Interrelation of Integrated Reporting with information

University of Amsterdam MSc Accounting & Control 2017/2018 thesis “Interrelation of Integrated Reporting with information asymmetry”

by Jacfar Yusuf (2018).

Interrelation of Integrated Reporting with information

asymmetry

Name: Jacfar Yusuf

Student number: 11419237

Thesis supervisor: Dhr. dr. A. Sikalidis,

Date: June 25, 2018

Word count: 14505, 0

MSc Accountancy & Control, specialization Accountancy

Faculty of Economics and Business, University of Amsterdam


by Jacfar Yusuf (2018). 2

Statement of Originality

This document is written by student Jacfar Yusuf who declares to take full responsibility for

the contents of this document.

I declare that the text and the work presented in this document is original and that no sources

other than those mentioned in the text and its references have been used in creating it.

The Faculty of Economics and Business is responsible solely for the supervision of completion

of the work, not for the contents.



Abstract

The period prior to the introduction of the so called ‘Integrated Reporting Framework’ by the

IIRC in 2013 the traditional reports were failing to capture the economic consequence of

corporate innovations in a timely fashion. The framework was presented as a response to the

huge demand of the investors for a change in the reporting regulation. The IIRC (2013)

mentioned that the IR framework aims to improve the quality of information, promote a more

cohesive and efficient approach of reporting, enhance accountability and stewardship and

stimulate integrated thinking, decision-making and actions. Nonetheless, does this change

faithfully represents the improvement of the economic consequences in the reports? Therefore,

the interrelation of Integrated Reporting with information asymmetry is examined during this

study. For the study two models are tested in a regression to see whether Integrated Reporting

is related with information asymmetry. The two models are the stock liquidity and abnormal

return model. Both models are examining if Integrated Reporting leads to respectively lower

stock liquidity or abnormal returns. The input that represents the framework in the models are

the ESG-scores of 503 companies with the sample period from 2010 till 2016. The final sample

consists of 3,155 firm year observations. Firstly, I find that Integrated Reporting lowers the

bid-ask spread of the firms that implemented the framework. Subsequently, no empirical

evidence is found that the Integrated Reporting framework lowers the company’s abnormal

returns. With the reliability issues in mind, I conclude based on this study that the framework

of the IIRC has a negative interrelation with information asymmetry. This thesis contributes to

the empirical world by expanding and widening the existing empirical literature about

Integrated Reporting. By looking at the association of IR and information asymmetry of the

Northern-American companies clarifying the relation and holding the criticisms of the

framework in mind.

Key words: Integrated Reporting Framework, IIRC, information asymmetry, ESG-scores, bid-

ask spread, abnormal returns.



Contents

Abstract .........................................................................................................................................................3

List of figures and tables .............................................................................................................................6

1 Introduction .........................................................................................................................................7

2 Literature review and hypothesis development ........................................................................... 12

2.1 Integrated Reporting ................................................................................................................ 12

2.1.1 IIRC Framework .............................................................................................................. 13

2.1.2 Guiding principles ............................................................................................................ 14

2.1.3 Content elements ............................................................................................................. 15

2.2 Support for IR .......................................................................................................................... 16

2.3 Criticism on IR ......................................................................................................................... 17

2.3.1 Denial of the criticism ..................................................................................................... 19

2.3.2 Criticism versus the supporting literature..................................................................... 20

2.4 Theoretical framework ............................................................................................................ 20

2.4.1 Agency theory ................................................................................................................... 20

2.4.2 Adverse selection ............................................................................................................. 21

2.4.3 The efficient market hypothesis..................................................................................... 22

2.4.4 Value relevance theory .................................................................................................... 22

2.5 Hypothesis development ......................................................................................................... 24

2.5.1 The bid and ask-spread ................................................................................................... 24

2.5.2 Abnormal returns ............................................................................................................. 25

2.6 Paragraph summary.................................................................................................................. 26

3 Data and research design ................................................................................................................ 27

3.1 Sample selection ....................................................................................................................... 27

3.2 Data sources .............................................................................................................................. 29

3.3 Stock liquidity model ............................................................................................................... 29

3.4 Control variables ...................................................................................................................... 30



3.5 Abnormal returns model ......................................................................................................... 31

3.6 Testing........................................................................................................................................ 31

3.7 Framework ................................................................................................................................ 32

4 Empirical results............................................................................................................................... 33

4.1 Descriptive statistics................................................................................................................. 33

4.1.1 Normality test ................................................................................................................... 34

4.1.2 Pearson correlation .......................................................................................................... 35

4.1.3 Homoscedasticity ............................................................................................................. 37

4.2 Regression analysis ................................................................................................................... 37

5 Conclusions....................................................................................................................................... 41

5.1 Summary .................................................................................................................................... 41

5.2 Conclusions ............................................................................................................................... 41

5.3 Limitations ................................................................................................................................. 42

5.4 Further research ........................................................................................................................ 43

References .................................................................................................................................................. 44

Appendices................................................................................................................................................. 50

Appendix 1: OLS Assumptions ......................................................................................................... 50

Appendix 2: Libby boxes .................................................................................................................... 51

Appendix 3: Test for normality .......................................................................................................... 52

Appendix 4: Regression ....................................................................................................................... 55



List of figures and tables

Figures

Figure 1 ESG-framework

Figure 2 Research Framework

Tables

Table 1 Final Sample

Table 2 Number of observations per year

Table 3 Descriptive Statistics of sample companies with ESG-scores before winsorizing

Table 4 Pearson correlations.

Table 5 Spearman correlations

Table 6 Regression Analysis of SPREAD

Table 7 Regression Analysis of ABNORMAL_RETURN

Table 8 Hypotheses outcomes of the regression

Table 9 Skewness/Kurtosis tests for Normality

Table 10 Shapiro-Wilk W test for Normality

Table 11 Descriptive Statistics of sample after winsorizing

Table 12 Histogram & Box plot SPREAD of the transformation due to winsorizing

Table 13 Histogram & Box plot ABNORMAL_RETURN of the transformation due to

winsorizing

Table 14 Breusch-Pagan test for the SPREAD model

Table 15 Breusch-Pagan test for the ABNORMAL_RETURN model

Table 16 Variance Inflation Factor (VIF)



1 Introduction

Behind every company there is a unique story, including a specific business strategy. A big

difficulty is the understandability of this strategy by the stakeholders. The story must be

developed in an understandable and unambiguous manner to let stakeholders comprehend the

story effectively (Druckman, 2014). There is an observed trend that annual reports soon would

become less relevant/significant for shareholders (FRC, 2011). Companies are reacting by

providing more non-financial information, but this does not seem to happen in an

understandable and unambiguous manner. The objective to communicate the operations of the

business in an integrated and sustainable manner is not met. So, there was a huge demand for

a change in the reporting regulation, IIRC countered this by introducing a new form corporate

reporting the ‘Integrated Reporting Framework’ (IIRC, 2013).

The overall purpose of traditional reporting is to provide assurance of the current and

forthcoming performances of an entity, but nevertheless these traditional reporting methods are

failing to clarify the economic consequence of corporate innovations in a timely fashion (Healy

and Palepu, 2001). In this the IR framework can be of use. Druckman (2014) mentioned that

the hardest and crucial part is to create insight in how the company's strategy and business

model creates value over time for the entity. The so called ‘Integrated Reporting’ complements

to the reporting environment of entities and creates a determination of internally performance

and attracts external financial capital for investment.

On September 1st in South Africa the King Code of Governance Principles for South

Africa (‘King III’) was released. A significant recommendation of the code King III is that

entities should not only adopt and implement sustainability reporting, but they should go a step

further. The King Committee Chairman Mervyn E, King says “Sustainability is, however about

more than just reporting on sustainability. It is vital that companies focus on integrated

performance.” The King III introduces the concept of integrated sustainability performance and

integrated reports into South African Corporate Governance principles. In addition, the

Johannesburg Stock Exchange Limited (‘JSE’) made the code King III mandatory by

incorporating into its listings requirements. This leads to that South-African based companies

are required to publish an integrated report, if not , they need to explain why they not choose

to meet the requirements of the code KING III (Jones, 2015).

In the big world of corporate reporting, Integrated Reporting is a relative new

phenomenon that has been on the rise during the last decade (Serafeim, 2015). Currently



Integrated Reporting is implemented on a mandatory basis in South Africa, and research

showed evidence of momentum towards Integrated Reporting in other huge economies around

the world. Integrated Reporting relies on a sequence of underlying activities, IR is more than

just a corporate report (Robertson, 2015). The International Integrated Reporting Council

(IIRC) has a long-term vision embedded within the business practice by formulating the

framework Integrated Reporting (IR). IR framework aims to improve the quality of

information, promote a more cohesive and efficient approach of reporting, enhance

accountability and stewardship and stimulate integrated thinking, decision-making and actions

(IIRC, 2013). There is an endless development going on to perfect Integrated Reporting.

Frequently there are reports with miscellaneous results published about the strengths and

weaknesses of IR. There are e.g. researches which heavy criticize the shareholders-oriented

view of Integrated Reporting e.g., in the paper of Flower (2015). The criticism led to the

introduction of the Integrated Reporting framework in 2013 by the IIRC, with the purpose to

stimulate companies to further develop reporting and to design a better fit of the framework to

their organization.

The report of IIRC (2014) contains a recommendation prepared by a panel with

members of the six globally largest accounting firms (BDO, EY, Deloitte, KPMG, PWC and

Grant Thornton). The panel recommends firms to encourage internally innovations interrelated

with corporate reporting (IR) and initiatives for the long-term investors.

For the execution of my master thesis I am prepared with experience of the accounting

world and knowledge gained during my MSc study, therefore I use my capabilities to bring

insight in how Integrated Reporting is viewed by the market. The main objective of my master

thesis is to bring insight in and explain the relation of Integrated Reporting and information

asymmetry. To answer the research question: how is Integrated Reporting interrelated with

information asymmetry?, is the reaction examined of the bid and ask-spread and abnormal

stock returns by the implementation of Integrated Reporting within an organization.

This research starts firstly with describing the background literature, for instance what

the Integrated Reporting framework means and how it is operationalized. This is essential to

understand how the framework perhaps is affected by presence of information asymmetry.

Furthermore, I described the theories that reflect the underlying effects and structure of

information asymmetry, which are necessary to support the underlying conception of the

research hypotheses.



For the dependent variable information asymmetry is translated through two proxies.

Stock liquidity is the first proxies defined based on prior studies. For stock liquidity is expected

that firms with Integrated Reporting will have a lower bid-ask spread. The first hypothesis is

formulated as follows: Organizations with a high level of alignment with the Integrated

Reporting framework results in lowering the bid and ask-spread. To test this hypothesis the

stock liquidity model is used, which will bring insight in the variance of the bid-ask spread.

Based on prior studies is abnormal returns defined as a proxies of information

asymmetry. For firms with Integrated Reporting is a lower abnormal returns expected. The

second hypothesis is formulated as follows: Organizations with a high level of alignment with

the Integrated Reporting framework results in lowering the abnormal returns. To test this

hypothesis the abnormal return model is used, which includes the abnormal returns.

Integrated Reporting, the independent variable of the research is operationalized

through ESG-scores, which represent the performance of the capitals environmental, social and

governance. 503 Northern-American listed firms are selected including their ESG-scores, in

order to function as the sample of this research. These ESG-scores are from the sampling period

of 2010 till 2016 retrieved from ASSET4 database available in DataStream.

To map the endogeneity for this research, I have determined based on prior literature

the following control variables FIRM_SIZE, VOLUME, ROA, LEVERAGE, PROFIT and

PRICE_VOL. The summed up control variables are used for the stock liquidity and abnormal

return model.

The first regression tests the effect of Integrated Reporting on the variance of the bid-

ask spread. The significant p-value of the model indicates a negative relationship of Integrated

Reporting with the bid-ask spread. Furthermore, the first hypothesis is accepted and the null

hypothesis rejected.

There is no significant evidence found as result of the regression of the abnormal return

model. For the abnormal return model is a positive relationship found of abnormal returns with

Integrated Reporting, however there is no support found for rejection of the null hypothesis.

In order to answer the research question, it is essential to determine the reliability of the

two research models. Both models have an Adjusted R-square that are interpreted as very low,

which don’t explain much of the variance. Altogether is hard to pick which model is more

reliable than the other, by a research opinion both models would be seen as not reliable.



Based on prior research it is expected that the implementation of the Integrated

Reporting of the IIRC lowers the information asymmetry. For the proxy bid-ask spread of

information asymmetry is significant results found. For the second proxy of information

asymmetry abnormal return is no significant evidence found. This means that investors are not

able to better estimate the abnormal returns when a firm uses the Integrated Reporting

framework. The effect might be clarified by other factors, than were included in the scope of

the research. Based on the stock liquidity model is suggested that the Integrated Reporting

framework has a negative relationship with information asymmetry.

The first contribution of this thesis happens in an empirical fashion by looking at the

association of Integrated Reporting framework with the stock liquidity and abnormal returns.

This thesis covers the fact that not much empirical research was done about the effect

framework itself. Currently known studies look into the quality of the framework. The found

results indicates that the integration of integrated thinking in the organization suggest a lower

information asymmetry. Due to reliability issues of the models is hard to say that is exactly the

case.

This study looks only at the Northern-American setting excluding the European firms.

This indicates a limitation that is hard to generalize on a general scale. For further research, I

suggest to research a more global setting, by also considering the European companies and

their relationship with the different variables.

Over the years numerous academics have criticized the framework. This leads to the

objective of this thesis to contribute to the discussion in an empirical manner. The found

empirical results indicate that Integrated Reporting reduces the information asymmetry.

Integrated thinking is a phenomenon that every firm should implement in their business. This

supports the investors in order to make better choices regarding investment choices based on

the information incorporated in the financial reports. Subsequently, the IASB or other

regulators could follow the reporting situation in South-Africa where Integrated Reporting is

mandatory for South-African firms, which this research could be a forerunner in were the

development is going.

In paragraph 2 the literature according to the research of the association of Integrated

Reporting with information asymmetry. The background of framework is described and

relevant theory in order to explain information asymmetry. Paragraph 3 displays the sample



selection and the research models of the study. Paragraph 4 present the empirical results of the

study and while paragraph 5 contains the conclusions and limitations of the research.



2 Literature review and hypothesis development

Integrated Reporting has the purpose to inform and give insight to the stakeholders how the

firm is creating value over time for the entity. The provided information in the financial

statement to the market and how the market perceives the information is very vague. For

instance, when a company gives full insight on how it creates value over time for its own

organization, this will lead to better decision-making for the investors to make a choice

regarding the stock returns.

The World Bank and IMF are advocating for greater focus on facets as risk and future

development, which can all be found on the webpage of the IIRC (2017), this follows from the

present existing information gaps within corporate reports. Furthermore IIRC created

Integrated Reporting to enhance company’s accountability, stewardship and trust in order to

improve information stream and transparency of the organization. IIRC (IR, 2017) says that

when a company’s incentives are influencing negative short-term behavior, capital markets are

weak and poor leads to incorrect assessment of the company’s value. Integrated Reporting

increases the decision usefulness on efficient capital markets.

The increase of the decision usefulness for investors is not the only goal of the

implementation of Integrated Reporting. Another goal of Integrated Reporting is to manage the

information gap between the companies and their shareholders by reducing this. This

information gap is heavily associated to the main subject of this research information

asymmetry. I have chosen and constrained myself to the following four theories:

Agency theory

Adverse selection

The efficient market hypothesis

Value relevance theory

I suppose that these theories are the most relevant theories regarding my topic. Those theories

will support the understanding of the interrelation of Integrated Reporting with information

asymmetry.

Integrated Reporting

The following subparagraphs are dedicated to the background information of the Integrated

Reporting framework of the IIRC.



In the past decade there has been an increase in the demand of the stakeholder for more

non-financial data in the financial reports. Preferred is a combination of financial and non-

financial information in the accounting figures. This combination will give a global picture of

the entire organization including the long-term effect of the decision making on the business

(Jensen & Berg, 2012). Van Zijl el al. (2017) mentioned that the IIRC (2013) described that an

integrated report is not just an aggregated report consisting of traditional corporate reports and

sustainability reports. The goal of IIRC is to bring insight on how an entity creates sustainable

value for the investors by incorporating financial and non-financial performance in one report

(IIRC, 2013; de Villiers et al., 2014; King, 2016). The IIRC formulates Integrated Reporting

as follows: “A process that is based around integrated thinking to stimulate entities to release

integrated reports about the value creation process over time” (IIRC, 2013, page. 34). The IIRC

(2013, p. 34) defines Integrated thinking as follows: “The consideration by several financial

and operational units and the capital is been used or affected. Integrated thinking takes in

account the value creation over the short, medium and long-term of the decision making and

actions effect.” Integrated Reporting shifted the emphasis on the value creation process from

looking on a traditional way at the financial reports towards a more forward-looking approach.

The IIRC is demanding an explanation from the reporting entity on how it used their financial,

manufactured, human, intellectual, natural, social and relationship capital in order to create

value over time for its different stakeholders (IIRC, 2013). This process should be in line with

the business model, strategy and the key risks faced by an entity (Stubbs and Higgins, 2014;

Raemaekers et al., 2016).

2.1.1 IIRC Framework

In 2013, the IIRC released the Integrated Reporting framework for the general public. The

framework doesn’t contain hard requirements in the form of e.g. key performance indicators,

it is mainly based around principles. The IIRC requires managerial involvement while

preparing an integrated report. In this section, I will describing the guiding principles and the

content elements. Therefore, follows an explanation of the seven principles and eight elements

that are key for the understandability of the framework and organizations their operations. The

guiding principles and content elements are significant and highlight the value creation for the

stakeholders.



2.1.2 Guiding principles

The long-term and strategic focus is incorporated in the first principle of the Integrated

Reporting framework, which would benefit the public by encouraging firms to incorporate

more future information in their financial reports. The principle is state as follows: a) “An

integrated report should provide insight into the organization’s strategy, and how it relates to

the organization’s ability to create value in the short, medium and long term and to its use of

and effects on the capitals,” (IIRC, 2013, p. 16).

Connectivity of information is incorporated in the second principle which is related to

the term ‘integrated thinking’. The principle is stated as follows: b) “An integrated report

should show a holistic picture of the combination, interrelatedness and dependencies between

the factors that affect the organization’s ability to create value over time,” (IIRC, 2013, p. 16).

The voice of the stakeholders concerning the relationship is incorporated in the third

principle. Disclosing information according to the framework strengthens the trust of the

stakeholders in the company. Integrated Reporting increases the transparency and

accountability of the company. The principle is stated as follows: c)“An integrated report

should provide insight into the nature and quality of the organization’s relationships with its

key stakeholders, including how and to what extent the organization understands, takes into

account and responds to their legitimate needs and interests,” (IIRC, 2013, p. 17).

Materiality is the key point where the fourth principle focuses on. Materiality is a key

decision-making element for the investors. Materiality is incorporated in integrated reports to

reach a higher level of information quality. According to Mio (2016) investors should be an

important consideration within the integrated reports. The principle is stated as follows: d) “An

integrated report should disclose information about matters that substantively affect the

organization’s ability to create value over the short, medium and long term,” (IIRC, 2013, p.

18).

Integrated reports should be formulated concisely, this facet is incorporated in the fifth

principle. This must leave out all less relevant information that the firm would document in

their reports which could hide fundamental and important information about the strategies,

governance and firm performance. So all the information must contain added value in the

integrated reports. The principle is stated as follows: e) “An integrated report includes

sufficient context to understand the organization’s strategy, governance, performance and

prospects without being burdened with less relevant information,” (IIRC, 2013, p. 21).



For organizations it’s crucial to have a good designed internal control and governance

structure, which will in turn enhance the reliability and completeness of the produced reports.

This is incorporated in the sixth principle which is stated as follows: f) “An integrated report

should include all material matters, both positive and negative, in a balanced way and without

material error,” (IIRC, 2013, p. 21).

Consistency and comparability are incorporated in the seventh principle. To enhance

the consistency and comparability concepts, integrated reports should stay consistent from one

period in comparison to the earlier periods unless changes are needed. The principle is stated

as follows: g) “The information in an integrated report should be presented: a) On a basis that

is consistent over time b) In a way that enables comparison with other organizations to the

extent it is material to the organization’s own ability to create value over time,” (IIRC, 2013,

p. 23).

2.1.3 Content elements

There are eight content elements that are included in the framework of the IIRC, which firms

that produce integrated reports should answer. The first content element is about the

organizations identifying and incorporating the core mission and vision in the integrated report

and also the effects of the external environment on the organizations culture, ethics, value and

operating structure. The content element is stated as follows: a) “What does the organization

do and what are the circumstances under which it operates?” (IIRC, 2013, p. 24).

Governance is incorporated in the second content element of the framework. This

element is about how the governance creates value towards the stakeholders. The content

element is stated as follows: b) “How does the organization’s governance structure support its

ability to create value in the short, medium and long term?” (IIRC, 2013, p. 25).

The organizations business model is the base for the third content element. This element

is focused on the value creation over time by the business activities. The content element is

stated as follows: c) “What is the organization’s business model?” (IIRC, 2013, p. 25).

The key risks and opportunities play a central role in the fourth content element.

Organizations should identify and incorporate the effect of the value creation of the key risks

and opportunities in the integrated report. The content element is stated as follows: d) “What

are the specific risks and opportunities that affect the organization’s ability to create value

over the short, medium and long term, and how is the organization dealing with them?” (IIRC,

2013, p. 27).



The strategy and resource allocation are playing a central role in the fifth content

element. Integrated reports should include how companies are implementing and achieving

strategic objectives over time and how they separate themselves from their competition. The

content element is stated as follows: e) “Where does the organization want to go and how does

it intend to get there?” (IIRC, 2013, p. 27).

Performance is a core component within the sixth content element. E.g. qualitative and

quantitative information about the performance (targets, risks and opportunities). The content

element is stated as follows: f) “To what extent has the organization achieved its strategic

objectives for the period and what are its outcomes in terms of effects on the capitals?” (IIRC,

2013, p. 28).

Outlook is a core topic within the seventh content element. What are actions/reactions

of the organizations to/towards challenges and uncertainties that they face. This gives the

stakeholders more insight and like this, the company becomes more foreseeable. The content

element is stated as follows: g) “What challenges and uncertainties is the organization likely

to encounter in pursuing its strategy, and what are the potential implications for its business

model and future performance?” (IIRC, 2013, p. 28).

Basis of preparation and presentation are playing an central role in the eight content

element. The content element is state as followed: h) “How does the organization determine

what matters to include in the integrated report and how are such matters quantified or

evaluated?” (IIRC, 2013, p. 29).

Support for IR

The pervious subparagraphs clarified the underlying thoughts of the objective of Integrated

Reporting. It is generally known that the implementation of framwork is required for the South

African and Brazilian companies (Robertson, 2015). This subparagraph describes why

organizations should embrace and implement the Integrated Reporting framework based on

prior literature.

Owen (2013) stated that old fashioned financial reporting is focused on the transactional

and operational aspect of business. Traditional financial reporting is missing the long-term

strategic and prospective analysis facets of reporting. This kind of reporting leads to a narrower

external financial reporting which explains only how the organization is creating short-term

value. Bringing insight into the long-term value creation of a business is captured by the



Integrated Reporting framework. Owen mentioned that Integrated Reporting gives a wealthier

picture of an organization. This is achieved by referring and accessing broader extended

sources than the current model. This includes making use of qualitative and quantitative data

as well.

Eccles and Saltzman (2011) find that the impact of Integrated Reporting leads to three

main benefits. According to Eccles and Saltzman are businesses benefiting of Integrated

Reporting by making better internal decisions, having better relationship with stakeholders and

a lower reputational damage. By incorporating qualitative and quantitative data, this will lead

to better risk management according to the research of Eccles and Armbrester (2011). By

incorporating this type data external advantages will arise as keeping the stakeholders satisfied

by providing nonfinancial information which give a complete, accurate and timely picture of

the organization. Providing both data leads to the third benefit which is minimized regulatory

risk. So an organization must be prepared and organized to meet the requirements of new

worldwide introduced regulations on the stock market, e.g. showing the relationship among the

organization qualitative and quantitative data.

The studies of Zhou et al. (2017) and Eccles and Krzus (2010) state that a lower cost of

capital will benefit the firm. Lower cost of capital arises from an increased reputation, a more

transparent organization and information that fulfills the desire of the shareholders. All those

elements can be traced back to the implementation of the Integrated Reporting framework,

which does not only disclose financial information but also environmental, social and

governance (ESG) related information (Eccles & Krzus, 2010). One finding of Zhou et al.

(2017) is that companies with a higher degree of implementation of the integrated framework

experience a lower cost of capital. This is primarily due to the creation of lower information

risk for the shareholders. Another finding of Zhou et al. (2017) is that the framework is relevant

to the capital markets. There is a negative relation found between ‘connectivity’, ‘newness’

and ‘forecast errors’. This shows that new information incorporated within integrated reports

advances the accurateness of forecasts. There is little evidence found that height of alignment

and earnings forecasts are negatively related.

Criticism on IR

At the moment Integrated Reporting is in an advanced stage of knowledge. A number of

researchers expressed criticism on the framework of the IIRC. An often cited paper is the

Flower (2015) paper. Flower’s deeply criticized the incorporation of the stakeholders within



the framework. Financial capital providers and funders are the targeted audience of Integrated

Reporting. One of the objectives of the framework is to bring insight on how firms create value

over time for their stakeholders. Despite this, it is one of the objective of the Integrated

Reporting framework that is not interpreted in the best interest of the stakeholders according

to Flower (2015). According to IIRC (2013) this is only the case when it is material in towards

creating value for its own organization.

Another criticism on Integrated Reporting is how human capital is processed in the

integrated reports. The IIRC describes human capital as follows: “Human capital as the

people’s their competencies, capabilities and experience, and their motivations to innovate and

there:

alignment with and support for an organization’s governance framework, risk

management approach, and ethical values ,

ability to understand, develop and implement an organization’s strategy,

loyalties and motivations for improving processes, goods and services, including their

ability to lead, manage and collaborate” (IIRC, 2013, p. 12).

The people that represent the human capital of a firm, as determined by the IIRC lack intrinsic

value according to Flower. The contribution of the people forms the core element in the

determination of the value of the human capital. This determination leads to omitting the people

who have not contributed to the value of the business. The losses that people make are caused

by e.g. pollution, is not part of the framework. This shows the narrow scope of the framework.

The same applies for the nature capital, this capital looks into the extent of how it impacts the

production process and how it omits the effect on the environment. The IIRC aware of the fact

that the several capitals are not fully integrated in the process and takes its stewarding role.

Currently, it is predominantly that information over the several capitals are disclosed when

regulation is in play. In the framework of IIRC it is stated that companies should accept their

stewardship responsibilities to meet the expectations of their stakeholders. Flower (2015) is

again pointing out the limited incorporation of the stakeholders in the framework. Again the

value of stakeholders, society and environment is only taken into account when it is material

to its own business processes. The opinion of Flower is embroidered on the work of Brown &

Dillard. Brown & Dillard (2014) are emphasizing the missing underlying ideas of economics

of the stakeholders, society and environment.



IIRC (2013) mentions when financial capital is fully utilized, society and environment

will profit from it. Flower (2015) mentions that the perception of the stakeholders is not taken

into account, while benefits are calculated in advantage of the firms and the costs of the

stakeholders as a disadvantage. An example that Flower (2015) gives is, when a firms succeeds

in lowering the employee wages this becomes a benefit for the business, but misses the fact

that the loss is taken by the employees and this is not incorporated. Furthermore Thomson

(2015) votes for emphasizing the underlying ideas of the sustainability difficulties to create a

sustainable case. This includes a wider emphasis on more elements than traditional reports had

and a shift in focus towards the stakeholders.

2.3.1 Denial of the criticism

The critical paper of Flower (2015) got challenged by Mio (2016) in her book “Integrated

Reporting A New Accounting Disclosure”. The core and essential principle ‘materiality’ in the

IR framework is heavily criticized by the paper of Flower (2015). Materiality in the framework

includes only the investors. IIRC (2013, p. 17) state in the framework that satisfying all

stakeholders is not part of the objectives. IIRC (2013) define materiality as follows: “an

element is material when it could substantively influence the opinion of users of the financial

statements (investors) with regard to the value over the short, medium and long term”.

Mio (2016) says the framework of IIRC should be viewed through a ‘dynamic’

viewpoint rather than a ‘static’ one.

How an issue is impacting the decision making of the investors is included under the

static perspective. The actions of the stakeholders and the reactions of the firms are a missing

component in the static perspective. Most researcher use the static perspective for their

researches.

The dynamic perspective considers a broader scope than the static perspective. It

includes the actions of the stakeholders and the reactions of the firms. The dynamic perspective

makes sure that the stakeholders have more input and control over what companies disclose or

leave out the integrated reports. The stakeholders must have an dynamic attitude towards this

aspect.

There are still questions about were the targeted audience in the framework of IIRC is

in place. It might be the case that the choices could be an effect of political actions. The

framework gives the freedom to interpret the concept value creation by your own perception.



2.3.2 Criticism versus the supporting literature

Over the last decade Integrated Reporting gained its momentum in the scientific world (Mio,

2016). Currently investors are prioritized in the information that is been served. Nonetheless

Mio (2016) argue this is not the case. The IR framework considers investors as the targeted

audience, however investors are left out in the determination of the integrated reports.

Nonetheless Mio (2016) votes for a more dynamic approach. My attitude towards this subject

is that these drivers are inadequate. The IIRC should review the given comments and perhaps

make changes to the framework.

According to Thomson (2015) it is possible for the IIRC to create a sustainable case.

In order to realize a sustainable case the IIRC must move their situation from a static towards

an more dynamic attitude. An example is the earlier mentioned case that all the stakeholders

are affected by the choices/actions made by a specific firm, which only would benefits the

investors.

From my point of view, I don’t think corporate reporting is all about the accounting

numbers. It is mainly about the accounting techniques that arrange the numbers on the balance

sheet in the annual report. The Integrated Reporting framework can be the solution in creating

a more sustainable case, which would create value on the short- and long-term for the firm and

their stakeholders.

Theoretical framework

2.4.1 Agency theory

One of the theories that explains the cause of information asymmetry is the agency theory.

Jensen and Meckling (1976, p.308) define an agency relationship as a contract between a

principal and an agent, e.g. a company and their employees. Within this relationship there is

some decision making delegated to the agent. The principle must create an optimal setting with

the proper incentives for the agent to make right decisions that favor the entity best as possible.

For example, the principle which incurs monitoring costs will influence the decision making

of the agent in a positive manner. In other situations principal pays the agent in form of a

bonding cost or incurring compensation costs to incentivize the agent to take decisions, that

would not affect the principal in a negative manner. The information asymmetry arises from

the aspect of when there are no costs occurred within the agency relationship and there is no



assurance that the agent will make the ideal decisions for the principal when there are zero cost

involved (Jensen and Meckling, 1976).

Separation of ownership and control creates well-known agency problems within

companies (Badertscher et al, 2013). Badertscher et al (2013) says that managers, ‘insiders’,

are having more information than e.g. stakeholders, ‘outsiders’. So, the outsiders are

demanding corporate reports that contain very detailed firm specific knowledge to make useful

decisions regarding their maximization of their stock return. As I earlier mentioned the IIRC

(2017) stated that they reduce this information asymmetry by narrowing the information gap

with their Integrated Reporting. This research is about whether this is significant.

Another agency problem is the ‘lemons’ problem. The ‘lemon’ problem addressed by

Akerlof (1970) who has a different opinion on the information asymmetry between companies

and their stakeholders. This problem regards the information asymmetry between the buyer

and seller of the value of an investment or product. Healy and Palepu (2001) described the core

problem, this is when the investors of an enterprise cannot distinguish the bad type companies

that pretend that their ideas as good form the good type. Again capital markets enhance the

‘lemons’ problem by overprizing bad ideas and underpricing good ideas. This is a very

important subject because one of the goals of Integrated Reporting is explaining how it creates

value over time for an entity, which again resolves the ‘lemons’ problem.

2.4.2 Adverse selection

Available information on the market is very crucial for the trading choices investors make. Due

to the difference in how well the investors are informed, differences in bidding and asking price

are caused. For this effect Stoll (2000) found evidence in his research. Stoll (2000, p. 1482) has

elaborated on the researches of scholars Copeland and Galai (1983), Glosten and Milgrom

(1985), and Kyle (1985). Stoll (2000, p. 1482) included in his paper two branches often not

distinguished. The work of Copeland and Galai (1983) is foundation for the first branch. The

first branch is about the difference between value of the trading options and the posted quotes.

There is a time lag between posting and removing quotes. When new information is published

and a quote is placed, then the investor or dealer would lose. The second branch is more

prevalent with superior information, which suggests the presence of information asymmetry.

There is a risk that adverse selection would incur that a person with superior information would

take the bid or ask price. The informed traders would buy at the ask price when they know its



value is a higher price and sell at the bid-price when its value is a lower price (Stoll, 2000, p.

1482).

Stoll (2000) mentioned that information asymmetry can be measured by the bid-ask

price spread and is seen as a proxy information asymmetry. Inventory holding, order processing

and asymmetric information costs are facets of bid-ask spread. The asymmetric information

costs aspect within the bid-ask price spread reflects and measures how well the investors with

private information can influence the difference within the bid and ask spread.

2.4.3 The efficient market hypothesis

The ownership in form of stock capital and the allocation is a significant aspect on the capital

market. The valuation of stock capital must happen in an efficient way, in order to provide the

right signal towards the capital market to create better decision usefulness for the investors for

better investment selections. So, it is very fundamental to incorporate all available information

in the market prices. There are lots of papers available about efficient markets. The most cited

and quoted paper is the Fama (1970) paper. Fama’s paper reviewed all the existing literature

on the efficient markets model. The review is done by comparing the adjustment of the security

prices at three levels of efficient markets, weak form, semi-strong form and strong form. These

three level stand for how well markets are incorporating newer information into the prices. The

strong-form is that some investors or parties are the only with the superior information like the

case in a monopoly. These could be parties like specialists or insiders of an organization. This

seems to be an extreme case, but this efficiency markets model is used as a benchmark to judge

different market efficiency cases. Under the semi-strong form it is expected that the market has

taken all noticeable and accessible information such as announcements and annual reports into

account. Markets that are covered by the ‘weak-form’, only take historical firm existing

information (e.g. returns) into account in their prices.

For the capital markets it matters how much private information companies

communicated to the markets, in order to the market to be efficient. So, for this research I will

be examining the effect of integrating reporting on the information subset within the company’s

stock prices.

2.4.4 Value relevance theory

Only in South Africa, application of the framework Integrated Reporting is mandatory. Where

standard corporate reports only report financial information to the investors, Integrated



Reporting adds non-financial information to the information flow, which aids for the investors

to better assess the value of the organization.

Prior research showed a positive association between standard sustainability reports and

the firm value of an enterprise. These standard sustainability reports contain mainly

nonfinancial, social, ecological and economic content (Berthelot et al., 2012). Berthelot et al.

(2012) concludes afterwards by better understanding of value relevance study that the

stakeholders can better estimate future cash flows of enterprises, all due to the relevance of the

incorporated information in the sustainability reports. Berthelot et al. (2012) researched

Canadian enterprises that published sustainability reports on the Toronto Stock Exchange's

S&P/TSX Composite Index. However, there is very little research’s available and done about

the added value to the firm value by IR. Mervelskemper and Streit (2017) stated in their paper

that prior research (Malik, 2015) investigated the value relevance of sustainability reports.

Other researchers (Orlitzky et al., 2003; Margolis et al., 2009; Fulton et al., 2012) found a

positive but small relationship between value creation and sustainability reports.

Mervelskemper and Streit find an association between value relevance and entity reporting on

the corporate governance, environmental and social pillars (sustainability reports). In the paper

about value relevance Barth et al (2001) mentioned that accounting amount contains value

relevance if it is cohesive with equity market values. This means that all the relevant

information to the investors is incorporated in the stock prices.

Authors Holthausen and Watts (2001) classify the relevance of important papers in

three categories according the relevance theory. The three categories are:

Relative association studies (Category 1)

Incremental association studies (Category 2)

Marginal information content studies (Category 3)

The first category compares the relative association of the stock value and the change with the

underlying measures (e.g. IFRS with US GAAP). The second category is about the explanatory

power of the accounting numbers on the stock prices or future returns. Scholar Venkatachalam

(1996) created a trustworthy estimation model by looking into accounting figures that could

predict the values. The third category looks into the add value of accounting figures towards

available information. All together the value relevance theory can be conceived broadly. This

theory is basically investigating the effects of managerial choices, underlying measures or

accounting figures on the value of the prices or returns.



During this research I am testing the level of information asymmetry related to the choice of

releasing an Integrated Reporting or holding on to the current corporate reporting method.

Hypothesis development

The research of scholars Lee and Yeo (2016) is predominantly the reason that information

asymmetry is linked to Integrated Reporting. Businesses that are in line with the framework

are more likely to have a higher percentage of external investors and a higher firm valuation

according to lee and Yeo (2016). The scholars mention that the framework reduces the

information asymmetry between the internal and external parties. Stubbs and Higgins (2014)

brought insight in how the level of provided information is related with how firms use the

Integrated Reporting framework. The implementation of the framework did not resulted in to

a reduction in information asymmetry according to the evidence found by Stubbs and Higgins

(2014). Firms are not obliged to provide information towards investors regarding their

investment decision making. Overall is the subject investors in the framework misunderstand.

To make information asymmetry explicit, I formulated proxies based on prior literature.

2.5.1 The bid and ask-spread

The researchers Bischof and Daske (2013) found that many oversight watchdogs as IIRC use

stock liquidity as an element within the disclosure regulation design. Many scholars delivered

researches with results that strength the association quantity of disclosures and the stock

liquidity (Healy et al, 1999), (Leuz & Verrecchia, 2000), (Welker, 1995). The bid and ask-

spread is a stand-in of the firm’s stock market liquidity which Bischof and Daske (2013) used.

On the market there are two types of traders: definable liquidity and informed traders

(Glosten, Milgrom, 1985). Informed traders have the privilege that they have private

information that is not incorporated in the market security prices. Liquidity traders trade on

other information apart from having hidden information. When liquidity and informed traders

are involved in the same transactions, the informed traders are ending up with a loss, this is

reflected in the bid and ask-spread (Glosten, Milgrom, 1985). The bid and ask-spread is

basically the difference between the price of the traders are willing to buy or sell from or to the

experts (Amihud & Mendelson, 1986). This is in line what Copeland and Galai (1983), and

Glosten and Milgrom (1985) indicated that the association of a higher level of information

asymmetry leads to a wider bid and ask-spread for the traders. As earlier mention in paragraph

2.4.2 is the bid and ask-spread functioning as a proxy for information asymmetry.



Bischof and Daske (2013) and Roulstone (2003) let the bid and ask-spread function as

a stand-in of the firm’s stock market liquidity. The only proxy for market liquidity that is use

is bid and ask-spread within theoretical and empirical literature according to Callahan et al.

(1997). Guenster el al. (2011) and Jo and Harjoto (2011) found that CSR is positive related

with the enterprise value. For this research I will add the enterprise value in the bid and ask-

spread which would help me to better assess and distinguish larger and smaller firms.

Based on the existing papers, I formed a hypothesis for testing the bid and ask-spread

as the stand-in for information asymmetry. See here below hypothesis 1 of this research.

Hypothesis 1: Organizations with a high level of alignment with the Integrated

Reporting framework results in lowering the bid and ask-spread.

If the hypothesis is supported, than can be suggested that Integrated Reporting has a negative

effect on the bid and ask-spread. Therefore when the hypothesis gets rejected, that indicates

that Integrated Reporting has a minimal effect on the information asymmetry.

2.5.2 Abnormal returns

Furthermore during this research I investigate whether Integrated Reporting impacts the

decision making of the investors regarding to the stock returns. Past researches sees abnormal

returns as an stand-in of information asymmetry. The study of Nichols and Wahlen (2004) is

assisting me to assess whether Integrated Reporting positively affects abnormal stock returns.

Nichols and Wahlen (2004) looked into how the changes of abnormal annual stock returns is

affecting the change in yearly earnings including abnormally yearly stock returns. An

integrated report contains in comparisons with traditional reports more non-financials

information about the business. The non-financial information is incorporated within the

accounting numbers in the financial statements. This leads for the investors to better decisions

making about their investments. This is earlier described in subparagraph 2.4.3. As earlier

mentioned for the capital markets it matters how much private information companies

communicated to let the market be efficient. All the future expectation of the direction is

incorporated with in the current stock price. So, this mean that the stock price would be based

on more superior information and secondly leads this a lower abnormal stock returns e.g., when

an organization has implemented the Integrated Reporting framework. (Nichols & Wahlen,

2004). The research of Nichols and Wahlen (2004) is the reason to add abnormal stock-returns

to determine the association of Integrated Reporting with information asymmetry.



Nichols & Wahlen (2004) continued were the prior study of Ball & Brown (1968)

stopped. My calculation will be identical in comparison to Nichols and Wahlen (2004). For

this research there will be a limit, this is further explained in the next chapter. Nichols &

Wahlen used the formula: total business stock-return – (minus) day return market index, to

calculate the abnormal stock returns.

Based on the described papers I formed a hypothesis for testing the abnormal stock-

returns as the stand-in to examine and making the interrelation explicit between Integrated

Reporting and information asymmetry. See here below hypothesis 2 of this research.

Hypothesis 2: Organizations with a high level of alignment with the Integrated

Reporting framework results in lowering the abnormal returns.

If the hypothesis is supported, than can be suggested that Integrated Reporting is negatively

related with abnormal stock-returns. It would lead to better estimation of the abnormal stock-

returns which removes the uncertainty of the stock-returns. I would assume this based on the

existing theory and research. Therefore when the hypothesis gets rejected, that indicates that

Integrated Reporting has a minimal effect on the information asymmetry.

Paragraph summary

Integrated Reporting ensures that the stakeholders receive a broad perceptive of the whole

organization of a company. By giving insight in the financial as the non-financial data and

having an efficient market potential investors get the opportunity to better assess the future

cash flow to make better investment decisions. The effect of minimized information asymmetry

must be traced back in the bid and ask-spread and abnormal stock-returns. This study is

bringing if Integrated Reporting is negatively related with the stock liquidity (information

asymmetry), which is translated in to two proxies bid and ask-spread and abnormal stock-

returns.



3 Data and research design

This paragraph contains how the sample is selected and which databases or data sources the

data is retrieved from, all to explain the interrelation of Integrated Reporting and information

asymmetry. Additionally, in this paragraph are the stock liquidity and abnormal returns model

explained in detail. Furthermore, Libby boxes are added that represent the framework of the

research that shows how the examining process of the interrelation. This framework is the

backbone of this study. The models are based and elaborate on existing and prior studies.

Sample selection

Since 2010, South-African corporations are compulsory to use Integrated Reporting as their

reporting standard and was acknowledged in more and more countries worldwide (Jones,

2015). Due to the rise of IR in 2010, I choose to start the sample period of the data from 2010.

Eccles and Krzus (2010) their criticism in their One report: Integrated Reporting for a

sustainable strategy shifted to how IR should be implemented within companies. The report of

Eccles and Krzus (2010) made The IIRC presented a framework in 2013 as a response to this

riticism. For this study I choose to run the sample till the latest accessible year 2016.

The scope for this study comprehends only North-American based corporations. This

limitation within the research is due to impossibility to gathering the necessary data of

European companies, even with the granted access in DataStream. This forces me to focus only

on the North-American companies for this research and due the limited timespan is it not

possible for me to gather the European data by hand.

The earlier formulated research question is being answered and the interrelation is

examined by using a sample of 600 North-American with the biggest market capitalization,

that represents the entire population in the US. These 600 companies are retrieved out the

DataStream. In the sample are e.g. Apple Inc, Amazon.com Inc and Alphabet Inc inlcuded.

Due the research of Eccles and Krzus, that showed similarities between Integrated Reporting

and CSR, I used ESG-scores out the ASSET4 ESG database as a proxy for Integrated

Reporting. The way financial, environmental, social and governance information are

incorporated in the financial reports is very similar in both type of reporting. The ESG-scores

stands for the overall performance subdivided in four pillars economic, environmental, social

and corporate governance (see figure 1).



Figure 1 ESG-framework

For the research I took the assumption that in 2010 the firms start adopting Integrated

Reporting, makes all the adopting firm years equally. This could be a limitation of the study. I

sort the available companies on market capitalization, and retrieved ESG-scores of the 600

companies with the biggest market capitalization including Apple, Alphabet/Google and

Amazon. Subsequently dropped 97 enterprises from my sample as result of missing the

matching data. Altogether my final sample contains 503 enterprises started from 2010 till 2016.

The final sample represents the independent variable of the research and is used for the two

models of the research explained in subparagraphs 3.3.1 and 3.3.2. See table 1 the final sampled

that is expressed in observations years.

Table 1 Final Sample



Data sources

To collect the necessary data of the dependent variables I used first the database The Center

for Research in Security Prices (CRSP) in WDRS. I retrieved the stock prices, bid & ask prices,

distributed dividends and the S&P 500 returns to compute the abnormal returns and spread of

the stocks. I used DataStream to retrieve the required data to compute the control variables:

firm size, volume, ROA, leverage, profit and price volatility.

Stock liquidity model

In most researches (Glosten & Milgrom, 1985; Copeland & Galai, 1983) is found an effect that

a higher level of information asymmetry leads to a wider bid and ask-spread for the investors.

An assumption is that the bid and ask-spread remains persistent throughout the examined

period. This bid and ask-spread represents the grade of information asymmetry, inventory cost

element and order processing costs. Due to the interaction of information asymmetry, inventory

cost element and order processing costs can the bid and ask-spread experience abnormalities.

Here below is the equation of the ordinary least regression (OLS) shown (including the control

variables) to test hypothesis 1.

Model 1

SPREAD = βo + β1*ESG_SCORES + β2*FIRM_SIZE + β3*VOLUME + β6*ROA +

β8*LEVERAGE + β9*PROFIT +β10*PRICE_VOL + ɛi,t

The ESG-scores are calculated by taking the average of the performance scores of the

283 key performance indicators. To calculate the yearly bid-ask spread, I first calculated the

daily bid-ask spread by taking end of the day daily spread according to Ayaraman (2008).

Secondly, I use Harris (1994) method to transform the end daily spread to an average yearly

spread.

SPREAD =

According to prior literature I forecast and expect an effect of higher alignment with IR

in lowering the SPREAD for investors, that is coherent with hypothesis 1. This indicates a

positive relationship of Integrated Reporting with information asymmetry.



Control variables

To map the endogeneity for this research, I have determined based on prior literature the

following control variables FIRM_SIZE, VOLUME, ROA, LEVERAGE, PROFIT and

PRICE_VOL. This determination is in line with the researches of Frias-Aceituno et al. (2013,

2014), Bischof & Daske (2013), Healy, el al. (1999), Sierra et al. (2013), Roulstone (2003) and

Leuz (2003).

Total assets represents the component FIRM_SIZE of a specific company and by taking

the log the FIRM_SIZE is determine. The component firm size is functioning as a proxy for

the total available information and its effect on the market’s reaction during the event period.

Larger amount of information results into lower adverse selection. Therefore, I forecast and

expect that FIRM_SIZE has a negative association with SPREAD.

By taking the shares traded annually and dividing it by the total shares outstanding the

control variable VOLUME is determined. I used log transformation to nuance the spread of the

variable. Traders who received more opportunities are more likely to succeed in managing their

stocks inventory and recouping their losses form the knowledgeable traders from companies

with a higher trading volume ratio. Subsequently is expected that VOLUME has a negative

correlation with SPREAD.

The profitability of companies is measured by the return on assets (ROA). A positively

influencing effect of the profitability of companies on the level of disclosed information is

found by Frias-Aceituno et al. (2014). Expected is that ROA has a negative correlation with

SPREAD.

By dividing the total liabilities by the total equity you determine the LEVERAGE of a

specific firm. According to Sierra et al. (2013) a higher LEVERAGE ratio is related toward

higher probability of occurrence of an economic disaster. Altogether is expected is that

LEVERAGE has a negative correlation with SPREAD.

To calculate the PROFIT for the share capital the net income is dividend by the share

capital. Frias-Aceituno et al. (2014) found that more resources are invested into the

development of maturing Integrated Reporting by companies that are more profitable.

Altogether is expected that this leads to lesser information asymmetry.

To determine the PRICE_VOL are the annually daily returns used and showed as the

standard deviation. Holding firm stocks on a short-term is affected by more uncertainties due

the higher volatility in the firm’s stock prices. This lead to an increase in the bid & ask



SPREAD, so the traders can protect themselves against the volatility. Subsequently, Jegadeesh

et al (1993) and Stoll (1978) reported that a positive correlation of PRICE_VOL with SPREAD

can be expected.

The ε stands for the residual term. There are no implications made towards the residual

term.

Abnormal returns model

As in the literature review in section 2 mentioned and discussed are the abnormal returns

functioning as a good representation of the information asymmetry of a firm. Here below is the

equation of the ordinary least regression (OLS) shown (including the control variables) to test

hypothesis 2.

Model 2

ABNORMAL_RETURN = βo + β1*ESG_SCORES + β2*FIRM_SIZE + β3*VOLUME +

β6*ROA + β8*LEVERAGE + β9*PROFIT +β10*PRICE_VOL + ɛi,t

The ABNORMAL_RETURN represents the abnormal returns which is the second

dependent variable. The ABNORMAL_RETURN are computed by first determining the stock

returns and subtracted by the returns on the S&P 500.

Stock return =

ABNORMAL_RETURN =

According to prior literature I forecast and expect an effect of higher alignment with IR

in lowering the ABNORMAL_RETURN for investors, that is coherent with hypothesis 1. This

indicates a positive relationship of Integrated Reporting with information asymmetry. Keeping

efficient markets in mind for investors the user of integrated reports is expected that they can

make better forecasts about the stocks returns of a firm. The same control variables discussed

in 3.4 for SPREAD are also applicable for ABNORMAL_RETURN.

Testing

The proxy of IR ESG_SCORES are tested if there is any effect on the SPREAD and

ABNORMAL_RETURN. Initially I will start with ordinary least squares regression if there is



any statistically significant effect of X on Y. Subsequently a multivariate analysis is executed

to look for validation of the two models in accordance with univariate analysis. Furthermore

difference in difference test is used to examine if there is any impact by the Integrated

Reporting framework on the SPREAD and CAR. Last but not least robustness tests are

executed. Subsequently are from these tests the inferences of the hypotheses and the answer of

the thesis question derived. The thesis question is : “how is Integrated Reporting interrelated

with information asymmetry”.

Framework

The regression model of the research is testing the effect of ESG-scores on the bid-ask spread

and abnormal return. To see and prove if the test are actually testing what it claims and purports

to measure, is all captured by the construct validity.

For the independent variable Integrated Reporting are the average ESG-scores used as

a proxy. This is very directly designed which may can be a limitation of the research.

Stock liquidity is translated into SPREAD that is computed by taking average

differences of the daily ask and bid prices to determine the yearly average spread. The yearly

abnormal returns are computed by taking the average of the subtracted stock day returns from

the market day return which are in this case the returns on the S&P 500. The Libby boxes of

the research are shown in figure 2 in the appendix that shows and paints in an arranged manner

how the interrelation of Integrated Reporting with information asymmetry is going to be tested.

The two upper boxes reflect the concepts and are translated in operational measures in the

lower boxes. In the separate boxes are the control variables added. For the research question

there are two hypotheses hypothesized that the framework is positive interrelated with

information asymmetry. This means that is expected that Integrated Reporting positively

influences the outcome of the SPREAD and ABNORMAL_RETURN.



4 Empirical results

This paragraph contains the empirical results of the executed tests and overall analyses of the

research hypotheses executed during the research. To test the normality of the research sample

the descriptive statistics and the correlation of the research variables are shown and explained.

Furthermore, is a regression executed and analyzed for the two research models.

Descriptive statistics

In table 2 are the number of observations per year displayed. The 3,155 observations are

representative of the data set originated from 503 North-American companies. The

observations are approximately equally distributed over the sample years from 2010 to 2016.

Table 2 Number of observations per year

For the descriptive statistics are the number of observations, means, standard

deviations, minimum and maximum presented in table 3 for the independent, dependent and

control variables. The total of 3,155 observation firm years represent the research sample. The

independent variable ESG-scores has a mean of 59.18693. The dependent variables bid-ask

spread and abnormal returns have respectively a mean of 0.0237083 and 0.003058. For the

control variable firm size is a mean displayed of 16.65642. For volume is a mean displayed of

16.65642. The mean of profit is 0.0397719. The mean of ROA is 0.0621177. For leverage is a

mean displayed of 0.4875014. The mean of price volatility is 24.35635.



Table 3 Descriptive Statistics of sample companies with ESG-scores before winsorizing

Notes: This table shows for the variables the descriptive statistics before winsorization total observations (N), mean, standard deviations, min,

max and median over the sample period 2010-2016.

4.1.1 Normality test

For the variables bid-ask spread and abnormal return are their normality tests executed to

determine if the distribution of the data sample is normally distributed. The skewness and

kurtosis tests and Shapiro-Wilk test are both significant 0.000, additional test values under 0.05

indicate a non-normal distribution for the two variables. The box plots of the variables

displayed in table 12 and 13 in the appendix illustrates that the distribution is heavily effected

by outliers in the sample. An observation that strongly differs from the other observations in

the sample are described as an outlier (Field, 2013). One of the methods to eliminate outliers

is winsorization. With winsorization the observation in the lowest and highest percentile

respectively 1st and 100th are equalize to the 2nd and 99th percentile in the observation sample

by using the mean of bid-ask spread and abnormal return as a reference point. The means of

the variables bid-ask spread and abnormal return after winsorizing are much better shaped,

despite the variable can be susceptible to reliability and inaccuracy errors, I assume that the

variable are normally distributed. The winsorized values of the variables are presented in table

11 disclosed in the appendix. Furthermore, are in the appendix table 12 and 13 presented, that

shows the transformation of the distribution by displaying the histograms and box plots of the

variables bid-ask spread and abnormal return before and after winsorization.



4.1.2 Pearson correlation

This section is dedicated to the analysis of the correlation between the research variables. In

table 4 are the Pearson correlations of the different variables displayed in order to look for any

mutual correlations and to exclude any multicollinearity issues within the model. The

correlation values show the extent to which two variables are coherent and if there is a statistical

relationship/effect. Pearson correlation p-values of less than 0.05 and 0.01 are being labeled as

significant. The negative correlation between ESG_SCORE and SPREAD shown in table 4 is

significant. By reporting ESG-scores in the financial reports of firms the spread decreases with

0.1461. Table 4 shows an insignificant negative correlation between ABNORMAL_RETURN

and ESG_SCORE. E.g. when report ESG-scores in their financial reports the abnormal returns

decreases with 0.0116. This decrease meets the earlier expectations.

There is evidence found for a positive significant correlation in table 4 of SPREAD

with the control variable ROA (0.0733) and a negative significant correlation of the control

variables FIRM_SIZE (-0.1125) and LEVERAGE (-0.0610). In table 4 is visible that

ABNORMAL_RETURN is significantly positive correlated with ROA (0.0541) and

negatively with FIRM_SIZE (-0.1007) and LEVERAGE (-0.0541).

The control variables in the framework are generally weak and moderate correlated,

except for the significant positive relationship of VOLUME with PROFIT (0.6149), which is

strongly correlated. Variables with correlations values between 0.6 and 1.0 (-0.6 and -1.0)

indicate a strong positive (negative) linear relationship. The relationship VOLUME with

PROFIT is the only correlation that is classified as a strongly correlated relationship, except

from the one strongly related correlation there is no reason to believe that multicollinearity

issues are present. This is consistent with Variance Inflation Factor (VIF) of the variables that

is below 10, which indicates no multicollinearity (Table 16 in the appendix). Altogether there

is no reason to assume that there is any interference with the OLS assumptions summed up in

the appendix.

The Pearson correlations assess linear relationship, while an additional test of Spearman

correlation also tests the relationship whether it is linear or not. Main reason why the Spearman

correlation test is used, is to assure that the correlations calculated are not driven by several

extreme found observations. Altogether there are no significant differences with the Pearson

correlation. In table 5 are the Spearman correlations displayed (Veenman, 2013).

University of Amsterdam MSc Accounting & Control 2017/2018 thesis “Interrelation of Integrated Reporting with information asymmetry” by Jacfar Yusuf (2018).

Table 4 Pearson correlations.

Notes: Table 4 and 5 shows respectively the Pearson and Spearman correlations. Variables with correlations values between 0.6 and 1.0 (-0.6 and -1.0) indicate a strong positive (negative) linear relationship.

Table 5 Spearman correlations


by Jacfar Yusuf (2018).

4.1.3 Homoscedasticity

Regression analysis contains several assumptions including homoscedasticity. When the

error/noise terms of independent variables have the same variance in the model, the assumption

is applicable, that the model contains homoscedasticity. When this variance differs

significantly there are reasons to assume that there is any heteroscedasticity in the model. Thus

heteroscedasticity occurs from the absence of homoscedasticity. Heteroscedasticity shows that

the standard errors are influenced by biases. Their biased standard errors are functioning as a

central element in testing the model, which lead to wrong interpretations of the significance

coefficients. The Breusch-Pagan test showed a significant p-values for both research models,

which indicates heteroscedasticity. I order to create more reliable input for the regression test,

I firstly created ‘robust’ standard errors and then I clustered the standard errors for both models

as suggested in the Stata manual (Veenman, 2013). The ‘clustered’ standard errors directly also

fix the issues with serial correlations.

Regression analysis

This paragraph analyzed the preformed regressions of the stock liquidly and abnormal return

models explained 3.3 and 3.5, which are displayed respectively in table 6 and 7.

During the first regression the dependent variable SPREAD is tested. The results found

during testing hypothesis 1 are displayed in table 6. The adjusted R-square of the stock liquidity

model is 0.0325, that indicates the explanatory value that the variance of dependent variable is

about 3% explained by the regression model. The significant p-value of the Prob>F test

indicates that the models coefficients are all nonzero. Now it can be stated that the independent

variable reliably determines the dependent variables. Prior literature suggested that ESG-scores

(IR) are negative related with the bid-ask spread. Table 6 shows a negative predicted coefficient

sign of -.0004629 with a significant p-value of 0.000. This finding is in line with hypothesis 1

that organizations with IR have will a lower bid-ask spread. As earlier mentioned, I used the

robust and clustered standard errors, which could weaken the conclusions derived out the

model.

For the controls variables PROFIT and ROA in the stock liquidly model are the findings

statistically significant, there are respectively negative and positive relations found with

SPREAD. The negative relation of FIRM_SIZE with SPREAD is in line with the predicted

negative association based on the prior empirical results. This relation is not significant.



Subsequently for the control variable VOLUME is positive related with SPREAD, while a

negative association was expected. For this relationship there is no significance evidence

found, which indicates that it would not materially affect the SPREAD. The negative signs of

LEVERAGE and PRICE_VOL are not statistically significant, although the signs are

consistent with the expected signs drawn from prior literature.

Table 6 Regression Analysis of SPREAD

Notes: In this table are the results of the regression displayed of the dependent variable SPREAD from the sample period 2010-

2016.

For the second regression of the research is the dependent variable ABNORMAL_RETURN

tested. The results found during testing hypothesis 2 are displayed in table 7. The Adjusted R-

square is 0.0186, that indicates the explanatory value that the variance of dependent variable is

about 2% explained by the regression model. The significant p-value of the Prob>F test

indicates that the models coefficients are all nonzero. Now it can be stated that the independent

variable reliably determines the dependent variables. Prior literature suggested that ESG-scores

(IR) are negative related with the abnormal returns. Table 7 shows a weak positive predicted

coefficient sign of .0000202. This sign is inconsistent with the earlier predict negative sign

based on prior literature that organizations with IR will have a lower ABNORMAL_ RETURN,

however for this association there is no significant evidence found. This finding is not in line

with hypothesis 2, that organizations with IR will have lower abnormal returns. As earlier



mentioned and used for the stock liquidity model, I will use the robust and clustered standard

errors of the abnormal return model.

For the controls variables FIRM_SIZE and ROA in the abnormal return model, there

are negative signs found, which are both statistically significant. For both variables, the

findings are consistent with earlier formulated predictions that they lower the Abnormal

returns. Subsequently for the variables VOLUME and PROFIT there is significant evidence

found in form of a positive relationship with SPREAD, while for the variables a negative

association was expected. The negative signs of LEVERAGE and PRICE_VOL are not

statistically significant, although the signs are consistent with the expected signs based on the

literature.

Table 7 Regression Analysis of ABNORMAL_RETURN

Notes: In this table are the results of the regression displayed of the dependent variable SPREAD from the sample period 2010-

2016.

In the table here below are the outcomes of the hypotheses displayed;

Table 8 Hypotheses outcomes of the regression

Hypothesis 1: Organizations with a high

level of alignment with the Integrated

Accepted



Reporting framework results in lowering the

bid and ask-spread.

Hypothesis 2: Organizations with a high

level of alignment with the Integrated

Reporting framework results in lowering the

abnormal returns.

Rejected

In general the results of the regression analysis suggest a support for hypothesis 1 that a high

level of alignment with the IR framework leads to a reduction in the bid and ask spread.

Furthermore, there is no supporting statistical evidence found that high level of alignment with

the IR framework results in a reduction of the abnormal returns. With the efficient market

hypothesis in mind, investors’ expectations are incorporated in the stock prices. Nonetheless

there was no supporting evidence found that an higher alignment with the Integrated Reporting

framework results in an reduction of information asymmetry.



5 Conclusions

Summary

Over the years the increase in the demand for integration of non-financial data in the financial

statement led to the introduction of a sophisticated integrated framework, that is based around

integrated thinking (Adams et al., 2011). Integrated Reporting gained its momentum over the

last decade. Integrated Reporting uses financial, manufactured, human, intellectual, natural,

social and relationship to create value overtime for its investors. E.g. Owen (2013) states that

old fashioned financial reporting is primarily focused on the transactional and operational

aspect of business and fails to capture the long-term strategic and the prospective analysis facets

of reporting. These shortcomings are being covered by the Integrated Reporting framework.

Other benefits of IR are having better internal decisions, having better relationships with

stakeholders and a lower reputational damage. Flower (2015) criticizes how stakeholders

interest and human capital are incorporated in the framework. There are still unanswered

questions how the targeted audience of the framework is incorporated.

Conclusions

The motivation to research this subject was mainly driven by the demand to bring insight in

how the stakeholders are incorporated in the IR framework. The main objective of the research

is to determine the effect of the Integrated Reporting framework on the information asymmetry.

The research question is as follows: “how is Integrated Reporting interrelated with information

asymmetry?”. Stoll (2000) mentioned that the bid-ask price functions as a proxy of information

asymmetry. Prior researches (Nichols & Wahlen, 2004) showed that abnormal stock-returns

good proxy for information asymmetry. Due to the similarities of CSR and IR of how financial,

environmental, social and governance information are incorporated in the financial reports, I

operationalized the independent variable IR via the proxy ESG_SCORE. Based on the two

proxies bid-ask price and abnormal stock-returns is expected that Integrated Reporting has

negative relationship with information asymmetry.

The dataset consists of 3,155 observations retrieved from the ASSET4 database of

ESG-scores from 503 US listed companies with the biggest market capitalization over a time

span of 7 years. The dataset contains firms such as Apple, Alphabet/Google and Amazon.

The results for the stock liquidity show a significant association of companies that

Integrated Reporting negatively predicts the bid-ask spread. Lower level of bid-ask spread



equals higher level of stock liquidity, which displays a lower information asymmetry for the

investors. There are numerous factors selected that could determine and have an effect on the

information asymmetry, still Integrated Reporting kept its significant negative sign. Altogether

the result found that IR has a negative relations with information asymmetry, is in harmony

with expected results based on the research Lee and Yeo (2016).

The results shows that the abnormal normal returns are positively predicted by

Integrated Reporting, however this relation is not significant. This indicates that users of the

Integrated Reporting framework have higher abnormal normal returns. Hence, this leads to an

growth of the information asymmetry for the investors. The found results are inconsistent with

the Integrated Reporting framework results into lower abnormal returns based on the research

of Nichols and Wahlen (2004).

A question that is still unanswered is, which model is the most reliable? The Adjusted

R-square of the stock liquidity and abnormal normal model are respectively 0.0325 and 0.0186.

Both models have an Adjusted R-square that are seen as very low, that doesn’t explain much

of the variance. Altogether is hard to pick which model is more reliable than the other, by a

research opinion both models would be seen as not reliable.

Finally, the results found during this master thesis suggests that the research outputs

meets the expectations that the Integrated Reporting framework is related in a negative manner

with information asymmetry. The contribution of this research enlarges the accounting and

reporting knowledge. Integrated thinking is key in order to protect the transparency of the

information flow and the business (IIRC, 2017). This corresponds to the findings found during

the research. Integrating integrated thinking in the business can be the motive that the worries

about the operations of the firm are taken away. This master thesis research can be used as a

baseline for future researches over the association of Integrated Reporting with information

asymmetry. The relationship could be examine more deeply. Although there is evidence found

that Integrated Reporting reduces information asymmetry, however it stays hard to say that it

is exactly the case due the reliability issues.

Limitations

During the execution of this research couple limitations appeared and for purposes as further

research it is convenient to keep the limitations in mind. The first limitation is about the initial

sample, which was to examine the European companies with integrated reports. In this research

I have only looked at the North-American companies.



Subsequently, the final sample of 503 Northern-American companies is relatively small

to generalize to a population level, in comparison to the total population of approximately

55,000 northern-American listed firms. Again, like the first limitation a broader scope could

improve the reliability of the study.

The third limitation is a very common limitation of an archival study. The chosen

variables are influencing the end results of this study. The limitation is about unsystematically

picking the variables, which indicates that the research could be subjected to biases. Integrated

Reporting could be associated with excluded variables.

The last limitation is about the determination of the desired height of the quality of the

Integrated Reporting framework, which was omitted from the scope of the study.

Further research

For further research, I suggest to research a more global setting, by also considering the

European companies and their relationship with the different variables. The dataset must then

be large enough to ensure more reliability and to have no conflict with the corresponding

assumptions related to the applicable regressions.



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Appendices

Appendix 1: OLS Assumptions

OLS Assumption 1: The linear regression model is “linear in parameters.”

OLS Assumption 2: There is a random sampling of observations.

OLS Assumption 3: The conditional mean should be zero.

OLS Assumption 4: There is no multi-collinearity (or perfect collinearity).

OLS Assumption 5: Spherical errors: There is homoscedasticity and no autocorrelation.

OLS Assumption 6: Error terms should be normally distributed.



Appendix 2: Libby boxes

Figure 2 Research Framework



Appendix 3: Test for normality

Table 9 Skewness/Kurtosis tests for Normality

Notes: This table shows for the variables the results of the skewness/kurtosis test including the Prob>chi2.

Table 10 Shapiro-Wilk W test for Normality

Notes: This table shows for the variables the results of the Shapiro-Wilk test including the Prob>z.

Table 11 Descriptive Statistics of sample after winsorizing

Notes: This table shows for the variables the descriptive statistics after winsorization total observations (N), mean, standard deviations, min,

max and median over the sample period 2010-2016.



Table 12 Histograms & Box plots SPREAD of the transformation due to winsorizing

Histogram

Box plot

Notes: Table 12 presents the change of the distrubution in the histograms and box plots toward a more “so called” normal distrubution of the

varible SPEAD.

05

10

SP

RE

AD

0.1

.2.3

.4S

PR

EA

D



Table 13 Histograms & Box plots ABNORMAL_RETURN of the transformation due to

winsorizing

Histogram

Box plot

Notes: Table 13 presents the change of the distrubution in the histograms and box plots toward a more “so called” normal distrubution of the

varible ABNORMAL_RETURN.

02

46

De

nsity

-.5 0 .5 1 1.5 2ABNORMAL_RETURN

02

46

8D

en

sity

-.2 -.1 0 .1 .2ABNORMAL_RETURN

-.5

0.5

11

.52

AB

NO

RM

AL

_R

ET

UR

N

-.2

-.1

0.1

.2A

BN

OR

MA

L_

RE

TU

RN



Appendix 4: Regression

Table 14 Breusch-Pagan test for the SPREAD model

Notes: Table 14 tests the heteroscedasticity of the variable SPREAD. The test used is the Breusch-Pagan test, which displays

the p-value for the variable. Heteroscedasticity shows that the standard errors are influenced by biases.

Table 15 Breusch-Pagan test for the ABNORMAL_RETURN model

Notes: Table 15 tests the heteroscedasticity of the variable ABNORMAL_RETURN. The test used is the Breusch-Pagan test,

which displays the p-value for the variable. Heteroscedasticity shows that the standard errors are influenced by biases.

Table 16 Variance Inflation Factor (VIF)

Notes: A Variance Inflation Factor of smaller than 10 indicates that there is no multicollinearity in the sample that is used for

the regression.

Documents

Interrelation of Integrated Reporting with information