investing in canada's climate

7/27/2019 Investing in Canada's Climate

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INVESTING IN CANADAS CLIMATE: AN

EMPIRICAL ANALYSIS OF RISK AND RETURNS TO PORTFOLIOS OF

CANADIAN ASSETS BASED ON ENVIRONMENTAL PERFORMANCE

Shamai Cohen

ECON 490

April 26, 2013

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Abstract: Environmental factors are increasingly being considered by both investors and corporations,

in terms of socially responsible investing (SRI). The theoretical framework regarding SRI and corporate

environmental initiatives suggests that the effect of environmental performance on returns is ambiguous

due to factors working in opposite direction. We take an empirical approach to analyze the effect of

environmental performance on returns in Canada. Using third party environmental and emissions data

we conduct a portfolio analysis using the CAPM and multi-factor models to estimate susceptibility

to market volatility. In the Oil and Gas sector, portfolios of strong environmental performers have

significantly lower betas, suggesting that the potential costs imposed by regulation are taken into

consideration when investment decisions are made.

CONTENTS

Section 1: Theoretical Background 3

Introduction to SRI: the moral use of money 3

The purpose of SRI: does it have an impact? 5

The returns to SRI: a disputed area 8

Section 2: Question Formation 10

The environment, public policy and risk 10

Four questions and hypotheses 12

Section 3: Empirical Analysis 14

The Model: CAPM and Fama and French 14

Data sources and portfolio formation 15

Table 3.1 Emission Reduction Plan Portfolios 16

Table 3.2 Sample Environmental Score Summary 16

Regression Results 17

Table 3.3 CAPM results 17

Table 3.4 Fama French 3 Factor results 17

Section 4: Discussion 19

Methodological concerns and a look at Sadorsky 20

SRI, returns and risk in light of empirical results 21

Section 5: Conclusion 22

Bibliography 23

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SECTION 1: THEORETICAL BACKGROUND

There is considerable academic interest in the use of non-financial characteristics in decisions in the

finance industry. In a cornerstone paper by Sally Hamilton on the performance of mutual funds that look

at non-financial qualities related to corporate social responsibility (CSR), she determines the possible

causes of different rates of return on these alternative funds. The term socially responsible investment

(SRI) is a term that denotes investment that includes factors related to CSR in the decision making

process. The three following possibilities are explored:

1. Corporate social responsibility is not priced. Therefore SRI does not add or destroy value in

terms of risk-adjusted returns.

2. SRI involves assets with inherently less risk, and drives down the capital and returns. Therefore

SRI portfolios deliver lower returns compared to regular portfolios.

3. SRI involves firms with inherently better fundamental performance. Therefore SRI portfolios

deliver higher returns compared to regular portfolios.

The goal of this paper is to contribute to the body of work that uses empirical analysis to find out which

effect is strongest. Testing returns to portfolios of assets using SRI criteria can help decide which of

the above hypotheses is correct. This paper is structured as follows: in section 1 the theory pertaining

to hypotheses 2 and 3 is discussed (1 is taken as the null hypothesis), in section 2 the question for this

study is formed, in section 3 the methodology and results of this empirical study are given, section 4 is

a discussion of the results and expounds on what conclusions may be drawn from them, lastly section 5

contextualizes the conclusions by making suggestions about policy implications.

INTRODUCTION TO SRI: THE MORAL USE OF MONEY

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Money and its use have always been subject to moral considerations. Often, but not necessarily,

this occurred through religion Islam, for example, prohibits the lending of money for profit. A

Methodist preacher named John Wesley gave a sermon in 1744 titled The Use of Money, in which he

urged his congregation to Gain all you can but to avoid causing harm to the mind or health of oneself

or ones neighbors. Fast forward to present day and shed the tone of religiosity, and there is still a case

to be made for ethical concerns regarding the use of money, and more people are beginning to take

note.

The common saying goes put your money where your mouth is, meaning that to really

support a cause you think is valuable, you must show this with investment rather than just words.

One global cause that has become mainstream in the arena of politics and business is that of the

environment. This cause generally encompasses things like the loss of biodiversity, destruction of

natural habitats, as well as degradation of water sources, release of pollutants and waste into the

oceans and atmosphere, and in the case of atmospheric gasses, the possibility of anthropogenic

climate change. As the environmental movement has grown and matured over the last half century,

awareness of these issues has, too. There is a growing breed of sustainable consumers that desire food

and consumer products to be of a higher standard to reduce the negative environmental impact (think

organic produce and green cleaning fluids). These consumers also want financial products that fit with

their values (Thorgerson 2002).

Step into the world of socially responsible investing (SRI). Though ethical or green mutual

funds have existed for a while, the rate at which large chunks of capital are being directed towards them

is impressively high. In 2006 the United Nations created the Principles for Responsible Investing (PRI)

as a way for investors to publicly commit to a set of goals related to SRI, and as of 2012 the group of

signatories represents over $30 trillion in assets under management. In the United States in 2011, 12.2%

of all assets tracked by Thomson Reuters Nelson fell into the category of SRI (US SIF).

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The overall effect of shareholder activism is not the subject of this paper. In a literature review

of academic papers on the topic (Sjostrom 2009) the effects of shareholder activism are ambiguous,

though most papers take a skeptical stance on its effectiveness. Shareholder activism may or may not

impact CSR, which includes potential environmental projects. If shareholder activism effects returns

exogenously to CSR outcomes, that may be a concern for this paper because those firms with better

CSR are also more likely to be influenced by shareholder activism. If this effect was significant then

the exclusion of shareholder activism from this model would make it subject to omitted variable bias.

However the empirical part of this paper looks at environmental performance as a given value, and

seeing that the effect of shareholder activism is ambiguous, the author does not think that this is an

issue of concern.

Another interesting possibility to consider is that ethical investors, through the process of

excluding companies with poor CSR, increase the cost of capital for them (Renneboog 2011). When a

large enough group of investors decide to divest from a company, the remaining investors incur higher

risks (as the same risk is shared by a smaller number). This has a downward effect on stock prices. If

the total increase in cost of capital becomes greater than the costs associated with making the reforms,

then it is now in the companys interest to do so in order to be considered by the ethical investors

again. This process is the topic of a paper by Robert Heinkel and in their (purely theoretical) model they

do observe the incentivization of reforms, but only at a threshold where at least 20% of investors are

excluding companies for environmental performance. Ultimately, this mechanism may cause investment

in poor environmental performers to give a higher rate of return, but at a greater risk. This mechanism

relates to hypothesis 2 from Hamilton, where SRI receives lower return to investment because of the

lower inherent risk.

The total assets under management in Canada under SRI in 2010 were reported to be $530.9

billion or 19.1% (Social Investment Organization 2011). This number lies too close to the theoretical

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threshold point to claim that the effect of ethical investment on costs of capital is negligible. As a

result, we must consider the possibility that this effect will impact returns endogenously through

environmental performance. If returns to good environmental performers are lower, then this effect is

the dominant one.

Working in the opposite direction is what we will term the fundamental effect. Theorists claim

that companies who are able to make the investments to improve their CSR are also more likely to be

leading performers in other fundamental aspects of business (Cormier 2007). By this logic, investing in

companies with top-notch performance as measured by ESG indicators should yield better returns due

to better company performance. This effect is the basis for hypothesis 3 as proposed by Hamilton. If

returns to portfolios of good environmental performers are higher, then this effect is the dominant one.

The final confounding factor related to SRI is the collection and use of data by investors. The

effect we call reporting bias is that companies are far more inclined to disclose information that is of

a positive nature (Cormier 1999). Put differently, no news isnt bad news, but any news at all is likely

good. Of course this effect occurs to varying degrees, and is dependent on the local regulations and

culture surrounding disclosure. In Canada, there is less of a reliance on mandated disclosure than

in the US (Buhr 2001). Companies are required to meet many standards related to environmental

performance, so voluntary disclosure of these performance indicators plays an important role in the

companys disclosure strategy (Cormier 1999). For our concerns, this causes a problem in sample

selection because we will only include in our analysis companies for which we have all the required data.

There has been a steady increase in environmental disclosure among Canadian firms, causing

us to ask the question whether the increase is due to do better environmental outcomes by firms, or

whether there is some increase in external pressure to disclose. If it is the former then our problem of

sample bias is likely magnified. However, if it is the latter, then it is likely that poorer performers are

also increasing disclosure in the face of such pressure. Unfortunately, enlightening the root cause of

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disclosure for each company used in this study would be too difficult a task to complete. In light of

our firm specific statistics, and our methods of controlling for other variables, we believe our sample

contains sufficient observations from both good and poor environmental performers.

THE RETURNS TO SRI: A DISPUTED AREA

Numerous studies exist looking at returns to ethical investment. There is some variability in the

methodology and sample selection, so here is presented a brief review of some of the literature on the

topic. First a brief overview of methodologies will be given. Then the results for each study are reported

with some context. Lastly, the implication of these results will be discussed and related to form the null

hypothesis of this study.

Returns to SRI can be measured in a few different ways. Some studies look exclusively at mutual

funds and compare ethical ones to conventional ones (Bauer 2005) while others compare ethical indices

to traditional ones (Managi 2012), and still others create their own portfolios based on specific ESG

criteria to perform comparative analysis (Ziegler 2011). The differences here are largely due to the

specific question being answered by the empirical analysis. The rationale for sample selection in this

study will be reviewed in section 2.

Most studies use a single factor model that estimates an assets abnormal return and

susceptibility to market risk. This model is called CAPM. Various studies have implied that CAPM is not

the best tool for conducting this sort of analysis (Chretien 2008), and more useful models have been

created. Most studies that use the CAPM also employ a more robust model: based on Eugene Fama and

Kenneth French (1993) or Mark Carhart (1997) they use a three or four factor model, respectively. The

basis for using both CAPM and a multi-factor model seems to be widespread, so this study considers

that the standard.

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MANAGI, SHUNSUKE ET AL. DO SOCIALLYRESPONSIBLEINVESTMENTINDEXES OUTPERFORM CONVENTIONAL

INDEXES? (2012)

This study compares ethical indexes with traditional ones in an international comparison that spans the

US, Japan and the UK over the years 2001-2008. They find that both indexes exhibit cyclical regimes

(bull and bear), and that the cycles coincide across the SRI and traditional stock indexes. Moreover, the

means and variances on return were not statistically significant, suggesting that there is little difference

between SRI and non-SRI activities.

BAUER, ROB ET AL. INTERNATIONAL EVIDENCE ON ETHICAL MUTUAL FUND PERFORMANCE AND INVESTMENT STYLE

(2004)

Using a database of ethical mutual funds and regular mutual funds in the US, UK and Germany, Bauer et

al. conduct a comparative analysis using the Carhart 4 factor model. They find no significant difference

in risk adjusted returns over the period 1990-2001. Their analysis also casts doubts over the ability of

ethical indexes to incrementally explain returns to ethical funds.

ZIEGLER,ANDREAS ET AL. DISCLOSED CORPORATE RESPONSES TO CLIMATE CHANGE AND STOCK PERFORMANCE: AN

INTERNATIONAL EMPIRICAL ANALYSIS (2011)

Ziegler et al. are interested to find out if disclosing a response to climate change (in the form of a climate

impact statement or an emissions reduction plan) has an impact on the returns of a corporation. Their

study is limited to the USA and EU. They use CAP-M and Carhart 4-factor model to chart returns of

portfolios created using two binary variables related to specific disclosure questions. In the time-series

analysis over the years 2001-2006 they find the excess returns for disclosure are higher in the EU than in

the USA, and that within the USA the excess returns for disclosure are higher in the energy sector than

in other sectors (where returns to disclosure are negligible).

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This sample from the literature is in no way exhaustive, but highlights a few interesting results.

There is little indication of significant differences when assessing SRI at the index or fund level. At the

asset level it appears to be possible to create portfolios that have significantly different results based

on CSR indicators. This study borrows greatly from the methods of Ziegler and focusses on the most

granular level by creating unique portfolios bases on ESG data, rather than ethical funds or indexes.

Also it should be noted that the Canadian sector has had less academic interest, probably because it is a

smaller market.

SECTION 2: QUESTION FORMATION

In this section the theory that pertains particularly to this study is outlined. Factors related specifically to

the environment and regulatory situation in Canada are discussed. Methodological issues are raised as

they pertain to the questions, leaving the models themselves to be explained in the next section.

THE ENVIRONMENT, PUBLIC POLICY AND RISK

Environmental concerns are embodied in a wide variety of corporate activity. So much so,

that narrowing down the list to something comparable across industries poses a problem. One type

of pollutant has been in the public eye extensively over the last decade and this is the category of

greenhouse gasses (GHGs). Carbon dioxide is a prominent GHG and though others contribute, the

industrial measure for emissions is called carbon emissions and is standardized such that other GHGs

get converted to their carbon equivalent. The overall phenomenon of climate change is taken to be the

increased anthropogenic emissions of GHGs that has led to an upward trajectory of global temperatures.

Climate change is a global issue and 194 countries are signed to the UN Framework Convention on

Climate Change (UN FCCC 2013). Because of the ubiquity of climate change, and the fact that the ethical

consumer drives demand for ethical financial products, we believe that a companys stance on climate

issues is likely to be considered a high priority for investment managers in SRI.

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Leaving aside the impact of SRI, what are the costs and benefits of corporate projects designed

to improve environmental performance? It is clear that for a company to engage in a project the cost

must be offset by benefits that come privately in the form of efficiency savings, or publicly if there are

incentives given by government regulation. Some environmental projects are undertaken as part of that

first category, but in the case of GHG emissions there is a clear case of tragedy of the commons in the

sense that private benefits to curbing emissions are negligible if any. Because we are still dealing with a

negative externality, the government ought to play a role and provide public incentives to curb

emissions. There are many forms of doing this, but most involve an emission ceiling, where emissions

beyond a certain point are charged a penalty (Jones 2007).

It is theorized that overcompliance with such regulations may be incentivized through financial

markets due to uncertainty around legislation of regulations (Mallory 2012). The mechanism for this is

two-fold, first as a signal of company value, and second as a method of pre-emption. As a signal,

enacting costly projects shows that the company has healthy finances and the capability to complete a

capital-intensive project, implying to investors the company is doing well in other areas. As a method of

pre-emption, improving a companys environmental performance reduces risk in the face of an

uncertain legislative environment. Regulations may be made stricter and pre-empting them allows

investors to attribute less risk to those assets. Also, by way of pre-emption, overcompliance may signal

to the government that the current regulations are not sufficient or need to be improved and then an

increase in regulation that follows will impose costs on the companys competitors, making their

position in the market stronger.

The legislative environment is full of uncertainty and varies country by country. The propensity

of a government to enact environmental regulation cannot be modelled, but we may look at regional

differences to get an idea of comparative likelihood. Canada, for example, signed the Kyoto Protocol

in 1997, but opted out of it in 2011 after more than 5 years of not attempting to achieve the emissions

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standards (IPCC 2012). The United States never signed or ratified the Kyoto Accord, while the European

Union did and remains committed to the reduction plan. Based on these differences, Ziegler expected

higher returns to good environmental performers in Europe, but not in the US (and confirmed that

result). Canada lies in between the two so the results should be interesting and help determine if

the regulatory environment impacts returns. Within this framework a subsector analysis will also be

conducted. The oil and gas sector is subject to more stringency in terms of regulation due to the high

amount of emissions it is responsible for. This makes the effect of environmental performance more

important. Ziegler found higher returns to good environmental performers in this sector in the United

States, and this study hopes to replicate that result in Canada.

So, given that compliance with future environmental regulations is a costly risk carried by firms,

it follows that investors would likely view good environmental performers as less risky. Assets that carry

less risk are going to have a lower rate of return to induce investment. Working in the opposite direction

is the theory that good environmental performance goes with good performance in fundamental

financial areas. So which way does the overall effect go?

FOUR QUESTIONS AND HYPOTHESES

Specifically, our questions are as follows:

(1)Compared to portfolios of poor environmental performers, are portfolios of good

environmental performing assets less risky?

(2)Compared to portfolios of poor environmental performers, do portfolios of good

environmental performing assets provide a higher return?

And two variants to the model:

(3) Does relying on overall environmental performance rather than corporate emissions

disclosure for portfolio formation yield a larger difference between good and poor

environmental performing portfolios?

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(4)Does the Oil and Gas sector exhibit a larger difference between good and poor

environmental performing portfolios?

The method used to test these questions empirically will be capital asset pricing model (CAPM) and a

multi-factor model. From this analysis we can learn about returns and volatility of assets grouped in

portfolios based on environmental performance. The model variation implied by question (3) means

that this study will use two different methods for estimating company environmental performance. The

first is the same as one used by Ziegler and is a measure of corporate disclosure. This result is a binary

variable and as such only reveals environmental performance to an extent. A more direct analysis of

environmental performance may yield different results, which is what the answer to question (3) hopes

to ascertain. The variant in question (4) simply means that the analysis will be done on a subset of assets

that comprise the oil and gas sector, to see if the results here are different than across all sectors.

We put forth a null hypothesis, given that Canadas regulatory environment occupies a grey area

between the United States and Europe.

HYPOTHESIS (1N): portfolios of good and poor environmental performers will exhibit no significant

observable difference in risk.

HYPOTHESIS (2N): portfolios of good and poor environmental performers will exhibit no

significant observable difference in risk-adjusted returns.

In answering the 2 variant questions we put forward positive hypotheses that elaborate on the expected

outcomes, given that these variants were selected for their hopefully explanatory outcomes.

HYPOTHESIS (3P): portfolios based on overall environmental performance will yield a larger

difference between good and poor environmental performing portfolios.

HYPOTHESIS (4P): portfolios formed of assets in the subsector of oil and gas will yield a larger

difference between good and poor environmental performing portfolios

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SECTION 3: EMPIRICAL ANALYSIS

In this section the models of financial analysis are explained and the method by which

environmental performance is integrated into these models is explained. Then the empirical findings are

given. Further discussion of these findings can be found in section 4.

THE MODEL: CAPM AND FAMA AND FRENCH

The Capital asset pricing model (CAPM) is used to estimate an asset or group of assets risk

adjusted return and volatility (Fama and French 2004). Using time series data of the assets returns,

the market rate of return, and the risk free rate of return, those parameters can be estimated using an

ordinary least squares (OLS) regression. The equation for CAPM looks like this:

Jensens alpha is the intercept parameter and accounts for abnormal return also known as risk

adjusted return because the model assumes a linear relationship between risk and return. If an asset

has a positive or negative Jensens alpha, then the asset deviates from that assumption, hence the

term abnormal returns. As mentioned risk is estimated by the regression coefficient (beta) and it is

important to note that this captures only systematic risk, also called market risk or undiversifiable risk. It

is defined as such because beta estimates the movement of the price of the asset in relation to market

returns. This means a beta value of 1 moves exactly as the market does, less than 1 and it moves with

the market but to a lesser degree, and it is possible to have a negative beta meaning it moves counter-

cyclically to the market.

The CAPM is widely used and widely criticized as a model. One more robust variation proposed

by Fama and French includes other slope estimating parameters that are supposed to give more

explanatory power to the model. With the addition of the factors for asset capitalization and book-to-

market ratio and the market movements of these factors, additional betas can be estimated. Small cap

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assets tend to have higher returns than big caps, so the variable SMB (small minus big) represents the

returns of a portfolio of small cap stocks minus big cap ones. Similarly, HML (high minus low) is a

variable determined by the difference in return to portfolios of high and low book-to-market ratios. A

fourth term called the momentum factor can be added for even more explanatory power (Carhart

1997). This factor takes into account the movement of the market over the previous months, it is usually

an average of returns from the previous 12 or 6 months. In all now, we have 4 factors and the equation

looks like this:

Using these two formulas, we take a closer look at Canadian markets, but first we need environmental

variables.

DATA SOURCES AND PORTFOLIO FORMATION

The Canadian Fama and French monthly factors as well as monthly market returns and t-bill

rates were generously provided by Claude Francoeur of HEC Montral. This data spanned from 1995 up

until the end of year 2009. I am very grateful for his contributions, without them I would have had to

compute the factors myself. Asset-specific data was all accessed via Datastream, provided by Thomson-

Reuters to the University of British Columbia. Also accessed via Datastream was asset ESG data compiled

by a third party Swiss company called ASSET4. ASSET4 bases its entire ESG database on publicly available

information; all of the environmental parameters that were looked at had been disclosed by the

company, much of it on a voluntary basis.

The first environmental aspect that was looked at is whether the company has an emissions

reduction policy. The variable is simply a yes or no, but we take this variable to be a good indicator

of the companys overall commitment to combatting climate change. The other environmental factor

considered is a score out of 100 that is given by the researchers at ASSET4. They describe this score

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as follows: The environmental pillar measures a company's impact on living and non-living natural

systems, including the air, land and water, as well as complete ecosystems. It reflects how well a

company uses best management practices to avoid environmental risks and capitalize on environmental

opportunities in order to generate long term shareholder value (ASSET4 2013). To include these

environmental factors into our analysis, portfolios were created for a comparison between better and

poorer environmental performing companies. For the emission reduction plan the portfolios were

divided on the yes/no basis, giving two portfolios of different sizes. For the environmental score, the

median was calculated and assets with scores above the median were in the good portfolio and below

the median were the poor portfolio.

TABLE 3.1 EMISSION REDUCTION PLAN PORTFOLIOS

All companies n=89 Oil and Gas n=19

Emission

Reduction

Plan (Y)

No

Plan

(N)

Market Cap

Ratio Y/N

Emission

Reduction

Plan (Y)

No

Plan

(N)

Market

Cap Ratio

Y/N

2005 25 (28%) 64 0.74937754 8 (42%) 11 2.557029

2006 29 60 1.05077807 11 8 4.598691

2007 44 45 2.00314465 14 5 16.14236

2008 56 33 3.54523756 17 2 51.25082

2009 59 (66%) 30 3.76894898 17 (89%) 2 75.20784

TABLE 3.2 SAMPLE ENVIRONMENTAL SCORE SUMMARY

Mean Median

2005 39.03382 24.07

2006 40.26674 32.26

2007 41.94292 29.65

2008 48.86708 44.38

2009 52.58213 59.73

Also note that the environmental parameters are updated on a yearly basis by ASSET4, while all

the other data was monthly. Furthermore, though ASSET4 has data on more than 250 Canadian

companies, the number of companies they have full data for that overlaps with the Fama and French

factors was considerably smaller. We selected the period 2005-2009 to maximize the number of

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observations while keeping the sample size large enough. In the end this left us with 89 companies and

60 monthly return observations for each. To deal with the dynamic nature of environmental parameters

we used a value weighted floating portfolio where each year it is as if the portfolios are liquidated and

then reformed based on updated environmental criteria and using that years asset market

capitalisation divided by portfolio market capitalization to give new asset ratios. An additional 4

portfolios using the same methodology were created using only companies from the oil and gas sector

(yes and no emission reduction plan, and good and poor environmental score). Thus, in total, we have 8

value weighted floating portfolios to conduct analysis on.

REGRESSION RESULTS

Regressions were run using Stata statistical software at the University of British Columbia.

Displayed in tables 3.3 and 3.4 below are the results from CAPM and Fama and French 3 factor models.

Regressions using a 4 factor model including momentum were also done, but the results had less

significance than the three factor model and lower adjusted r-squared values so those results are not

included here.

TABLE 3.3 CAPM RESULTS

Portfolio Jensen's Alpha Beta R-squared

ENVSCORE-TOP 0.009(0.008) 0.352(0.111)** 0.147

ENVSCORE-BOT 0.007(0.007) 0.36(0.109)** 0.157

O&G-ENVSCORE-TOP 0.011(0.011) 0.307(0.156) 0.060

O&G-ENVSCORE-BOT 0.005(0.01) 0.459(0.151)** 0.136

E REDUC-YES 0.01(0.008) 0.352(0.114)** 0.140

E REDUC-NO 0.005(0.008) 0.345(0.117)** 0.139

O&G-E REDUC-YES 0.011(0.01) 0.317(0.153)* 0.069

O&G-E REDUC-NO 0.01(0.117) 0.496(0.173)** 0.125

**means statistically significant to the 1% level

* statistically significant to the 5% level

TABLE 3.4 FAMA FRENCH 3 FACTOR RESULTS

Portfolio

Jensen's

alpha Beta SMB HML

Adjusted R-

squared

ENVSCORE-TOP 0.009(0.007) 0.216(0.152) 0.19(0.261) 0.464(0.162)** 0.216

ENVSCORE-BOT 0.007(0.007) 0.285(0.152) 0.06(0.262) 0.382(0.162)* 0.195

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O&G-ENVSCORE-TOP 0.012(0.01) 0.182(0.222) 0.179(0.382) 0.411(0.237) 0.063

O&G-ENVSCORE-BOT 0.004(0.009) 0.511(0.208)* -0.316(0.357) 0.507(0.222)* 0.200

E REDUC-YES 0.011(0.007) 0.207(0.158) 0.219(0.271) 0.447(0.168)** 0.196

E REDUC-NO 0.005(0.008) 0.286(0.162) 0.012(0.279) 0.402(0.173)* 0.171

O&G-E REDUC-YES 0.011(0.01) 0.209(0.217) 0.131(0.374) 0.425(0.232) 0.075

O&G-E REDUC-NO 0.009(0.011) 0.551(0.249)* -0.235(0.428) 0.257(0.265) 0.101

First, note that in all the regressions there is not a single significant value for alpha, meaning

that none of the portfolios experienced abnormal returns. From this we may choose to infer that the

null hypothesis 2N is confirmed, because there is no significant difference in returns across portfolios.

Next, observe the extremely low r-squared values in both tables (adjusted r-squared for 3-factor

model), this indicates the extent to which the independent variable influence the dependent variable.

In this instance it seems that these models explain only a small portion of the returns on these assets.

The adjusted r-squared values for the 3 factor model are higher than those using CAPM in 6 out of 8

instances, lower in 1, and roughly the same in another. The low explanatory power poses a problem for

drawing conclusions from this analysis, and this will be elaborated on in the next section. For now, we

will allow inferences from the available data to be made on the basis that low r-squared values do not

make them invalid merely less explanatory; in other words they do not tell us the whole story.

Using CAPM the beta estimates are significant to the 1% level in 6 instances, to the 5% level in

1, and only insignificant in 1. The difference between good and poor environmental performers across

all sectors is negligible; however in the oil and gas sector we get an interesting result. The difference

between oil and gas assets with an emissions reduction plan, and without a plan is 0.18, significant to

the 5% level. This result is 0.15 in the oil and gas environmental score portfolios, but not significant.

What this difference implies is that poor environmental performing oil and gas firms move pro-cyclically

(with the market) at a rate of 0.18 higher than good environmental performers in that sector. One way

to interpret this is to say that oil and gas firms without an emissions reduction plan are 44% (0.496/

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0.345) more volatile. This implies greater risk for these assets, adjusted for returns suggesting that

though the null hypothesis 1N holds across all sector, the hypothesis 4P may be inferred as correct

based on the data.

Also from the CAPM regressions, the difference in estimates across environmental parameters

is negligible with the largest being less than 0.04 and most within 0.02 points. The results given from

portfolios created based on emissions reduction plan data compared to portfolios created based on

environmental score data are virtually the same. This suggests that hypothesis 3P should be rejected

and the two environmental assessment methods can be said to be largely interchangeable for our

purposes. This result is possibly explained by the portfolios having similar composition of assets. One

should note that the trend is for more companies to come out with an emissions reduction plan, so in

the future this variable will likely not be a good indicator as nearly all companies will have one.

Turning now to the 3 factor analysis, the first thing to notice is that we have lost most of the

significance for the beta values. Thus, we cannot infer much about riskiness of assets using this model.

Based on the market capitalization ratios of the portfolios given in table 3.1 it is clear that market

capitalization between good and poor environmental performers could play a role in their rate of return.

For example the average market capitalization ratio of oil and gas firms with emissions reduction

plans to those without emission reduction plans is 30:1. Therefore it makes sense that we have more

significant results for the HML factor than for market returns. However no clear pattern emerges from

this data, confusing the analysis slightly.

SECTION 4: DISCUSSION

In addressing the results, the first issue to discuss is the low explanatory value of the

regressions. While there are some reasons to think that a flaw in methodology is to blame, comparison

with a similar empirical study shows that these results are likely not an anomaly. Then after a look at

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how the results fit with various theories, future areas of study are recommended.

METHODOLOGICAL CONCERNS AND A LOOK AT SADORSKY

As noted above, the low r-squared values initially were viewed as possibly caused by

methodological concerns. A usual r-squared value for CAPM lies around 0.7-0.8 and for 3 factor models

that value is higher, more like 0.85-0.9 (Fama and French 1993). What the low r-squareds mean is that

there are other factors that are impacting the dependant variable, in this case asset returns minus the

risk-free rate. CAPM only takes into account market risk, and does not account for any ideosynchratic

or asset-specific risk. It is possible that the assets that were used happened to have high levels of

ideosynchratic risk that is not accounted for in either model. Another possible confounding factor in our

analysis is the financial crisis that hit in 2007 and continued to impact global financial markets into 2008

and 2009. It is possible that the portfolios we created were not representative of the overall Canadian

market, in the sense that some sectors were affected differently than others and if our portfolios do

not share similar constituency as the market, then market returns are not a good indicator for portfolio

returns.

On the topic of portfolio composition, a common criticism of these models is that they

over-estimate returns due to an effect known as survivorship bias. Survivorship bias can lead to an

overestimation of 0.14-0.3% in ethical mutual fund returns (Bauer 2005), and is an issue when looking

at any sector. The process that was used to select assets for use in this study was not arbitrary, but was

based on which companies had complete environmental data in the ASSET4 universe over the specified

time period. Companies with incomplete data were not used, meaning that companies that went out

of business during the period were not available for selection and this should put an upward bias on

return results. Though this does not directly affect r-squared values it is a methodological concern worth

noting.

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Given these concerns, let us do a brief comparison with results from a peer-reviewed journal

article by Perry Sadorsky titled Risk factors in stock returns of Canadian oil and gas companies. In

this study CAPM is used, along with multi-factor models using factors specific to oil and gas in Canada,

namely the price of crude futures and the Canadian/US exchange rate. In this analysis the r-squared

using CAPM was 0.04, and in the multivariable model 0.22. This shows that it is likely that there is more

going on than can be explained by these financial models. There are many critics of these models, but

we will leave the solution to this problem to another paper, perhaps.

SRI, RETURNS AND RISK IN LIGHT OF EMPIRICAL RESULTS

The main focus of this paper is to determine a causal relationship between these key factors in

the Canadian market. Based on the results, there does not seem to be a higher return to investing in top

environmental performers. Based on this, it seems the results support the null hypothesis of Hamilton,

that CSR is not priced and there is no difference in returns when investors try to include CSR in

decision making. At the least, it appears that SRI does not suffer from inherently lower returns. Ethical

consumers, who wish to engage in SRI but are concerned about sacrificing profits, should evaluate their

decision in light of this result. If we wanted to extend the model and use a utility function to represent

returns to ethical investment with two inputs of financial returns and stringency of ethical requirements,

we could do that. What the expected result would be is that consumers with preferences for ethical

investment should engage in it because there seems to be no sacrifice in profit. In other words, this

paper predicts the continual growth of the market for SRI so long as the market segment of ethical

consumers continues to grow. It will be interesting to how the empirical results of this paper hold over

time, as the market for SRI grows. We mentioned the 20% theoretical threshold that has not yet been

crossed, but it will be soon. If the market for SRI becomes over-saturated then it is possible that returns

will suffer and profit-driven investors will be able to capitalize by investing in companies with poor CSR.

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The one exception to the above discussion is the interesting result of higher betas in poor

environmental performers in the oil and gas sector. The literature (this paper included) is guilty of

conflating the terms risk and volatility, to some extent. What the higher beta means is not that those

assets are less likely to achieve returns (risk) but that the price fluctuates more (volatility). Still, volatility

is potentially something that should be avoided. The higher volatility for poor environmental performers

in this sector is probably explained by the overcompliance theory. As companies make investments to

curb environmental destruction, those who dont make those investments are subject to an increasing

likelihood of government intervention. Investors respond to this by making bets on whether they think

regulation ill or will not happen (by making investment decisions on the more polluting firms), and this

causes more movements in asset prices. To find out more about this effect, an event study framework

that analyzes prices and how they respond to new regulation could give more insight.

SECTION 5: CONCLUSION

If socially responsible investing wants to grow to become more than a niche market, there

needs to be proof that selecting assets with positive ESG profiles yields as good, if not better, results

as a no-holds barred approach to finance. The financial world is notoriously profit-driven and if ethical

finance is going to have the opportunity to promote corporate social responsibility, it needs to do so

by making money as well as its not-so-ethical competitors. This paper looked specifically at investing

in Canada based on environmental criteria, to see if portfolios of good environmental performers

performed better than poor environmental performers. The results showed that there was no significant

difference, but this may be due to limitations of the CAPM and multi-factor financial models. One

interesting result of this analysis was that poor environmental performing companies in the oil and gas

sector do exhibit higher volatility to market risk than good environmental performers, by an estimated

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factor of about 44% higher.

If the public decides that it is the governments role to reduce volatility in financial markets,

then making stricter environmental regulations may be a good solution. By increasing the regulatory

standard, there will be fewer companies that are seen by investors as being subject to future regulatory

change. Companies near the bottom will be forced to make the capital investment, but then the playing

field will be more level and speculation will be less. This solution has a double effect of improving

environmental and economic outcomes. It is also important to note that the government can reduce

uncertainty by making its regulatory goals clear and communicating them to the companies, investors

and the public. Also on the topic of information, the collection and dissemination of information related

to ESG factors is still reliant on corporate disclosure and this is likely not an efficient solution.

Government regulations surrounding disclosure could help in this case, as well.

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