Adoption of International Financial Reporting Standards (IFRS) and Measurement of Reporting Quality: A Review of Methodologies

This paper conceptually review the various models employed by previous studies in the measurement of reporting quality following the adoption of International Financial Reporting Standards (IFRS) around the world. In the review, attention is paid to the nature, appropriateness and limitations of each of the models identified. It was found that, the methodologies used in studying the relationship and impact of IFRS on reporting quality are classified into qualitative, quantitative and firm-specific attributes models on one hand, and direct and indirect models on the other hand. Finally, the study calls on researchers to be wary, by selecting appropriate method that commensurates with the objectives of their studies, and their ability to adequately mitigate the limitation of the model highlighted in the review.


INTRODUCTION
The importance of reporting quality and its measurement cannot be over emphasised, as it assists users to differentiate useful financial reports from less useful or even useless ones, this makes it central to the overall concept of financial reporting. The concept of reporting quality and its measurement is as old as the concept of financial reporting itself. The concept became more important and challenging with the adoption of International Financial Reporting Standards (IFRS) around the world. This is because, IFRS adoption has among other issues assures improvement in reporting quality, easy access to capital and elimination of supplementary information by the investors.
However, these assertions by the proponents of IFRS adoption have attracted the interest of many researchers around the world, such as; Barth, Wayne and Mark (2007), van Beest, Geert and Suzanne (2009), Yoon (2007), Kallob (2013), Outa (2011) and Yurisandi and Evita (2015), who examined the relationship between IFRS adoption and reporting, at firms, country, continental and inter-continental levels. But, the major challenge faced by these researches was the measurement of the extent of reporting quality following IFRS adoption, due to the pervasive and multi-dimensional nature of the measurements. In view of the above discussion, this article conceptually reviewed these dimensions, with specific reference to the nature, appropriateness and limitation of each of the dimensions identified from previous studies on the subject matter.

Literature Review
Measurement of reporting quality remains one of the fundamental challenge affecting reporting quality studies (Tasios & Michalis, 2012). The fragile nature of the measurement is evidenced by the lack of single standard methodology employed by studies on the subject matter. Different dimensions are found to be employed by studies, which include; quantitative model, accrual model, firm-specific attributes model and qualitative model.

The Quantitative Model
This model uses financial statements figures in computing a combination of other determinants that include earnings management, earnings quality, value relevance and timely loss recognition. In an earlier attempt to study the relationship between IFRS adoption and accounting quality, this method was used by Barth, et al (2007), in their study, value relevance, earnings management and timely loss recognition were considered as proxies in measuring reporting quality, the model was also used by Outa (2011), andAhmed, Michael andDechun (2012) among others. The model holds that, higher quality of earnings is an indication of less possibilities of earnings management, more value relevance and prompt timely loss recognition are affirmation of improvement in accounting quality (Outa, 2011).
Earnings management reflects relationship between accruals and cash flows, the ratio of variation of the change in net income to the variation of change in cash flows. The higher the ratio of variance of the change in cash flows and higher the ratio of variance of the change in net income. This is interpreted as more positive correlation between cash flows and accruals and lower frequency of small positive net income that indicate less opportunity on the side of management to manipulate earnings (less earnings management). Timely loss recognition means up front recognition of larger net negative income in the financial reporting, while value relevance is measured as the capacity of net income and equity book value to reflect earnings on stock (Barth, et al, 2007). Outa (2011) and Barth et al. (2007) further modified and called the three elements (timely loss recognition, earnings management and value relevance) as quantitative metric, which are either used individually or together in measuring accounting quality, while earnings management has four sub-metrics, value relevance with three and timely loss recognition with only one sub-metric.
Earnings management metrics; are also sub-divided in to earnings smoothing and earnings managing towards a target which has only one metric. The smoothing metrics has three sub-metrics which include, first, variability of adjustment in net income to total assets, second the mean ratio of the variability of adjustment in net income to the variability of the adjustment in operating cash flows and third the spearman ranking correlation between accruals and cash flows. Finally, the metrics for managing earnings toward positive target, which is based on the magnitude of small positive net income.
The three metrics under value relevance are; the equity price (stock) to net income and equity book value metric. The second and third metrics are based on net income per share on yearly return on stock to envisage the effect of bad and good news, while timely loss recognition has one metric, which is measured as the magnitude of huge negative net income.
Similarly, another element that is, sometimes used as a model of itself or along with the quantitative elements is the accrual. According to van Beest et al. (2009) and Kallob (2013), accrual model is employed to measure the degree of earnings management, i.e. manager's deliberate action to manipulate financial reports, with the aim of influencing firm's overall performance, outcome of some contracts or interest in order to mislead stakeholders. Accrual model is measured as inverse of earnings management, the quality of accruals is presented by error variance obtained when working capital accruals is regressed against past, current and lagged cash flows (Tasios & Michalis 2012). This model has been used in the previous studies by a number of authors among which are Dechow and Llia (2002) and Yoon (2007).
However, a major limitation of the quantitative models as expressed by Barth et al. (2007) is lack of assurance, as to whether the findings of the study are only influenced by fluctuations in the financial reporting attributes rather than fluctuations in firm's incentive and economic environment. Similarly, the proponents of qualitative model such as van Beest et al. (2009) criticised this model for its inability to capture all the factors expected to influence reporting quality based on FASB and IASB (2008) improved conceptual framework for financial reporting. The financial reporting attributes used in measuring earnings quality are intersected, which may lead to inconsistency or overlapping effects as they are not separately measured (Yoon, 2007). Moreover, Kallob (2013) observed that, the accruals model only focus on one aspect of reporting quality, i.e. earnings management. While value relevance and timely loss recognition models concentrated only on the financial aspect of reporting quality of relevance and reliability to the neglect of other non-financial attributes such as understandability and comparability.

Firm-Specific Attribute Model
Under this model, some firm or institutional specific financial and non-financial reporting factors such as; revenue, expenses, assets, turnover are selected and measured to determine reporting quality, or relationship between certain institutional factors that include; auditors, number of branches, corporate governance, ownership concentration , economic development and regulatory environment with reporting quality are determined (Raonic & Helena 2012). The method attempts to assess the effect of specific reporting or non-reporting element on user's decisions.
However, the major weakness of this model is, it measures reporting quality indirectly, as it gives more attention to other factors which may not have direct relationship with reporting quality. Likewise its findings are usually limited to the particular attribute observed. Notwithstanding this limitation, the model allows researchers to incorporate several important firm and institutional variables that can influence not only reporting quality but firms' growth, development and survival. Tasios & Michalis (2012), Klai &Abduelwahed (2011) andChalaki, Hameh &Mohacleseh (2012), were among the studies that employed this model.

Operationalized Qualitative Characteristics Model
The qualitative model is another method of measuring reporting quality developed in order to overcome the shortcomings observed with the quantitative and other indirect models of accounting quality measurements. Among others, van Beest et al. (2009), Tasios andMichalis (2012), Kallob (2013) and Agyei-Mensah (2013), have previously utilised this model in their studies. The method operationalised the qualitative characteristics of financial report based on International Accounting Standards Board (IASB) and Financial Accounting Standards Board (FASB) improved conceptual framework for financial reporting (2008 & 2010). In the model, the various aspects of financial reporting and disclosure of both financial and non-financial information that assist user's decisions were captured. Furthermore, the qualitative characteristics are divided into two main classes, i.e. the fundamental and enhanced qualitative characteristics.
According to IFRS Conceptual Framework for Financial Reporting (2014), the fundamental characteristics are the primary attributes which make accounting information useful and a more desirable commodity in decision-making without which information will not be of any value. They consist of relevance with five requirements and faithful representation with another five requirements. The enhanced qualitative characteristics on the other hand are secondary qualitative characteristics that augment the relevance and reliability of accounting information. They are supplementary to the fundamental qualitative characteristics and they make the financial reports more useful in taking decision. They include understandability with five requirements, comparability six requirements, verifiability and timeliness with only one requirement which were compared against a firm financial report. Furthermore, this model is recommended for its ability to cover both financial and nonfinancial reporting quality characteristics. However, its major challenge is the possibility of the effect of personal bias and subjectivity of the researcher in the measurement of reporting quality, i.e. comparison and scoring of the annual reports against the operationalized qualitative characteristics. Nevertheless, the model remains the only one that measures reporting quality directly based on IFRS requirements.

Methodology
This article attempt to highlight the basic methodologies applied by previous studies in their effort to investigate the effect and nature of relationship between IFRS adoption and reporting quality. Hence, the study reviewed previous studies conducted on the effect and relationship of IFRS adoption and reporting quality.

CONCLUSION
The review of related studies indicates various method have been employed by scholars in assessing the impact or relationship between IFRS adoption and reporting quality around the world, and these methods have been classified into qualitative model, quantitative model and firm-specific attribute on one hand and direct and indirect models on the other.
The qualitative model; in the model the qualitative characteristics of financial reporting have been operationalised into a number of questions with a five point Likert scale options, which are qualitatively compared and graded against firms' annual reports. This model is also called direct model, because it measures reporting quality based on agreed IFRS qualitative characteristics of Conceptual Framework for Financial Reporting.
The firm-specific attribute; is an indirect model that, allows studies to use other non-reporting variables to determine reporting quality. This model is more appropriate in measuring the effect of non-reporting variables, i.e. Firm (micro) and institutional (macro) factors on reporting quality.
The quantitative model otherwise known as indirect model, measures reporting quality using quantitative data (mostly financial statements figures). The model includes other methods such as; Value Relevance method, Earnings Management and Earnings Quality methods and Timely Loss Recognition method. Furthermore, this models are called indirect models, because they do not measure reporting quality based on the agreed IFRS Conceptual Framework, in some circumstance they use firm non-financial reporting characteristics in measuring reporting. Finally, researchers need to be cautious, by selecting appropriate method that commensurate with the objective of their studies, and their ability to adequately mitigate the limitation of the model highlighted in the review.