings on environmental management and some

environmental key figures for about half of the companies in order to account for differences

of companies in one industry.

System border: Another advantage of the method is that input-output tables reflect

the exchange between economic sectors and industries; therefore, the environmental impact

and damage calculated for a company includes its complete supply chain. This enhances the

comparability of companies within a single industry, which can vary significantly in the

extent of their value chain. This means also that the outsourcing of a specific division, which

is for example energy intensive, does not influence the calculated environmental impact of a

specific company. The disadvantage of the IO-LCA is clearly that the use phase and end-of-

use phase are beyond the system border.

Functional unit: In the LCA framework, the functional unit is a measure of the

performance of the functional output of the product system (ISO 1997). The functional output

of investment products is an expected financial return on the capital invested. We have chosen

the risk-adjusted performance (RAP) as the functional unit, because it takes the financial

return and the risk into account. It is possible to compare investment funds with different

return/risk profiles based on their environmental impact and damage standardized per 1 %

RAP.

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Quantification of impacts and damage of an investment in a fund: In order to

develop a method for quantification of environmental impacts and damage, we clarify the

links between the investment market and the consumer market. The operation of an

investment itself has minor environmental impacts in terms of paper use and energy use in

banks. What is important is the link to the consumer market and, thus, to the activity of the

companies invested (Figure 1).

Our argument is that investors become shareholders of a portfolio of companies by

buying one unit of an investment fund. As a shareholder, they own a (small) part of each

company i, and as a consequence, take part in the economic success or failure of that

company. Being joint owners, they are also partially responsible for the environmental

impacts and damage D caused by the companies as a result of their operational activity (for

simplicity, we only refer to the damage D in the development of the method, but the equations

apply equally to the impacts).

Insert Figure 1 here

Based on the total net asset value N of the investment fund in $ and the market capitalization

M of company i in $, it is possible to calculate the relative ownership S of company i (see

Figure 1, Investment Market portion). Knowing the weight wi of each company in the fund’s

portfolio, the relative ownership or percent share Si is calculated as

�

Si =wiNMi

Equation 3

For each company, we calculated the total environmental damage

�

Ditotal

�

Ditotal = d jTi Equation 4

where dj is the environmental damage caused by the purchase of $1 of goods and services

from industry j and Ti, the turnover (sales) of company i. This equals the sum of the cost of

goods purchased (COGS) and the value added (see Figure 1, Consumer Market portion). The

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proportion of the total environmental damage Dik for an individual company i found in fund

k is calculated as

Dik = DitotalSi Equation 5

and the total damage D of fund k as

Dk =i=1

n

∑ DitotalSi .

Equation 6

Since the total market capitalization of funds differ, the normalized damage Dknorm for an

investment of $1000 in a fund k is calculated and used for statistical analysis. In order to

calculate the environmental damage per functional unit Dkrel , we built the ratio of Dk

norm and

the risk-adjusted performance RAP of fund k.

Dkrel =

Dknorm

RAPk

Equation 7

Data sources for calculating environmental impacts and damages: We have

obtained the data on the environmental impacts and damage associated with $1 in purchases

of goods and services from a specific industry in producer prices from two databases–the

EIOLCA (Carnegie Mellon University - Green Design Initiative 2003) and CEDA (Suh

2005a; Suh 2004a). EIOLCA uses the US 1992 annual input-output data and CEDA those for

the US from 1998. We matched the 78 sectors of EIOLCA and the 81 sectors of CEDA with

the 62 GICS (Anonymus 2005) industries as properly as possible.

Data on environmental impacts (greenhouse gases in metric tons CO2 equivalents,

water used in 1000 liters, ores used in metric tons, energy used in GJ, external cost in $) were

obtained from the EIOLCA database. The environmental damage (human health damage in

Ecoindicator EI points, ecosystem quality damage in EI points, resource damage in EI points)

came from CEDA. Based on the three types of damage, we calculated the total environmental

damage in EI points according to Goedkoop and Spriensma (1999, pp 96) based on the

European normalization (hierarchist) factors per inhabitant (damage to human health 1.54E-

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02 Daly/yr, damage to ecosystem quality 5.13E+03 PDF*m2*yr/yr, damage to resources

8.41E+03 MJ/yr, and with 3.8E+8 inhabits in Europe) and the weighting factors for

hierarchists (ecosystem quality 40%, human health 30%, resources 30%).

Correction of average environmental damages for industries with companyspecific environmental ratings

Since we used IO-LCA, the damages calculated for companies are only a function of the

industry they belong to. However, the level of environmental impacts and damage per

functional unit can considerably vary within one industry from company to company. To

account for those differences in companies within an industry with respect to the

environmental impacts and damage they produce, we integrated company-specific ratings ri

on the environmental management and environmental performance of 413 companies.

Because the company ratings are on a standardized scale between 1 and 10 it is not

possible to directly quantify on a metric scale the difference of environmental impacts and

damages between a company rated with e.g., 5 to one rated with 7. For this reason we

conducted a robustness check where we vary the level of differences between the differently

rated companies. This allows to calculate changes in environmental damage ΔDi of

companies i, depending on their ratings ri. Companies rated “good” receive a damage

reduction relative to the industry average and companies rated “bad”, an extra damage. We

calculated this for four levels of correction factors y (y = 2.00, 1.00, 0.50, and 0.25) to check

for the robustness of the calculation. The factors are chosen to reflect moderate to extreme

ΔDi due to differences of environmental ratings. The damage Diy for company i was

calculated as

Diy =

Di  if ri =∅

Di +5 − ri10

yDi  if ri ≥ 1

⎧⎨⎪

⎩⎪ 

Equation 8

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where ri is the rating of the company i. This means that in the case of companies that didn’t

have any rating available, the original damage value

�

Di was taken. For all companies with a

rating, the damage value was adjusted. Taking the correction factor of 1.00 as an example in

Figure 6, companies rated with the mean rating of 5 receive no change (industry average); the

companies rated as best, receives a reduction by the factor 0.50 and companies rated worse

than 5 receives an increase of its damages. Based on the values of Diy   the total damage Dk

y

for an investment of $1000 in each fund k was calculated according to Equation 6.

Results

Portfolio composition and sector allocation of investment funds

In our investigation, we have focused on equity funds, which are managed using the MSCI

World as the benchmark. In general, portfolio managers attempt to follow the chosen

benchmark in the sector allocation. One would expect that sector weights do not differ

between benchmark and funds. However, the sector weights can vary considerably from fund

to fund (Table 1). Mean sector weights of the benchmark deviate from sector weights of

conventional funds and sustainability funds. Compared to conventional funds, sustainability

funds underweighted the sectors Energy and Consumer Discretionary. In contrast, Industrials

are overweighted, probably because they include environmental friendly industries (e.g,,

production of solar panels). Only the weights for Industrials show significant differences

(multivariate ANOVA, p = 0.018).

The 13 conventional funds consist of many more stocks than the 13 sustainability

funds (1877 to 1085). Particularly in the sectors Materials, Consumer Discretionary,

Financials, and Energy, the sustainability funds consist of fewer stocks. As a consequence, in

those sectors the average weight of stocks in a conventional fund is lower compared to the

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weight in a sustainability fund. All of the investment funds were clustered according to the

portfolio composition (name of the stock i and its individual weight wi in the fund’s

portfolio) (Figure 2). The results didn’t reveal any separation into two distinct clusters as

expected (one cluster for conventional funds and one for sustainability funds), but brought to

light some interesting insights. Funds Sust 2, Sust 3, and Sust 4 form one narrow cluster which

can be explained by the fact that they are all managed by one company. Together with fund

Sust 11–its portfolio focused on companies dealing with water issues–they form another

cluster, which is furthest from that of all of the other funds. All of the other funds form one

cluster, which breaks down into rather homogenous sub-clusters of sustainability or

conventional funds. The cluster analysis also shows that funds Sust 1 and Sust 9 are almost

equal, in spite of the fact that they are managed by two different companies, one from

Switzerland and one from Austria (in fact, Sust 1 is a clone of Sust 9).

Insert Table 1 here

Insert Figure 2 here

Financial performance of investment funds

The mean of the absolute RAP is lower for sustainability funds for 4 years backcasting

(1/1/2000 to 12/31/2004) and 2 years backcasting (1/1/2002 to 12/31/2004) (Table 2). For the

1 year period from 1/1/2004 to 12/31/2004, the return is higher for sustainability funds than

for conventional funds. Volatility as a measure of risk is similar for both types of funds in the

first two periods (16%) and decreases to 11% when only calculated for 2004. All

performances are measured in U.S. dollar $. Funds’ currencies are Swiss Francs and Euro.

That means that the performances shown in Table 2 also include changes in the exchange

rates. For the period 1/1/2004 to 12/31/2004 there was a 7.4 % performance increase for funds

in Euro due to the exchange rate of Euro into dollars.

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Insert Table 2 here

Statistical analysis of the environmental impact of investment funds

For statistical analysis of the environmental impact of investment funds, we compared the

funds’ portfolios with respect to the environmental ratings of stocks based on SIRI group data

and the environmental impacts based on IO-LCA (absolute and relative to financial

performance).

For comparison of conventional and sustainability funds with respect to their

environmental ratings, we pooled all of the stocks of the 13 conventional funds and all of the

stocks of the 13 sustainability funds. Figure 3 shows the distribution of environmental ratings

for conventional funds (number of stocks = 1034, mean = 5.5, standard deviation = 1.9) and

sustainability funds (number of stocks = 633, mean = 6.2, standard deviation = 1.7). The

mean environmental rating of sustainability funds is significantly better than that of

conventional funds (t-test for equality of means with p < 0.001). The standard deviations are

also significantly different (Levene's Test for equality of variance, p < 0.001). The individual

distributions of environmental ratings for each fund reveal that sustainability funds tend to

eliminate stocks with bad environmental ratings (Figure 4). For example in Figure 4 the fund

Sust 4 has no companies in the portfolio with (bad) ratings 1, 2 or 3. You find this pattern

quite often in sustainability funds but not in conventional funds.

Insert Figure 3 and Figure 4 here

The mean environmental impacts calculated for a $1000 investment was always

higher for the 13 conventional funds than it is for the 13 sustainability funds (Table 3).

However, the differences are only statistically significant for the emission of greenhouse

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gases in metric tons (680 kg for conventional funds versus 460 kg for sustainability funds),

energy use (8.5 GJ versus 6.3 GJ), and external costs ($28 versus $20). The environmental

impacts relative to the functional unit (RAP for the period 2004) show no significant

differences.

Insert Table 3 here

The mean environmental damage of a $1000 investment measured in Ecoindicator

points (EI points) is higher for conventional funds for all three areas of protection than for

sustainability funds (Table 4). The same applies to the relative environmental damage

measured against financial performance RAP2004 (only for this period significant differences

of performance could be found). However, statistically significant differences are only found

on a 10% security level. Figure 5 shows that the ranking of conventional funds and

sustainability funds, in terms of total environmental damages in EI points, is not clear-cut at

all. Already the fifth worst fund out of 25 funds in terms of environmental damage is a

sustainability fund; yet the distributions indicate that sustainability funds cause less

environmental damage.

Insert Table 4 here

Insert Figure 5 here

The assessment of environmental damages done with IO-LCA is only based on a

company’s industry affiliation. That means that the method does not differentiate between

environmental leaders and latecomers within a given industry. To address this, the

environmental impacts and damages were calculated using also the environmental ratings of

the companies. Companies with an above average environmental rating receive a reduction in

their environmental damage total; those with a below average rating, an additional damage

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(Figure 6). The results of the robustness check indicate that changes–even large changes,

which introduce large differences between companies rated as good and bad–only have a

small to modest impact on the overall environmental damage (Table 4, middle part). An

explanation for this result is that the mean environmental rating of both conventional and

sustainability funds are close to the average rating of 5 (see Figure 3). As a consequence the

overall damage of a fund portfolio remains rather stable, because reductions in environmental

damages, which receive companies better than the average are out weighted by additional

damages for the companies worse than the average.

Insert Figure 6 here

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Discussion

Differences between sustainability funds and conventional funds are smallerthan expected

Overall, the results show that with respect to portfolio composition, differences between the

two investigated types of funds–sustainability funds and conventional funds–exist. The

portfolios of sustainability funds in our sample exhibit better environmental ratings, fewer

environmental impacts, and less damage. At the same time, the difference between the two

types of funds is smaller than investors might expect. This is partly due to the fact that we had

a rather homogenous sample, since all 26 funds are managed according to the benchmark

MSCI World.

There was no statistically significant difference in the financial performance of the

two groups of funds. The sustainability funds investigated, however, show worse financial

returns for the periods that include the poorly performing years of 2001 and 2002. This might

be partially explained by information technology’s overweight in sustainability funds, being

regarded as a relatively clean and sustainable sector. According to our data, this trend turned

around in the period 2004, for which sustainability funds in the sample show significantly

better RAP compared to conventional funds.

With respect to the environmental ratings of the companies in the portfolio, we can

see that sustainability funds we have analyzed tend to omit companies with very bad ratings

and overweight companies with good ratings–although to different degrees. However, the

difference in mean ratings between the aggregated portfolio of sustainability funds and of

conventional funds that we constructed based on every investigations of the individual fund

portfolios is significant, but much smaller than one would expect. This might be explained by

the difficulties SRI fund managers face while attempting to construct portfolios that are

similar to conventional funds in terms of risk/return structure, but dissimilar in terms of

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environmental and social performance. On the other hand, this trend might be supported by

uninformed investors who invest money in sustainability funds, but do not scrutinize the fund

managements’ self-declarations and marketing messages. Even for investors who are trying to

critically challenge the fund managers’ assertions, however, it is currently difficult to get

information, since there is no independent authority to review the quality of sustainability

funds and their portfolios. Only the transparency guideline of EUROSIF is going in that

direction (Eurosif 2004).

The main outcome of this paper is the quantification of environmental impacts and

damages in absolute terms for an investment of $1000 into a specific equity fund. The idea is

that investment funds can be regarded as a physical product that needs energy and resources

and emits CO2 and other chemicals in order to generate a financial return on the investment.

Of course the fund itself is not a machine producing money, but it is a certificate confirming

ownership in a portfolio of fractions of companies; and companies harm the

environment–clearly to varying degrees–in order to generate profits. The results for our

sample suggest that statistically, on average, the portfolios of firms of sustainability funds

emit significantly less greenhouse gases and use less energy than conventional funds.

Furthermore, the damage to human health, ecosystem quality and resources is less for

sustainability funds.

In order to base this calculation not only on industry membership, but also on the

individual environmental ratings of companies, we combined the two sources of information.

Since we do not know in absolute terms how much better than average a positively rated

company is, we conducted a robustness check. However, the difference was very slight. Even

assuming that the company rated as best would only exhibit a damage of 25% and the

company rated as worst, 175% of the average damage (see Figure 6), we find no influence on

the end result. The reason for this is that the ratings are approximately normally distributed

around mean rating (Figure 3). This means damage reductions for the half of the companies

rated as good are balanced out by damage supplements for the other half of companies rated

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as bad. Consequently, the industry allocation of each fund strongly determines the calculated

impacts and damages. However, the relationship between the physical size of the company

and its financial performance is important as well. Assuming equivalent financial

performances like RAP per $1000, a small sized company is superior to a large company,

simply because within a single industry class, absolute environmental impacts and damages

are correlated with size. As a consequence the environmental impact and damage relative to

the financial performance is superior for small companies. The portfolio analysis showed that

small and medium-sized companies are in fact more common in sustainability funds than in

conventional funds.

The external costs are clearly lower for sustainability funds than for conventional

funds, but still reduce the absolute performance of a $1000 investment considerably ($144

financial return annually for 2004 in Table 2 vs. $20 in external costs in Table 3). When

discussing such results, the question that comes to mind is the validity and reliability of the

figures just presented. In the next section, we address this through our discussion of

methodological problems and limitations.

Limitations of the method

Assessment of the environmental impacts and damages has three main limitations. These are

i) the application of IO-LCA to calculate a company’s impact on and damage to the

environment, ii) the restricted system border, and finally iii) data availability and data

uncertainty.

i) The environmental impacts and damages calculated with IO-LCA are strongly

determined by a company’s membership in a specific industry. Since environmental

performance can vary considerably within a single industry, this is clearly no more

than a rough proxy of the true environmental impacts and damages for a specific

company. To refine this, one would need company-specific inventories of energy use,

resource use, emissions, and so on. However, given that environmental reporting is

21

not standardized, it is currently nearly impossible to have a data set of sufficient

quality for the large number of companies found in the investigated investment funds.

We tried to account for differences between companies within an industry and took

company-specific environmental ratings as a substitute for missing quantitative

information. The ratings produced by the SIRI group, however, were only available

for a subset of the companies.

Furthermore, we were not able to take the particularities of two specific

subindustries into account, so they were assessed as equal to the respective industry.

These are the subindustries Alternative Energy (providers of renewable energy) and

Environmental Services (providers of environmental services includes waste

management and pollution control services and excludes large-scale water treatment

systems classified in the Water Utilities subindustry). The weight of the 2

subindustries in the funds, however, is rather small: companies which fall into the

subindustry Alternative Energy are found in 7 sustainability funds with an average

weight of 2.7%; those related to Environmental Services, in 12 funds (7 sustainability

and 4 conventional funds) with an average of 2.7%, as well.

Since all of the calculations are based on IO-LCA, we only have monetary

input variables to determine the company’s impact and damage. This is particularly

problematical because the calculation of relative ownership is based on market

capitalization (calculated as outstanding number of shares held by public investors

times price per share). If companies reduce their market capitalization by

repurchasing their own stocks (e.g., to reduce cash) or private owners increasing their

holding in treasury shares, then the relative ownership of public investors, as

calculated with Equation 3, increases and a larger proportion of the company’s impact

and damage is allocated to public stock owners. To adjust for this bias, it would be

necessary to include information on the portion of a company that is not publicly

traded (treasury shares).

22

ii) Since the calculation is based on IO-LCA, the system border comprises the

company’s activities from gate-to-gate and all industry tiers in the supply chain. The

use phase and end-of-use phases, however, cannot be taken into account with IO-

LCA. Consequently, the calculation underestimates industries selling products with

large environmental impacts during and after the use phase.

iii) Data availability and uncertainty are major issues in an assessment of investment

funds. As previously mentioned, company-specific information on environmental

data is difficult to obtain for the large number of companies required, but even the

most basic information about a company–its industry affiliation–is uncertain. The

assignment to one industry is not always easy, especially for conglomerates (see

Koehler et al. 2005, for more discussion on this issue). To be accurate it would be

necessary to split the business activities of conglomerates into the respective

industries and calculate the environmental impacts and damages separately (e.g., car

producers can bring in a considerable part of their revenue through credit banking

and, therefore, belong to two industries). On average, for 4.9% of the fund portfolios,

we did not have any information on their industry membership. To account for this,

we linearly extrapolated the results, based on the known part of the portfolio, to

100%.

As an input variable for the IO-LCA, we used the most basic monetary

information about a company–its turnover in dollars. It would be better to use cost of

goods sold (COGS) broken down into industries downstream to the individual

company investigated, because this would allow to take a company-specific cost

structure into account and not to rely on the average cost structure of the whole

industry. However, to our knowledge, these data are not consistently available for this

large number of companies.

Another limitation is that the geographical scope of the Input-Output data and

the environmental assessment with Ecoindicator is not consistent with the country

23

allocation of portfolios. The problem is that companies from 48 countries can be

found in the 26 funds portfolios. Because, it is not possible to find consistent data for

all countries, the portfolios were assessed based on IO tables from the US and the

damage assessment was done based on European data with Ecoindicator. With this

we assume that US IO tables are a good proxy for all countries for which we find

companies and that the European damage assessment is representative for other parts

of the world. This of course provides room for further improvements in the analysis.

iv) An important issues is how to allocate the damage between demand, i.e. consumers

and supply, i.e. producers represented by different groups like shareholders,

employees, and managers. We did argue that the shareholder as an owner of a

company participates in the economic success (or failure), but should also be made

partly responsible for the environmental impacts and damages. This is the basic idea

of environmentally or socially responsible investment (Koellner et al. 2005). On the

other side the extended consumer responsibility framework (see Gallego and Lenzen

2005) suggests that the final consumer demanding the goods is responsible for

downstream and upstream impacts.

This discussion has also consequences on the IO models to be used. The IO

model we did use are based on the Leontief model, which assumes that supplies are

perfectly elastic to demands (Suh 2005a). In other words, when an additional demand

is placed, supply (input) will always follow under the fixed purchasing (input)

structure. Conceptually, therefore, the demand is the driver or the cause that runs the

system and all responsibilities are allocated to the demand side. The Ghoshian model

(Ghosh 1958) assumes instead that productions are perfectly elastic to supply,

meaning when additional supply is provided additional output (production) will

always follow. In this case supply drives the system and thus the supply will be

responsible for the ensuing economic activities. When Ghosh suggested this

framework at the first place, he assumed a monopolistic economy where supplies are

24

the limiting factors: imagine the 70s when industries are begging for oil, and then

additional availability of oil to a company should mean additional production of the

company. Because in modern economy supply is often not limited, Dietzenbacher

(1997) argued that the Ghoshian model should be interpreted as the price-push

mechanism, which shows how the increased input prices are imputed to the price of

the end products. Even there, one needs to consider that it is not the cost of input but

the market that determines the value of the output.

Of course, reality lies in between the Ghosh and Leontief model: both supply

side and the demand side can be somehow responsible for part of the consequences

taking place by their activities. However, in this paper we did only calculate the total

damage broken down to stock ownership, but the results should not suggest that

shareholders are a 100% responsible for the companies’ environmental damage.

Certainly the allocation of environmental damage between supply and demand is an

issue for further investigation.

Opportunities of the method

The approach shown in this paper facilitates assessments of the environmental impacts and

damages of fund portfolios. On that basis, portfolio managers are able to perform a multi-

criteria optimization of the fund portfolio with respect to its environmental and financial

performances, as proposed by Hallerbach (2004). This is an essential part of a comprehensive

sustainability rating of investment funds, and it complements the rating of the fund

management processes (e.g., quality of the research method, diligence in carrying out

research activities, the overall accountability/compliance, continuous improvement in

research processes, transparency and influence on companies in the investment portfolio)

(Koellner et al. 2005).

25

Conclusion

Based on this study, we conclude that the environmental impact and damage caused by

sustainability funds is in general lower compared to conventional funds. The environmental

advantage of sustainability funds, however, is less clear-cut than investors might expect,

because the portfolios of both types of funds investigated have a considerable overlap. The

Null hypothesis (no differentiation between the two types of funds in terms of their

environmental impact) could be rejected for 3 out of 5 measures of impact and for 3 out of 4

measures of damage, however only at a 10% level of significance.

Portfolio managers have the potential to change this situation and to reduce the

environmental impact and damage of sustainability funds. Normally, they deviate from the

sector allocation of the chosen benchmark only for financial reasons. From the perspective of

sustainable development, it is preferable to actively the sector allocation and not to passively

adopt it from the benchmark. They need to actively control the sector and industry allocation

with respect to environmental criteria, because the benchmark reflects the sector allocation of

the world economy. If, for example, the sectors energy and materials were to gain weight in

the benchmark as a result of resource intensive (and environmentally damaging) economic

growth, those sectors would be automatically weighted higher in the sustainability fund,

unless the portfolio manager considers environmental criteria when defining the sector

allocation.

The method developed here can help to optimize portfolios with respect to

environmental impacts and damages. For a reliable assessment, we recommend expanding the

static view adopted in this paper and to continuously monitor the development of funds’

environmental impacts and damage in order to detect improvements and deteriorations over

time (for more on that issue see Koellner et al. 2005). In order to assess sectors and

26

companies at the same time in a more accurate way, the use of hybrid LCA where IO-LCA

and process LCA are combined, should be investigated.

27

Acknowledgement

We would like to thank Patrick Wirth, Moritz Leuenberger and Basil Vitins from Care Group

AG, Switzerland for helpful discussion and the information they provided us on fund

portfolios. Thanks to Centre Info, Switzerland who provided the data on environmental

ratings of companies (SIRI Ratings).

28

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31

Annex 1: Names and IDs of funds investigatedID ISIN Fund name Number

of stocksTotal

assetsin mill $

Conventional fundsConv 15 BE0167281535 DEXIA INDEX WORLD 588 97Conv 16 CH0013211567 POSTSOLEIL EUROPE 57 16Conv 17 DE0005315154 ALBATROS AKTIEN INTL OP 66 4Conv 18 DE0009750273 UNIGLOBAL -NET- 214 935Conv 20 DE0009757930 KOELNER-AKTIENFONDS-UNION+ 69 14Conv 21 DE0009769950 DWS KONSUMWERTE 60 32Conv 22 LU0071970049 ML OFFSHORE ST-GLOBAL FUND 138 96Conv 23 LU0088165062 ACTIVEST LUX GLOBALGROWTH 113 104Conv 24 LU0092017853 PICTET F-GLOBAL EQT SEL-P 51 86Conv 25 LU0103938170 WM FUND GLOBAL GROWTH-B 30 7Conv 26 LU0114434946 ACTIVEST LUX MF BALANCD EQ-N 106 118Conv 27 LU0123347535 INVESCO GT GLOBAL VALUE-A 77 33Conv 28 LU0149329681 UBS ACCESS SICAV-GL EQUITY-B 301 535Sustainability fundsSust 1 AT0000820287 SALZBURG-KLASSIK OEKO TRND-A 117 5Sust 2 BE0167113795 DEXIA SUSTAIN ACCENT SOCIAL 88 71Sust 3 BE0175503300 DEXIA SUSTAIN WORLD LG CAPS 68 51Sust 4 BE0176815810 DEXIA SUSTAINABLE ACCENT EAR 90 10Sust 5 CH0009074300 SWISSCA GREEN INVEST 105 175Sust 6 CH0011981005 RAIFFSN FUTURA GLOBAL STOCK 44 43Sust 7 DE0007013641 DLI GLOBAL QUALITY 97 8Sust 8 LU0036592839 SEB INVEST OEKOLUX 88 45Sust 9 LU0076532638 UBS LUX EQTY-ECO PERFORM-BSfr 119 216Sust 10 LU0119216553 ING (L) INV-SUSTAIN GRWTH-PC 81 40Sust 11 LU0133061175 SAM SUSTAINABLE WATER FUND 39 72Sust 12 LU0138546881 ABN AMRO SOCIAL RESPONS EQ-A 68 6Sust 13 LU0138810733 HENDERSON HORIZ-GL SUST I-A2 80 3

32

Annex 2: Sector and industry classification according to GICS

Sector Industry

10 Energy 101010 Energy Equipment & Services

101020 Oil & Gas

15 Materials 151010 Chemicals

151020 Construction Materials

151030 Containers & Packaging

151040 Metals & Mining

151050 Paper & Forest Products

20 Industrials 201010 Aerospace & Defense

201020 Building Products

201030 Construction & Engineering

201040 Electrical Equipment

201050 Industrial Conglomerates

201060 Machinery

201070 Trading Companies & Distributors

202010 Commercial Services & Supplies

203010 Air Freight & Logistics

203020 Airlines

203030 Marine

203040 Road & Rail

203050 Transportation Infrastructure

25 Consumer Discretionary 251010 Auto Components

251020 Automobiles

252010 Household Durables

252020 Leisure Equipment & Products

252030 Textiles, Apparel & Luxury Goods

253010 Hotels, Restaurants & Leisure

254010 Media

255010 Distributors

255020 Internet & Catalog Retail

255030 Multiline Retail

255040 Specialty Retail

30 Consumer Staples 301010 Food & Staples Retailing

302010 Beverages

302020 Food Products

302030 Tobacco

303010 Household Products

303020 Personal Products

35 Health Care 351010 Health Care Equipment & Supplies

351020 Health Care Providers & Services

352010 Biotechnology

352020 Pharmaceuticals

40 Financials 401010 Commercial Banks

401020 Thrifts & Mortgage Finance

402010 Diversified Financial Services

33

Sector Industry402020 Consumer Finance

402030 Capital Markets

403010 Insurance

404010 Real Estate

45 Information Technology 451010 Internet Software & Services

451020 IT Services

451030 Software

452010 Communications Equipment

452020 Computers & Peripherals

452030 Electronic Equipment & Instruments

452040 Office Electronics

453010 Semiconductors & Semiconductor Equipment

50 Telecommunication Services 501010 Diversified Telecommunication Services

501020 Wireless Telecommunication Services

55 Utilities 551010 Electric Utilities

551020 Gas Utilities

551030 Multi-Utilities & Unregulated Power

551040 Water Utilities

34

Tables

Table 1: Sector allocation for selected equity funds in percent.F

und

ID

Ene

rgy

Mat

eria

ls

Indu

stria

l

Con

sum

erD

iscr

etio

nary

Con

sum

er S

tapl

es

Hea

lth C

are

Fin

anci

als

Info

rmat

ion

Tec

hnol

ogy

Tel

ecom

mun

icat

ions

Util

ities

mis

sing

tota

l

Conventionalfunds

15 8.0 5.3 10.0 11.7 9.3 10.5 23.6 11.3 4.7 4.3 1.2 100

16 17.3 1.1 1.2 2.6 9.3 14.4 35.9 2.2 14.2 1.3 0.6 10017 18.6 4.9 2.1 3.3 6.7 13.8 25.6 5.8 3.9 8.7 6.7 10018 6.2 6.6 11.6 13.0 7.3 10.7 29.8 7.3 4.0 0.9 2.6 10020 9.9 6.2 6.8 7.5 10.8 4.7 40.8 7.6 1.4 1.8 2.4 10021 . . 1.2 64.7 28.3 . . 1.5 . . 4.2 10022 9.7 5.0 11.6 11.5 8.8 9.7 24.3 8.5 4.2 1.8 5.0 10023 2.5 3.0 5.8 13.7 10.9 22.7 9.0 20.6 8.6 1.1 2.2 10024 2.9 13.8 13.0 13.5 2.3 6.4 14.5 12.4 8.5 6.2 6.4 10025 3.6 3.5 3.0 16.7 . 19.3 3.5 19.1 14.3 . 17.1 10026 6.4 9.2 12.9 9.8 4.8 3.5 5.1 20.4 5.5 9.1 13.3 10027 9.9 4.1 8.8 14.2 8.2 13.5 21.7 8.7 6.2 3.1 1.7 10028 10.9 5.4 6.1 13.7 5.0 6.6 27.5 10.0 9.2 3.6 2.1 100

∅ 8.1 5.2 7.1 15.1 8.6 10.6 20.4 10.3 6.5 3.1 4.9 100

Sustainabilityfunds

1 3.9 6.6 9.2 11.0 9.2 12.6 22.3 12.6 6.1 1.8 4.6 100

2 7.5 3.8 10.0 11.9 10.2 9.5 25.1 10.2 6.4 3.1 2.4 1003 5.8 2.2 10.1 14.0 10.0 8.3 27.0 11.6 6.9 2.7 1.3 1004 6.8 3.6 10.6 13.1 10.3 9.1 23.6 10.1 6.5 4.9 1.3 1005 5.0 6.6 17.0 6.6 12.3 9.4 15.1 14.6 7.0 4.3 2.0 1006 0.6 7.4 13.2 12.4 4.9 9.7 24.1 15.1 7.6 3.3 1.6 1007 7.2 2.9 12.5 14.5 7.0 8.9 20.1 15.9 5.4 3.2 2.3 1008 13.1 5.6 17.4 5.0 2.6 8.5 13.2 13.3 6.0 8.9 6.3 1009 3.0 7.0 9.2 11.4 9.2 12.6 22.6 12.5 6.3 2.0 4.2 100

10 8.5 5.2 8.3 9.8 7.7 11.7 25.1 10.0 7.9 5.0 0.8 10011 . 1.8 34.9 . 11.3 0.5 . 1.4 . 21.2 28.9 10012 7.9 0.9 8.8 11.3 6.0 14.1 21.8 18.0 7.1 1.1 3.1 10013 1.4 3.4 10.2 12.4 7.1 13.7 30.5 8.5 9.2 . 3.7 100

∅ 5.3 4.4 13.2 10.3 8.4 9.9 20.8 11.8 6.3 4.7 4.9 100

MSCI world1) 8.2 5.3 10.6 12.4 8.8 10.2 24.5 11.2 4.7 4.1 100

1) Benchmark

35

Table 2: Financial return RP , volatility

�

σ , and risk-adjusted performance RAP of 13

conventional funds and 13 sustainability funds over three periods based on $ (* is

significant with t-test, p<0.1). In addition, the total assets in million $ are given for the

end of 2004.

Conv. funds Sust. funds Sign. Mean Std. Dev Mean Std. Dev

2000 to 2004 RP in % 3.6 7.8 2.2 5.9

�

σ in % 16.4 2.6 16.4 1.4

RAP in % 4.7 11.2 2.6 5.8

2002 to 2004 RP in % 9.3 6.2 5.9 4.5

�

σ in % 16.3 2.6 16 1.2

RAP in % 10.1 9.5 6.1 4.6

2004 RP in % 11.5 6.2 14.4 5.1

�

σ in % 11.1 2.0 11.2 1.9

RAP in % 10.5 4.8 12.5 3.6 *Total assets

in mill $159.8 271.1 57.2 66.5

36

Table 3: Comparative environmental impacts of investing $1000 into 13 conventional

funds versus 13 sustainability funds. The first block shows absolute impacts Iknorm

and the second block shows impacts Ikrel relative to risk-adjusted performance

RAP2004 of the funds. The significance of differences of the mean are tested with t-

test,* p<0.1 and ** for p<0.05.

Conv.funds

Sust.funds

Sig.

MeanStd.Dev. Mean

Std.Dev.

Iknorm Greenhouse gases in metric tons CO2 equ. 0.68 0.37 0.46 0.11 *

Water used in 1000 liters 8.56 2.33 7.64 1.91

Ores used in metric tons 0.16 0.14 0.14 0.10

Energy used in GJ 8.50 3.96 6.30 1.34 *External cost in $ 28.23 13.97 19.54 4.92 **

Ikrel Greenhouse gases in metric tons CO2 equ. to RAP2004 0.11 0.18 0.04 0.02

Water used in 1000 liters to RAP2004 1.43 2.08 0.64 0.21

Ores used in metric tons to RAP2004 0.04 0.09 0.01 0.01

Energy used in GJ to RAP2004 1.22 1.61 0.52 0.18

External cost in $ to RAP2004 4.59 7.57 1.68 0.77

37

Table 4: Comparative environmental damages of investing $1000 into 13

conventional funds versus 13 sustainability funds. The first block shows absolute

damages Dknorm ; the second block, the robustness check for damages Dk

y with

correction factors y; and the third block, damages Dkrel relative to risk-adjusted

performance RAP2004 of the funds. The significance of differences of the mean is

tested with a t-test (* p < 0.1 and ** for p < 0.05).

Conv.funds

Sust.funds

Sig.

MeanStd.Dev. Mean

Std.Dev.

Dknorm Human health damage in EI points 0.10 0.04 0.08 0.03 *

Ecosystem quality damage in EI points 38.14 17.54 29.82 9.96

Resource damage in EI points 0.56 0.42 0.34 0.19 *Total env. damage in EI points 0.20 0.13 0.13 0.06 *

Dky Total env. damage in EI points with y = 2.00 0.19 0.12 0.12 0.05 *

Total env. damage in EI points with y = 1.00 0.20 0.13 0.12 0.06 *Total env. damage in EI points with y = 0.50 0.20 0.13 0.12 0.06 *Total env. damage in EI points with y = 0.25 0.20 0.13 0.13 0.06 *

Dkrel Total env. damage in EI points to RAP2004 0.03 0.03 0.01 0.01 *

38

Figures

Figure 1: An investment into company i of a fund k results in a partial ownership over

company i. The investor therefore partially participates in the company’s economic

activities on consumer markets in terms of sales, added economic value, and cost of

goods sold (COGS) in $. As a side effect of the ownership in a fraction of a company

he is also partially responsible for environmental damages D resulting from the

production and processes in the supply chain.

Figure 2: Cluster analysis of investment funds based on weights of stocks in the

portfolio (Squared Euclidian distances calculated according to Ward method). Conv

refers to conventional funds; Sust, to sustainability funds; and the number, to the ID

of each fund given in Annex 1.

Figure 3: Distribution of environmental ratings of stocks found in conventional funds

(number of stocks = 1034, mean = 5.5, standard deviation = 1.9) and sustainability

funds (number of stocks = 633, mean = 6.2, standard deviation = 1.7). The mean

environmental rating r of sustainability funds is significantly better than that of

conventional funds (t-test for equality of means with p<0.001). Standard deviations

are also significantly different (Levene's Test for equality of variance, p<0.001).

Figure 4: Distribution of environmental ratings r for conventional funds (first 12

graphs labeled with “Conv”) and sustainability funds (other 13 graphs labeled with

“Sust”). One conventional fund (Conv) is missing, because it has no companies with

environmental ratings.

Figure 5: Ranking of conventional and sustainability funds according to total

environmental damage of a $1000 investment in a) absolute values Dknorm and b) as

a ratio Dkrel to risk-adjusted performance RAP2004 .

Figure 6: Calculation of environmental damages damage ΔDi for company i based

on their environmental ratings ri . In order to check for the robustness different

39

correction factors y ranging from weak to strong influence were used. Above average

companies receive a reduction by the factor in their environmental damages; below

average companies receive an additional damage (e.g., a company with positive

rating 8 gets a damage reduction of 50% when the most extreme correction factor y

= 2 is chosen).

40

Figure 1

ProductionEconomic value

added [$]

Environmentaldamage D

[EI points]

Net assetvalue of fund

N [$]

Investment Market

Consumer Market

Final demand[$]

Ownership S[%]

Company i

Supply chainProducer price [$]

Sales S [$] COGS [$]

Market cap M[$]

Investment [$]

Responsibility [%]

EnvironmentResources, emissions [t]

41

Figure 2

42

regular funds SRI funds

2 4 6 8 10Env. Rating R

5%

10%

15%

20%

25%

Fre

qu

ency

2 4 6 8 10Env. Rating R

Conventional funds Sustainability funds

Environmental Rating r

Figure 3

43

10%

20%

30%

40%

Per

cen

t BE0167281535 CH0013211567 DE0005315154 DE0009750273 DE0009757930

DE0009769950 LU0071970049 LU0088165062 LU0092017853 LU0114434946

LU0123347535 LU0149329681 AT0000820287 BE0167113795 BE0175503300

BE0176815810 CH0009074300 CH0011981005 DE0007013641 LU0036592839

LU0076532638 LU0119216553 LU0133061175 LU0138546881 LU0138810733

10%

20%

30%

40%

Per

cen

t

10%

20%

30%

40%

Per

cen

t

10%

20%

30%

40%

Per

cen

t

2 4 6 8 10Env. Rating

10%

20%

30%

40%

Per

cen

t

2 4 6 8 10Env. Rating

2 4 6 8 10Env. Rating

2 4 6 8 10Env. Rating

2 4 6 8 10Env. Rating

Conv 15 Conv 16 Conv 17 Conv 18 Conv 20

Conv 21 Conv 22 Conv 23 Conv 24 Conv 26

Conv 27 Conv 28 Sust 1 Sust 2 Sust 3

Sust 4 Sust 5 Sust 6 Sust 7 Sust 8

Sust 9 Sust 10 Sust 11 Sust 12 Sust 13

Fre

qu

ency

Environmental Rating r

Figure 4

44

0.00 0.05 0.10

5132111

625

732

2224

415

98

2027

11810281223161726

Fu

nd

ID

Conventional funds

Sustainability funds

0.00 0.10 0.20 0.30 0.40

25211356

238

11732

244

22129

15181

26271020281716

Total env. damage Dknorm in EI points Total env. damage Dk

rel relative to RAP2004 in EI points

a) b)

Figure 5

45

0%

50%

100%

150%

200%

1 3 5 7 9

Environmental rating r

Del

ta o

f en

v. d

amag

e ∆

D

0.25

0.50

1.00

2.00

Figure 6