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Integrated reporting and information asymmetry

Name: Ömer Erhotamis Student number: 11371773

Thesis supervisor: dr. G. Georgakopoulos Date: 24-06-2018

Word count: 12082, 0

MSc Accountancy & Control, specialization Accountancy Faculty of Economics and Business, University of Amsterdam

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Statement of Originality

This document is written by student Ömer Erhotamis 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.

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Abstract

By using a sample of 44 companies listed on the NYSE in the period between 2011-2015, this study aims to examine the relation between the voluntary adoption of integrated reporting and information asymmetry. The analysis is performed estimating a simple OLS regression of the information asymmetry proxy on integrated reporting and control variables. The dependent variable is the bid-ask spread and the independent variable is integrated reporting. The regression results indicates that the coefficient of integrated reporting is not significant. Therefore, I do not find sufficient evidence that the information asymmetry is lower for firms that voluntarily use integrated reporting. The sample size of this study is considered a

limitations. The data available during the sample period on voluntary users of integrated reporting in the North American region is limited.

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Acknowledgment

I would first like to thank my thesis supervisor dr. G. Georgakopoulos of the University of Amsterdam. He gave me the right direction and motivation when I needed it and helped me to finish my thesis.

I would also like to thank the my coach D. Akkurt. Who gave me motivation and helped me in monitoring my progress during my internship at PwC Amsterdam. Therefore I would like to thank him for his passionate involvement in my personal development.

Finally, I must express my very profound gratitude to my parents for providing me with their endless support and continuous encouragement throughout my years of study. It would not be possible to finish my master without them.

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Contents

Abstract ... 3 Acknowledgment... 4 1 Introduction ... 6 2 Literature review ... 9 2.1 Integrated reporting ... 9 2.2 Agency theory ... 10 2.3 Adverse selection ... 11 2.4 Empirical ... 12 2.5 Hypothesis development ... 15 3 Research methodology ... 19

3.1 Measuring information asymmetry ... 19

3.2 Sample selection ... 20

4 Empirical findings ... 22

4.1 Descriptive statistics ... 22

4.2 Correlation ... 23

4.3 Testing regression assumptions ... 24

4.5 Regression results ... 25

5 Conclusion ... 28

References ... 30

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1

Introduction

After the banking crisis in 2007 the western modern capitalism has started to been questioned on its dependence on short-term rather than long-term financial factors. It is the responsibility of companies to manage capital of investors, and society, to create and preserve value over the short, medium and long-term. The capital system demands a change towards more financial stability and sustainability. According to Humphrey, O'Dwyer and Unerman (2017) different groups seek to change the organizational field of corporate reporting. In this process the International Integrated Reporting Council (IIRC) introduced the "enlightened" long-term investor. In 2011 the IIRC released the Discussion Paper explaining the rationale behind the move towards integrated reporting. The IIRC (2011) claims that integrated reporting will meet the needs of the 21st century, because integrated reporting aims to improve the quality of information available to providers of financial capital to enable a more efficient and

productive allocation of capital. Integrated reporting makes this possible by communicating on financial and non-financial aspects that materially affect the ability of an organization to create value over the short, medium and long-term (IIRC, 2013). But does an integrated report really matters to the capital markets?

Theoretically, the effect of integrated reporting on information asymmetry is still unclear. According to the agency theory delegating some decision rights will lead to information asymmetry problems between managers and investors (Jensen & Meckling, 1976). As soon as savers have invested in a company, the self-interested manager has an incentive to make decisions that expropriate savers' funds. The information asymmetry and conflicting incentives between managers and investors can lead to a breakdown in the functioning of the capital markets (Akerlof, 1970; Healy & Palepu, 2001). Adverse selection is a type of information asymmetry whereby one or more parties to a business transaction have an information advantage over other parties. Increased levels of disclosure can be used as a mechanism to control adverse selection by timely and credible conversion of inside information into outside information (Leuz & Verrecchia, 2000; Scott, 2014).

According to the papers of Lee and Yeo (2016) and García-Sánchez and Noguera-Gámez (2017) they support the notion that integrated reporting improves the information environment of firms by facilitating integration of information in their reporting. They show that companies that use integrated reporting reduce information asymmetry by mitigating agency problems. Also Zhou, Simnett and Green (2017) show that information contained in an integrated report is incrementally useful to analysts and investors in addition to current

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7 reporting practices. Mainly those components in an integrated report that contain new

information are perceived as useful for investors. They found evidence that integrated

reporting is associated with lower cost of equity capital and realized market returns. Investors are willing to accept a lower rate of return as a result of reduced information risk.

However, the paper of Cheng, Green, Conradie, Konishi, and Romi (2014) addresses three key issues of integrated reporting that needs to be solved. The first issue is the narrow scope of integrated reporting that focuses first on providers of financial capital and neglecting other stakeholders. According to Flower (2015) this approach to reporting that has been adopted by the IIRC is inconsistent with full reporting by the firm on the impact of its activities on stakeholders, on society and on the environment. The sustainability concept is also very much removed of the objectives of integrated reporting (Flower, 2015). The second issue is the subjective concept of stock and flow of capitals. It is difficult to measure the different capitals in a consistent and comparable way which also makes it hard to explain the trade-offs between them. The third issue is the assurance of integrated reports. The provided assurance is limited and currently not even possible to provide reasonable assurance on the on the accountability principles (Cheng et al., 2014). According to Eccles, Krzus and Watson (2012) to produce an integrated assurance opinion a global set of credible standards for measuring and reporting non-financial information needs to be developed and have governmental support. Besides that methodologies need to be developed for providing positive assurance on non-financial information. These standards and methodologies have to be integrated to provide financial and non-financial assurance. In sum, there is still much to be explored with regards to integrated reporting. Therefore, I would like to examine whether there is a relation between integrated reporting and information asymmetry. More specifically, this thesis will research if there is a relation with using integrated reporting as a corporate reporting tool and the effects on the bid-ask spread. The research question is formulated as follows:

RQ: Does the voluntary adoption of integrated reporting have an effect on information asymmetry?

To examine this empirical issue, I used a sample of 44 companies listed on the New York Stock Exchange (NYSE) in the period between 2011-2015. The data is comprised of companies that use integrated reporting on a voluntary bases. The sample is divided in a group of 21 companies that use integrated reporting and a control group of 23 companies that

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8 do not use integrated reporting. The bid-ask spread is used as a proxy for information

asymmetry. The integrated reporting is analyzed by creating a dummy variable. Based on prior literature I also added five control variables (Leuz & Verrecchia, 2000; Roulstone, 2003; Mohd, 2005; Fu, Kraft, & Zhang, 2012).

The empirical results can be summarized as follows. In a simple Ordinary Least Square (OLS) regression of information asymmetry on integrated reporting and the control variables, the coefficient on integrated reporting is not significant. Additionally, I performed a robust regression. The results are similar as compared to the OLS regression and therefore also not significant. Conclusively, I do not find sufficient evidence that the information asymmetry is lower for firms that voluntarily use integrated reporting.

This sample size of this study is considered a limitations. The data available to test the hypothesis within the scope of voluntary users of integrated reporting in the North American region was limited. Mainly because integrated reporting started to get widely used after 2011.

The contribution to the literature is as follows. The literature on integrated reporting is a relatively new topic and still in development. The research methods most often used in research on integrated reporting are qualitative research methods. This study on integrated reporting distinguishes itself by using quantitative research methods. By choosing integrated reporting as a topic I would like to contribute to the call of Cheng et al. (2014) for further research relating to the development and implementation of integrated reporting. I also would contribute to the call of García-Sánchez and Noguera-Gámez (2017) for further research on integrated reporting within the context of a single country.

The rest of the paper is organized as follows. Section 2 reviews prior literature and develops the main hypothesis. Section 3 discusses the measurement of information

asymmetry. Also the sample selection and the distribution per industry is given. Section 4 gives the descriptive statistics and the empirical findings. Section 5 provides the conclusion and explains the limitations.

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2

Literature review

This paragraph discusses integrated reporting and the relevant theories related to information asymmetry. Further, it provides an overview of the empirical findings of several papers related to the integrated reporting literature. After that the hypothesis development is explained. This paragraph ends with a summary table of the literature used in the literature review.

2.1 Integrated reporting

According to Churet, Sam and Eccles (2014) integrated reporting in its simplest form is the convergence of the sustainability report and the financial report into a single "narrative". It is a communication system intended for investors in which top management provides its views on how sustainability issues and initiatives are expected to contribute to the long-term growth strategy of the business. An integrated report shows the holistic picture of a company about future targets as well as links between financial performances and non-financial performances (Jensen & Berg, 2012). According to the International < IR > framework an integrated report is a concise communication about how an organization's strategy, governance, performance and prospects, in the context of its external environment, lead to the creation of value over the short, medium and long-term (IIRC, 2013).

But there is more to integrated reporting than what is observed on the surface. Churet et al. (2014) address the relevance of "integrated thinking" and "integrated decision-making" as an important aspect of the integrated reporting process. The IIRC (2013) describes

integrated reporting as a process founded on integrated thinking that results in an organizations periodic integrated report about value creation over time and related communications regarding aspects of value creation. Integrated thinking is the active consideration by an organization of the relationships between its various operating and functional units and the capitals that the organization uses or affects.

The research of Steyn (2014) focuses on the perspectives of senior executives that use integrated reporting. The integrated reporting principles mandate the collection and reporting of both financial and non-financial information. As a result this enhances the managements decision making process. The use of integrated reporting advances the strategic decision making that aims a long-term sustainable wealth creation.

The IIRC (2013) defines six capitals as a guideline for ensuring organizations to consider all forms of capital they use or affect. Based on the business model and how

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10 companies use these capitals, they will be able to explains how they create value over time for the stakeholders. These are financial, manufactured, intellectual, human, social and

relationship, and natural capitals. According to Morros (2016) integrated reporting brings governance, financial capital, intellectual capital, social capital, and environmental capital to a common platform.

The IIRC's long-term vision is a world in which integrated thinking is embedded within mainstream business practice in the public and private sectors, facilitated by integrated reporting as the corporate reporting norm. The aim is to improve the quality of information available to providers of financial capital to enable a more efficient and productive allocation of capital. Also promote a more cohesive and efficient approach to corporate reporting that draws on different reporting strands and communicates the full range of factors that materially affect the ability of an organization to create value over time. Finally support integrated thinking, decision-making and actions that focus on the creation of value over the short, medium and long-term (IIRC, 2013).

2.2 Agency theory

In the paper of Jensen and Meckling (1976) the agency relationship is explained as a contract under which one or more principals engage another person (agent) to perform some service on their behalf which involves delegating some decision making authority to the agent. This relationship defined as agency theory is about shareholders and managers. This agency relationship leads to information asymmetry problems, because managers are insiders they have access to more or better private information than shareholders. It is generally impossible for the principal or the agent to ensure that at zero cost the agent will make optimal decisions from the principal's viewpoint. Due to these costs there will be information asymmetry between the principal and the agent (Jensen & Meckling, 1976).

According to Healy and Palepu (2001) the agency problem arises because people that invest in a firm typically do not intend to play an active role in its management and that the responsibility is delegated to the manager. As soon as savers have invested their funds in a firm, the self-interested manager has an incentive to make decisions that expropriate savers' funds. The information differences and conflicting incentives between managers and investors can lead to a breakdown in the functioning of the capital markets. This information problem is also referred to as the "lemons" problem (Akerlof, 1970). For example, consider a situation where half the business ideas are "good" and the other half are "bad". Both investors and entrepreneurs are rational and value investments conditional on their own information. If

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11 investors cannot distinguish between the two types of business ideas, entrepreneurs with "bad" ideas will try to claim that their ideas are as valuable as the "good" ideas. Realizing this possibility, investors will value both good and bad ideas at an average level. Therefore, if the lemons problem is not fully resolved, the capital market will rationally undervalue some good ideas and overvalue some bad ideas relative to the information available to entrepreneurs (Healy & Palepu, 2001).

The IIRC has recognized the information problem that exist with traditional corporate reporting. They state that integrated reporting has been developed to enhance accountability, stewardship and trust as well as to harness the information flow and transparency (IIRC, 2017). With regards to this aspect investors would be able to better distinguish between the "good" and "bad" investment. The use of integrated reporting could eventually reduce the information problem.

2.3 Adverse selection

According to Scott (2014) adverse selection is a type of information asymmetry whereby one or more parties to a business transaction have an information advantage over other parties. This occurs because some insiders will know more about the current condition and future prospects of the firm than outside investors. This can lead to managers behaving unethically by biasing or otherwise managing the information released to investors. They may release information early to selected investors or analysts, enabling insiders to benefit at the expense of ordinary investors. This typically leads to information asymmetry between the investors and managers.

According to Leuz and Verrecchia (2000) information asymmetry create costs by introducing adverse selection into transactions between buyers and sellers of firm shares. In real institutional settings adverse selection typically manifests in reduced levels of liquidity for firm shares. A commitment to increased levels of disclosure reduces the possibility of information asymmetries arising either between the firm and its shareholders or among potential buyers and sellers of firm shares. Scott (2014) sees financial accounting and reporting as a mechanism to control adverse selection by timely and credible conversion of inside information into outside information.

Integrated reporting improves the quality of information available to providers of financial capital to enable a more efficient and productive allocation of capital. The IIRC promotes a more cohesive and efficient approach to corporate reporting that draws on different reporting strands and communicates the full range of factors that materially affect

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12 the ability of an organization to create value over time (IIRC, 2013). Therefore it is important to research whether this will have an effect on the asymmetric information and the adverse selection problem

2.4 Empirical

Firms provide disclosure through regulated financial reports. Some firms engage in additional voluntary communication. This section provides insights in the academic papers available that are related to the adoption of integrated reporting.

According to Humphrey et al. (2017) different professions and professionals seek to change the organizational field of corporate reporting by promoting and shaping integrated reporting. In this process the IIRC created a demand for integrated reporting by introducing the "enlightened" long-term investor. Also Serafeim (2015) found evidence that firms practicing integrated reporting have an investor clientele that is more dedicated and less transient. This results in a more long-term oriented investors.

According to Owen (2013) it is likely that the accounting process will even need more of a strategic instead of an operational or transactional focus. They will need to adopt a more long-term rather than short-term view and present more prospective rather than retrospective analysis. Also including more qualitative comments as well as quantitative information. Also report on wider business performance indicators rather than on narrower external financial reporting data or audit compliance. The quality of financial reporting can only be improved by initiatives like the IFAC, the IIRC and the < IR > framework (Owen, 2013).

On the other hand Zhou et al. (2017) found evidence that an integrated report matters to capital markets. The results from this study suggests that information contained in an integrated report is incrementally useful to analysts and investors in addition to current

reporting practices. Additional analyses indicate that it is mainly those components containing new information in an integrated report that are driving these results. Further, they found that the improvement in the level of alignment of integrated reports with the < IR > framework is associated with a subsequent reduction in the cost of equity capital and the realized market returns. This is consistent with the notion that investors are willing to accept a lower rate of return as a result of reduced information risk (Zhou et al., 2017).

The IIRC (2013) claims that integrated reporting is intended to create a transparent information environment in which investors can process firm-specific financial information more easily than before. The paper of Lee and Yeo (2016) provides empirical evidence that support the notion that integrated reporting improves the information environment of the firm

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13 by facilitating the flow and integration of information of these firms. For their research they use a sample of listed firms in South Africa. The findings suggests that better disclosure arising from integrated reporting reduces agency costs and information asymmetry between managers and suppliers of external financial capital. Also the research of García-Sánchez and Noguera-Gámez (2017) focuses on integrated reporting and stakeholder engagements. They found evidence of a reduction of information asymmetry for companies that provide an integrated report and indicate that it can be used to mitigate agency problems.

The paper of Cheng et al. (2014) discusses a range of potential research issues relating to the development and implementation of integrated reporting. According to them three key issues needs to be solved to enhance the acceptability of integrated reporting worldwide.

The first issue is the focus of integrated reporting on providers of financial capital. The < IR > framework identifies "providers of financial capital" as the primary users of an

integrated report. The IIRC also states in the < IR > framework: "An integrated report benefits all stakeholders interested in an organization's ability to create value over time, including employees, customers, suppliers, business partners, local communities, legislators, regulators and policy-makers" (IIRC, 2013, p.7). This issue has also been addressed by Flower (2015) by saying that there is a neglect of other stakeholders. The IIRC recognizes the existence of stakeholders other than investors and try to give the impression that it takes into account their needs. But it is clear that the IIRC considers reporting to stakeholders is on the second place after reporting to investors. Also its interest in stakeholders other than investors is only to assure the future prosperity of the firm. This approach to financial reporting that has been adopted by the IIRC is inconsistent with full reporting by the firm on the impact of its activities on stakeholders, on society and on the environment (Flower, 2015).

According to Flower (2015) the sustainability concept is also very much removed of the objectives of integrated reporting. This is an interesting development since the

fundamental principle of the bodies that founded the IIRC (the GRI and A4S) was to improve the reporting of sustainability. The reporting on the increases and decreases of the values of the different categories of capital could be a valid method of reporting on sustainability. The integrated report should cover sustainability without using the term itself. This is only possible when three conditions are met (Flower, 2015):

First the term "value" should be interpreted much wider. The crucial point is the meaning given to the word "value". An alternative interpretation is the "value to society" which is consistent with social and environmental accounting. Also "value to stakeholders" which is consistent with the stakeholder theory. Another one is "value to present and future

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14 generations" which is the interpretation that is consistent with sustainability concept. The words "providers of financial capital" used in the framework (IIRC, 2013) suggest that the IIRC's focus is "value to investors". The framework recognizes alternative concepts of value. But the framework (IIRC, 2013) states that the primary purpose of an integrated report is to explain to the providers of financial capital how an organization creates value over time. According to Flower (2015) the creation of value by the firm is the framework's central theme, because it is mentioned over fifty times in the framework.

Second, the firm should report comprehensively on all the categories of the six capitals. The firm should report on capitals that it does not control if they have a significant effect on the firm's ability to create value to investors. This would mean that it is in order for a firm not to report on the impact of its activities on natural capital, where this has no

significant impact on its own long-term profitability, for example when polluting the environment. In general the firm needs to report on capitals that are inputs to its production process, because the firm's profitability will mostly be affected by these capitals. But it will often be the case that a firm's activities have a negative impact on other capitals but have no significant impact on the firm's long-term profitability. According to the framework there is no requirement to report this negative impact. If the IIRC had adopted a wider concept of value, such as "value to society" then it would have been necessary for the firm to report on its impact of its activities on all capitals, no matter the impact on its own profitability (Flower, 2015)

Third, all six capitals valued appropriately should show no decrease resulting from the firm's activities. But if one or more capitals shows a decrease, then overall sustainability is only achieved, if this decrease in value can be compensated by the increase in the value of other capitals. The IIRC calls this the trade-off principle. The framework states that "an integrated report . . . may also include a discussion of the nature and magnitude of the

significant trade-offs that influence the selection of inputs" (IIRC, 2013, p.26). All trade-offs should be considered as a problem, because it makes it difficult to measure the different capitals in a consistent and comparable way. But trade-offs involving natural capital are surely highly unlikely to be in the interests of society as a whole. Especially for a sustainable future generations. They would expect that the present generation should not leave the planet in a worse state than it had received it (Flower, 2015).

If we return to the second key issue of Cheng et al. (2014), we see that there is a certain overlap with the trade-offs issue as pointed out by Flower (2015). Therefore the second key issue according to Cheng et al. (2014) is the meaning of "Overall Stock of

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15 Capital" and tradeoffs between capitals. The concepts of the stock and flow of capitals are very subjective and it will be difficult for organizations to explain some of their capitals. For example, how does an organization assess its stock of shared norms, and common values and behaviors (IIRC, 2013) or how can organizations meaningfully explain and evaluate the tradeoffs between capitals.

The last key issue discussed by Cheng et al. (2014) is the assurance of integrated reports. The majority of integrated reports are being produced in South Africa. The assurance of integrated reports is limited to selected sustainability indicators, GRI application level checks and sometimes the three accountability principles. Currently assurance providers have not yet been able to provide reasonable assurance on the accountability principles. Some major challenges stand in the way of reaching mature assurance practices in integrated reporting.

According to Eccles et al. (2012) there are three major challenges to producing an integrated assurance opinion. The first issue is developing a global set of credible standards for measuring and reporting non-financial information which have the appropriate

governmental support. Second issue is the development of methodologies for providing positive assurance on non-financial information. The third issue is integrating standards and assurance methodologies for financial and non-financial information in a way that provides a "true and fair view of an organization's sustainability". In order to address these issues active engagement of the accounting profession, including those in auditing firms, corporations and academia is required. The long-term relevance of the accounting profession is at risk if they fail to help address these challenges. This also puts the development of a sustainable society at risk (Eccles et al. 2012).

2.5 Hypothesis development

Consistent with the different views presented in the empirical part, there is still mixed evidence about the claimed benefits of integrated reporting. The relationship between the voluntary use of integrated reporting and information asymmetry is still a gap in the literature that needs to be explored.

In primary capital markets, equity shares of a firm are sold to investors to raise cash for investment. A disclosure related cost that makes the firm's equity sales more costly is the transaction cost that arises from the adverse selection problem, due to the different degree of information. This also called the "information asymmetry component of the cost of capital" (Verrecchia, 2001). Using voluntary disclosure firms can affect the information asymmetry.

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16 To measure the information asymmetry I will use the bid-ask spread as a proxy for

information asymmetry. The bid-ask spread is commonly used in research to measure information asymmetry (Leuz & Verrecchia, 2000; Roulstone, 2003; Mohd, 2005; Silber, 2005; Daske, Hail, Leuz & Verdi, 2008; Fu et al., 2012). The reason for this is that the bid-ask spread addresses the adverse selection problem that arises from transacting in firm shares in the presence of asymmetrically informed investors. Less information asymmetry implies less adverse selection. This in turn would mean a smaller bid-ask spread (Leuz & Verrecchia, 2000). If the investor is willing to pay an amount that is less than what the owner is asking to sell it for, it must be because the seller and the potential buyer have different level of

information, which leads to information asymmetry. If the information asymmetry is severe there will be a wider spread to cover the losses from trading with informed investors (Fu et al., 2012). Therefore the following hypothesis is constructed:

H1: Firms that use integrated reporting have a negative effect on the bid-ask spread.

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. . . Table 1 Summary table of the literature . . . .

Author(s) Year Title Topic

Research

type Key variables

1 Akerlof, G. 1970 The market for lemons Quality and uncertainty in markets Qualitative NA

2 Cheng, M., Green, W., Conradie, P., Konishi, N. & Romi, A.

2014 The International Integrated Reporting Framework: Key Issues and Future Research Opportunities . . . . . . . . . . . .

Issues and future research on integrated reporting

. . . . . . .. . . . . . . . . . . . . . . . . . Qualitative NA 3 Churet, C., Sam, R. & Eccles, R.G.

2014 Integrated Reporting, Quality of Management and Financial Performance

The association between of integrated reporting,

quality of management and financial performance Qualitative NA

4 Eccles, R. G., Krzus, M. P., & Watson, L. A

2012 Integrated reporting requires integrated assurance . . . . . .

The challenges faced in providing an integrated assurance opinion.. . .

. . . Qualitative NA

5 Flower, J. 2015 The international integrated reporting

council: a story of failure

The history of an initiative that promised to change

the practice of financial reporting and how it failed. Qualitative NA

6 Fu, R., Kraft, A. & Zhang, H.

2012 Financial reporting frequency, information asymmetry, and the cost of equity

The impact of financial reporting frequency on

information asymmetry and the cost of equity Quantitative log(turnover) and Frequency, size,

log(volatility 7 García-Sánchez,

I. & Noguera-Gámez, L.

2017 Integrated Reporting and Stakeholder Engagement: The Effect on Information Asymmetry, Corporate Social Responsibility and Environmental Management

The possible relationship between integrated information disclosure and the degree of

information asymmetry Quantitative

IR, frequency, size, sustainable report utility,

profitability, leverage, industry and growth 8 Healy, P.M. &

Palepu, K. G.

2001 Information asymmetry, corporate

disclosure, and the capital markets: A review of the empirical disclosure literature

Disclosure regulation, information intermediaries, and the determinants and

economic consequences of corporate disclosure. Qualitative NA

9 Humphrey, C., O'Dwyer, B. & Unerman, J.

2017 Re-theorizing the configuration of organizational fields: the IIRC and the pursuit of ‘Enlightened’ corporate reporting

This paper studies the emergence of the IIRC and how it attempts to institutionalize the integrated reporting as a practice that is critical to the relevance and value of corporate reporting.

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10 Jensen, J. C., & Berg, N.

2012 Determinants of traditional sustainability reporting versus integrated reporting. An institutionalist approach

Analyze similarities and differences between companies with traditional sustainability reporting and those that publish integrated reports.

Quantitative IR, TSR (difference

analysis) 11 Jensen, M. C., &

Meckling, W. H.

1976 Theory of the firm: Managerial behavior, agency costs and ownership

structure. Journal of financial economics

Using the agency theory, the property rights theory and the finance theory to develop a theory on the

ownership structure of firms Quantitative NA

12 Lee, K. W., & Yeo, G. H. H.

2016 The association between integrated reporting and firm valuation

The association between integrated reporting and

firm valuation Quantitative TOBINQ, IRSCORE

13 Leuz, C., & Verrecchia, R. E.

2000 The Economic Consequences of Increased Disclosure.

The effect of greater disclosure on cost of capital

Quantitative Bid-ask spread, trading

volume, volatility

14 Mohd, E. 2005 Accounting for software development costs

and information asymmetry

The impact of immediate expensing of research and

development on information asymmetry Quantitative

Bid-ask spread, share turnover

15 Morros, J. 2016 The integrated reporting: A presentation of

the current state of art and aspects of integrated reporting that need further development

The emerging field of integrated reporting, with emphasis on the International Integrated Reporting

Council Qualitative NA

16 Owen, G. 2013 Integrated reporting: A review of

developments and their implications for the accounting curriculum

Reviewing the developments and implications of

integrated reporting on the accounting profession Qualitative NA

17 Roulstone, D.T. 2003 Analyst Following and Market Liquidity Analyst Following and Market Liquidity Quantitative Bid-ask spread

18 Scott, W. R. 2014 Financial accounting theory Accounting and reporting Qualitative NA

19 Serafeim, G. 2015 Integrated reporting and investor clientele. The relation between integrated reporting and the

composition of a firm's investors Qualitative NA

20 Silber, W. L. 2005 What happened to liquidity when world war

I shut the NYSE?

How financial markets respond on extreme events

Quantitative Bid-ask spread

21 Steyn, M. 2014 Senior executives' perspectives of integrated

reporting regulatory regimes as a mechanism for advancing sustainability in South African listed companies.

Senior executives' perspectives on integrated reporting

Qualitative NA

22 Verrecchia, R.E 2001 Essays on disclosure Essay on disclosure literature Qualitative NA

23 Zhou, S., Simnett, R., & Green, W.

2017 Does integrated reporting matter to the capital market?

Providing empirical evidence on the claimed benefits of integrated reporting in a capital market

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3

Research methodology

This section discusses how to measure information asymmetry by describing the bid-ask spread model. After that the sample selection process is explained and an overview of the sample distribution per industry is provided.

3.1 Measuring information asymmetry

Based on Fu et al. (2012) I use the bid-ask spread as a proxy for information asymmetry. The bid- ask spread is a commonly used measure of information asymmetry. The more severe the information asymmetry, the wider the spread necessary to cover higher expected market-maker losses from trading with informed traders. The study of Fu et al. (2012) measures the impact of reporting frequency on the information asymmetry and the cost of capital. Their findings suggest that higher reporting frequency reduces information asymmetry and the cost of equity. I follow Mohd (2005) and Silber (2005) by calculating the daily bid-ask spread as (ask-bid)/((ask+bid)/2). The research of Mohd (2005) examines the effect of accounting for software development costs on information asymmetry. If the information asymmetry

between management and investors is high, some traders can use their private information to gain at the expense of uninformed traders. Stock dealers realize this information advantage and increase the bid-ask spread to protect themselves from informed traders (Mohd, 2005). Also Leuz and Verrecchia (2000) use the bid-ask spread as a proxy for information

asymmetry. They focus on the economic consequences of increased disclosure. They found that disclosure strategies are associated with lower bid-ask spreads.

Based on prior literature, the proxy for information asymmetry used in this study is the bid-ask spread. I estimate a simple OLS regression of the information asymmetry proxy on integrated reporting and control variables. The analysis is performed using the following bid-ask spread model:

SPREAD: α + β1*IR + β2*ROA + β3*LEVERAGE + β4*FIRM_SIZE + β5*LOG_TURNOVER + β6*LOG_VOLATILITY + ԑ

In accordance with Leuz and Verrecchia (2000), Roulstone (2003), Mohd (2005), Daske et al. (2008) and Fu et al. (2012) I use several control variables. The model has five control

variables: LEVERAGE, ROA, FIRM_SIZE, LOG_TURNOVER and LOG_VOLATILITY. These variables are commonly used when an information asymmetry measure is a dependent

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20 variable. The following overview provides a detailed description of these variables and the search codes used to retrieve the data.

. . . . Table 2 Overview of variables . . .

Variable Definition Database search codes

SPREAD The bid-ask spread is the absolute difference between

the bid and ask price at the end of each trading day divided by the average of the bid and ask price at the end of each trading day (ask-bid)/((ask+bid)/2) (Fu et al., 2012; Leuz & Verrecchia, 2000).

CRSP:

Closing Ask and Closing Bid

IR Dummy variable whereby 1 for firms using integrated

reporting and 0 firms that do not use integrated reporting. . . .

. . .

LEVERAGE Leverage is calculated as total liabilities divided by the

sum of total liabilities and market value of equity (Fu et al. 2012). . .

Compustat:

Long-term debt (DLTT) Debt in current liabilities (DLC)

Stockholders' equity (SEQ)

ROA The average return on assets. Is computed by dividing

operating income by total assets (Leuz & Verrecchia, 2000). . .

Compustat: Net income (NI) Total assets (AT)

FIRM_SIZE The log of the average market value of equity at the

beginning and end of the prior calendar year (Fu et al. 2012).

Compustat: Total Assets (AT)

LOG_TURNOVER The log of the median daily turnover ratio in a year (Fu

et al. 2012).The turnover ratio is calculated by dividing the trading volume by the outstanding shares.

CRSP:

Volume and Number of shares outstanding

LOG_VOLATILITY The log of the standard deviation of daily return in a

year (Fu et al. 2012).

CRSP:

Holding period return

3.2 Sample selection

The sample of this archival study consists of North American companies listed on the NYSE. I have limited the study to this region, due to the availability of stock data for companies using integrated reporting on a voluntary basis. Using Wharton Research Data Service (WRDS) I accessed two different databases. As shown in table 2 for company stock data I used CRSP stock security files and retrieved company stock data to calculate SPREAD, LOG_TURNOVER and LOG_VOLATILITY. For fundamental company data I used the

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21 Compustat - Capital IQ. The data retrieved from the Compustat North America section is used to calculate LEVERAGE, ROA and FIRM_SIZE. These two databases are linked using the Historical CRSP PERMNO Link to COMPUSTAT Record to merge the data.

Integrated reporting started to gain worldwide attention since 2010. The initial sample had companies between 2010 and 2015. This sample had 50 companies, from which 24 companies used integrated reporting and 26 companies that do not use integrated reporting. Initially there were 229 firm year observations were. Due to lack of company data in the sample period between 2010 and 2015 or not being subsequent years for the whole sample, 9 firm year observations (6 companies) were dropped. Table 3 provides an overview of the final sample distributed per industry using the Standard Industry Classification Code.

. . . . Table 3 Sample distribution per industry . . . .

Range of SIC codes

. . . .

Division Firms Non-IR IR

0100 - 0999 Agriculture, Forestry and Fishing 1 0 1

1000 - 1499 Mining 2 2 0

1500 - 1799 Construction 0 0 0

1800 - 1999 Not used 0 0 0

2000 - 3999 Manufacturing 17 8 9

4000 - 4999 Transportation, Communications, Electric, Gas and Sanitary service 7 3 4

5000 - 5199 Wholesale Trade 1 0 1

5200 - 5999 Retail Trade 2 2 0

6000 - 6799 Finance, Insurance and Real Estate 11 7 4

7000 - 8999 Services 2 1 1

9100 - 9729 Public Administration 0 0 0

9900 - 9999 Non classifiable 1 0 1

Total amount of firms . . . . 44 23 21

Subsequent years 2011 - 2015 . . . . 5 5 5

Total amount of observations . . . . 220 115 105

The final sample is comprised of 44 companies listed on the NYSE with subsequent data from 2011 up to and including 2015. The sample is divided in a group of 21 companies that use integrated reporting (IR) and a control group of 23 companies that do not use integrated reporting (Non-IR). This results in 220 firm year observations. These are 105 observations of IR companies and 115 observations of non-IR companies. The data sample is checked for outliers. Due to a relatively small amount of observations, the winsorizing method is used instead of the data trimming method to avoid dropping more observations. I used a

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22

4

Empirical findings

This section provides insights in the regression results. First, the main descriptive statistics will be discussed. Then the Pearson correlation matrix is provided for the bid-ask spread model. After that the regression assumptions are tested. Finally, the OLS regression and additionally the robust regression results are explained.

4.1 Descriptive statistics

In order to measure the information asymmetry I will use the bid-ask spread as a proxy for information asymmetry. Less information asymmetry implies that there is less adverse selection and this should give a smaller bid-ask spread (Leuz & Verrecchia, 2000). The adverse selection problem occurs from transactions in firm shares with asymmetrically informed traders and investors. They realize this information advantage and increase the bid-ask spread to protect themselves from informed traders and investors (Mohd, 2005).

According to Fu et al. (2012) if the information asymmetry is severe, there will be a wider spread to cover the losses from trading with these informed investors. Therefore I test the hypothesis whether firms that use integrated reporting have a negative effect on the bid-ask spread.

Table 4 gives an overview of the descriptive statistics of this research. The table provides the dependent and independent variables used in the bid-ask spread model. For each variable the amount of observations (N), the mean, the standard deviation (SD), the minimum values (Min) and the maximum values (Max) are given for the group of companies using integrated reporting (IR:1) and for the group of companies that do not use integrated reporting (IR:0). The sample has 220 observations. These are divided in two groups, 115 observations for companies that are non-IR and 105 observations for companies that are IR. The mean of the SPREAD for the non-IR group is 0.000304 and the mean for the IR group is 0.0003594. The mean of the SPREAD is slightly higher for the IR group with a difference of 0.0000554. The mean of ROA is higher for the IR group. These companies are relatively more profitable and therefore have the budget to invest in integrated reporting. The minimum value of LEVERAGE is zero which indicates that there are companies in the sample that have no liabilities on their balance sheet. The IR group has companies that have much higher leverage (15.01948) compared to the non-IR group (9.210522). This could be linked with the higher ROA. These companies attract more capital form investors and therefore have a more sophisticated reporting tool.

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23 The mean of LOG_TURNOVER is lower for the non-IR group. This is consistent with the idea that firms with higher information asymmetry have lower share turnover, because uniformed traders are less likely to trade in these shares (Mohd, 2005). The LOG_VOLATILITY minimum and maximum values are shown as a negative value. This does not indicate that there is a negative stock volatility. The LOG_VOLATILITY is

computed as the logarithm of the volatility of the shares. The negative values indicate that all the values of this variable are between zero and one.

4.2 Correlation

This paragraph explains the correlation of the variables in the bid-ask spread model. Table 5 presents the Pearson correlations between the variables. The correlation values are significant at the 5% level. Table 5 shows that there is a positive correlation between the SPREAD and IR. This implies that when companies use integrated reporting the bid-ask spread becomes wider with 0.0776. However the value is not significant (0.2519) it is not the expected outcome. This is against the notion that increased disclosure would reduce the information asymmetry (Fu et al., 2012).

Furthermore, table 5 also provides a significant correlation with the control variables ROA, FIRM_SIZE, LOG_TURNOVER and LOG_VOLATILITY. The ROA and

FIRM_SIZE has a negative correlation with the SPREAD respectively -0.2411 and -0.2519. This is in line with the notion that larger firms makes more information available (Mohd,

. . . . Table 4 Descriptive statistics . . . .

Variable IR N Mean SD Min Max

SPREAD 0 115 .000304 .0003115 .0001041 .0024729 . . . 1 105 .0003594 .000402 .0001041 .0024729 ROA 0 115 .0583487 .0651929 -.1163026 .2370331 . . . 1 105 .062769 .0765204 -.1034016 .3436324 LEVERAGE 0 115 1.429121 1.884615 0 9.210522 . . . 1 105 1.433903 2.52578 0 15.01948 FIRM_SIZE 0 115 11.65565 1.918148 7.839336 14.67381 . . . 1 105 10.71112 1.660368 8.032182 14.32205 LOG_TURNOVER 0 115 1.768165 .5902633 .8551726 3.055747 . . . 1 105 1.846057 .5455674 .9056107 3.055747 LOG_VOLATILITY 0 115 -4.224634 .4019779 -5.000162 -3.133359 . . . 1 105 -4.244267 .3773088 -5.000162 -3.133359

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24 2005). The LOG_TURNOVER and LOG_VOLATILITY have a positive correlation the SPREAD respectively 0.5073 and 0.5847. These results are not in line with the hypothesis of Leuz and Verrecchia (2000) that firms with higher information asymmetry have lower share turnover and less share price volatility. The difference in these results could be explained by the larger sample size of Leuz and Verrecchia (2000). They had a sample of 102 companies, which is more than double the size of the sample I used in this study.

4.3 Testing regression assumptions

This paragraph tests the assumptions for the regression analysis. First I check whether the variables have outliers. For the variables SPREAD, ROA, LEVERAGE, FIRM_SIZE, LOG_TURNOVER and LOG_VOLATILITY outliers were found in the data. Due to a relatively small amount of observations I use winsorizing instead of trimming the data for outliers. These variables are winsorized at the 1st and 99th percentile of their distributions.

I test for normality of the data by using Shapiro-Wilk W test and the

Skewness/Kurtosis test. Both of these numerical methods gives a p-value that is lower than 0.00 for all the variables. This means that the null hypothesis of a normal distribution must be rejected. Also I use graphical methods such as a histogram and the Kernel density line to visualize the distribution of the data (see appendix 1 Kernel Density Estimation). Based on

. . . . Table 5 Pearson correlation matrix . . . .

. . . 1 2 3 4 5 6 7 SPREAD 1 1.0000 . . . . . . . . . . . . . . . . . . IR 2 0.0776 1.0000 . . . . . . . . . . . . . . . P-value 0.2519 . . . . . . . . . . . . . . . ROA 3 -0.2411 0.0313 1.0000 . . . . . . . . . . . . P-value 0.0003* 0.6443 . . . . . . . . . . . . LEVERAGE 4 -0.0500 0.0011 -0.1648 1.0000 . . . . . . . . . P-value 0.4602 0.9872 0.0144* . . . . . . . . . FIRM_SIZE 5 -0.2519 -0.2546 -0.2603 0.1503 1.0000 . . . . . . P-value 0.0002* 0.0001* 0.0001* 0.0257* . . . . . . LOG_TURNOVER 6 0.5073 0.0685 -0.1125 0.0221 -0.2832 1.0000 . . . P-value 0.0000* 0.3119 0.0959 0.7441 0.0000* . . . LOG_VOLATILITY 7 0.5847 -0.0252 -0.2449 -0.0931 -0.1847 0.7333 1.0000 P-value 0.0000* 0.7098 0.0002* 0.1686 0.0060* 0.0000*

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25 these methods I conclude that the standard errors of the bid-ask spread model does not follow the assumption of a normal distribution. Therefore I use robust standard errors in the OLS regression to correct for normality.

Furthermore, the data is tested for heteroscedasticity. The OLS regression assumes that the errors term is same across all values of the independent variables. This is called the assumption of homoscedasticity. If this assumption is violated then there is heteroscedasticity. To test this I use Cameron & Trivedi's decomposition of IM-test. The test gives a p-value of 0.0000, which indicates that the data is heteroscedastic. The existence of heteroscedasticity is a major concern in doing a regression analysis. To control for this violation I perform

additionally a robust regression.

Finally, I test the data for signs of multicollinearity. I use the Variation Inflation Factor (VIF) to check for multicollinearity. According to O'Brien (2007) this is a measure of the independent variable's collinearity with the other independent variables and is directly

connected to the variance of the regression coefficient that is associated with the independent variable. If the VIF-value exceeds 10, then this is a sign of severe multicollinearity. The mean VIF-value of the regression model is 1.58. This indicates that there is no sign of

multicollinearity that can have a significant impact on the regression results.

4.5 Regression results

In this paragraph the regression results are analyzed. The bid-ask spread model will be used to perform the regression. In order to test the hypothesis the following model is examined:

SPREAD: α + β1*IR + β2*ROA + β3*LEVERAGE + β4*FIRM_SIZE + β5*LOG_TURNOVER + β6*LOG_VOLATILITY + ԑ

The first analysis is an OLS regression of the bid-ask spread. Table 6 provides the OLS regression output. The results are after controlling for heteroscedasticity by using the robust standard errors. The R-squared of the model is 0.3977. This means that 39,77% of the SPREAD is explained by the independent variables. The R-squared indicates a good fit of the variables. The IR has a positive coefficient (0.0000292) and has a p-value of 0.491 which is considered not significant at the 5% level. There is no significant evidence to support the hypothesis. Therefore I cannot support the hypothesis that firms that use integrated reporting have a negative effect on the bid-ask spread.

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26 The results suggest that the p-value of LOG_TURNOVER is positive and significant. The LOG_TURNOVER is expected to have a negative coefficient, indicating that lower information asymmetry is associated with a lower share turnover. This result is in line with the results of Mohd (2005).

The coefficients of ROA and FIRM_SIZE are negative and have significant p-values. This in line with the notion that firm size affects the amount of information available

regarding a firm. If there is more information disclosed, the adverse selection problem is lower and therefore a negative correlation with the bid-ask spread is as expected (Roulstone, 2003).

The LOG_VOLATILITY has a positive coefficient and the p-value is significant at the 1% significance level. According to Roulstone (2003) investors will protect themselves against price swings by increasing the bid-ask spread. It is expected that the information asymmetry is lower and that this would be indicated by a negative correlation of

LOG_VOLATILITY with the bid-ask spread. Also Leuz & Verrecchia (2000) suggest that low levels of volatility can suggest fewer information asymmetries. The results are contrary suggesting that the opposite is true. This could be explained by the relatively small sample size used in this study. According to Leuz & Verrecchia (2000) measuring the effects on volatility is complex and may depend on the type of investors attracted to these firms. This makes volatility less reliable among the other control variables.

. . . . Table 6 OLS regression results . . . .

Variable Coefficient

Standard

Error T-statistic P-value

95% Confidence Interval

IR .0000292 .0000423 0.69 0.491 -.0000541 .0001125

ROA -.0008789 .0002927 -3.00 0.003*** -.0014558 -.000302

LEVERAGE -2.93e-06 4.49e-06 -0.65 0.515 -.0000118 5.92e-06

FIRM_SIZE -.0000327 .0000146 -2.24 0.026** -.0000615 -3.86e-06

LOG_TURNOVER .0000859 .0000453 1.90 0.059* -3.25e-06 .0001751

LOG_VOLATILITY .0003764 .0001023 3.68 0.000*** .0001747 .000578

Constant .0021783 .000608 3.58 0.000*** .0009797 .0033768

All variables are winsorized at 1% and 99%. The * indicates P-value lower than 0.10 and ** indicates P-value lower than 0.05 *** indicates P-value lower than 0.01

The second analysis is a robust regression of the bid-ask spread model. This regression is performed to control for the heteroscedasticity problem that was found in testing the

regression assumptions. Table 7 provides an overview of the robust regression results. The results are different compared to the OLS regression.

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27 The variable IR now has a negative coefficient -0.0000241, which is more aligned with my expectations. The p-value is 0.125 and is lower than the p-value of the OLS regression (0.491). But it is still not significant to support the hypothesis firms that use integrated reporting have a negative effect on the bid-ask spread. In table 7 the ROA has a different p-value (0.204) and therefore not significant anymore. The variables FIRM_SIZE, LOG_TURNOVER and LOG_VOLATILITY are still significant as before. Overall, the robust regression indicates that the results are influenced by heteroscedasticity or other

factors. Given these results it can be said that future research with a larger sample size can get different results.

. . . . Table 7 Robust regression results . . . .

Variable Coefficient

Standard

Error T-statistic P-value

95% Confidence Interval

IR -.0000241 .0000157 -1.54 0.125 -.000055 6.74e-06

ROA -.00015 .0001178 -1.27 0.204 -.0003822 .0000822

LEVERAGE -2.64e-06 3.55e-06 -0.74 0.459 -9.64e-06 4.37e-06

FIRM_SIZE -.0000192 4.62e-06 -4.15 0.000*** -.0000283 -.0000101

LOG_TURNOVER .0000155 .0000203 0.76 0.446 -.0000245 .0000555

LOG_VOLATILITY .0001166 .0000301 3.87 0.000*** .0000572 .0001759

Constant .0009372 .000163 5.75 0.000*** .0006159 .0012585

All variables are winsorized at 1% and 99%. The * indicates P-value lower than 0.10 and ** indicates P-value lower than 0.05 *** indicates P-value lower than 0.01

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28

5

Conclusion

In this thesis I attempted to answer the question whether the voluntary adoption of integrated reporting does have an effect on the information asymmetry? The study focused on a sample of 44 companies listed on the NYSE during the period 2011-2015 that use voluntarily integrated reporting as their corporate reporting tool. These companies are divided in two groups. The first group has 21 IR companies and a control group of 23 non-IR companies. By using five subsequent firm years the sample comprises 220 firm year observations.

Prior literature (Lee & Yeo, 2016; García-Sánchez & Noguera-Gámez, 2017) suggests a negative relationship between integrated reporting and information asymmetry. An

integrated report provides a holistic view on the links between financial and non-financial information of a company in one single narrative report. It is a system intended for investors in which top management communicates how an organization's strategy, governance,

performance and prospects, in the context of its external environment, lead to the creation of value over the short, medium and long-term. Disclosing all the key information about the company in an integrated manner, should enable investors to make better decisions. The increased amount of integrated information should lead to mitigating the adverse selection problem and lower information asymmetries.

I used the bid-ask spread as a proxy for information asymmetry to perform an OLS regression and a robust regression. For the independent variable of integrated reporting I created a dummy. Based on prior literature (Leuz & Verrecchia, 2000; Roulstone, 2003; Mohd, 2005; Fu et al., 2012) I also added five control variables that are related to the bid-ask spread model. Then I tested the regression assumptions to check the reliability of the analysis. The tests on normality showed that the data does not have a normal distribution and additional testing showed signs of heteroscedasticity in the data. I tried to control for these issues by using the robust standard errors and performing a robust regression analysis. Based on the OLS regression and robust regression results, I conclude that there is no sufficient evidence that the information asymmetry is lower for firms that voluntarily use integrated reporting. These findings are not in line with the research of Lee and Yeo (2016) and García-Sánchez and Noguera-Gámez (2017).

The findings of this research are different from that of Lee and Yeo (2016), because their sample is larger and based on mandatory use of integrated reporting in South Africa. Especially, for this reason it is interesting for further research to test the hypothesis based on a

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29 larger sample and gain more insight on the difference between voluntary and mandatory use of integrated reporting.

Also compared to García-Sánchez and Noguera-Gámez (2017) the results of this research are different. This could be explained by the heterogeneity of the data they used, involving multiple countries that differ in law or practice of voluntary disclosure information. They advise for further research analyzing within the context of a single country.

It is necessary to acknowledge the relatively small sample size as the most important limitation of this study. This limitation arises due to the small amount of companies in the North American region that uses integrated reporting. Also not all of the companies that use integrated reporting have suitable data available to use in research.

This relatively new concept of integrated reporting is still in development and trying to institutionalize itself as a new global standard. This is a limitation that can be resolved over time by more companies using integrated reporting and therefore more data becoming available for analysis. This could have an impact on the non-normal distribution and the heteroscedasticity violation of the regression assumptions and therefore maybe lead to different results. Therefore, this research topic still has potential to be explored in future research.

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30

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