A Review On The Multidimensional Analysis Of Earnings Quality

There is a generalized consensus among accounting researchers about the multidimensional nature of earnings quality: Earnings quality depends on a series of characteristics that enhance the usefulness of the earnings figure for decision making. In this paper, we undertake a literature revision on empirical research on earnings quality that reveals that, although earnings quality is probably the most recurrent topic in accounting, empirical research that have treated earnings quality as a multidimensional concept is almost inexistent. In this sense, we document that: (1) Most of the empirical papers on earnings quality deal with just one earnings characteristic, not including the potential effect of the other characteristics related to earnings quality. (2) Some characteristics (particularly, accruals quality and, in a lesser way, conservatism) are widely employed for representing earnings quality, whereas other characteristics (smoothness, persistence) are much less used by researchers. (3) The research on the relationships among the different earnings quality characteristics is scant and with mixed results. (4) Only a few papers develop multidimensional measures of earnings quality, but these measures are based on too restrictive assumptions and there is no evidence of superiority over single-property measures. We complement our bibliometric analysis by discussing the limitations of both the single-dimension approach and the multidimensional approaches used to date, illustrating our arguments with a simulation process. Finally, we conclude that the research on earnings quality can benefit from the use of more sophisticated statistical methods, particularly Structural Equation Modelling, for overcoming these issues.

Line-Item Analysis of Earnings Quality provides a comprehensive summary and analysis of the specific earnings quality issues pertaining to key line item components of the financial statements. After providing an overview of earnings quality and earnings management, Line-Item Analysis of Earnings Quality analyzes key line items from the financial statements. For each key line item, the authors: review accounting principles; discuss implications for earnings quality; evaluate the susceptibility of the item to manipulation; describe analyses and red flags which may inform on the item's quality. Line-Item Analysis of Earnings Quality will prove useful in conducting fundamental and contextual analyses through its analysis and evaluations.

This review lays out a research perspective on earnings quality. We provide an overview of alternative definitions and measures of earnings quality and a discussion of research design choices encountered in earnings quality research. Throughout, we focus on a capital markets setting, as opposed, for example, to a contracting or stewardship setting. Our reason for this choice stems from the view that the capital market uses of accounting information are fundamental, in the sense of providing a basis for other uses, such as stewardship. Because resource allocations are ex ante decisions while contracting/stewardship assessments are ex post evaluations of outcomes, evidence on whether, how and to what degree earnings quality influences capital market resource allocation decisions is fundamental to understanding why and how accounting matters to investors and others, including those charged with stewardship responsibilities. Demonstrating a link between earnings quality and, for example, the costs of equity and debt capital implies a basic economic role in capital allocation decisions for accounting information; this role has only recently been documented in the accounting literature. We focus on how the precision of financial information in capturing one or more underlying valuation-relevant constructs affects the assessment and use of that information by capital market participants. We emphasize that the choice of constructs to be measured is typically contextual. Our main focus is on the precision of earnings, which we view as a summary indicator of the overall quality of financial reporting. Our intent in discussing research that evaluates the capital market effects of earnings quality is both to stimulate further research in this area and to encourage research on related topics, including, for example, the role of earnings quality in contracting and stewardship.

This book provides an overview of earnings quality (EQ) in the context of financial reporting and offers suggestions for defining and measuring it. Although EQ has received increasing attention from investors, creditors, regulators, and researchers in different areas, there are various definitions of it and different approaches for its measurement. The book describes the relationship between EQ and earnings management (EM) since they can be considered related challenges, especially in the context of international financial reporting standards (IAS/IFRSs). EM occurs when managers make discretionary accounting choices that are regarded as either an efficient communication of private information to improve the informativeness of a firm’s current and future performance, or a distorting disclosure to mislead the firm’s true performance. The intentional manipulation of earnings by managers, within the limits allowed by the accounting standards, may alter the usefulness of financial reporting and lead to lower quality of earnings. The use of fair value in financial reporting has created a current debate about the impact it might have on EQ. At times, the high subjectivity in estimating fair value can allow opportunities for the exercise of management judgments and intentional bias, which can reduce the quality of financial reporting. Management discretion can result in high EM and hence in a reduction of EQ. Particularly during difficult financial periods, managers engage in EM to mask the negative effects of the turmoil, and in such circumstances accruals and earnings smoothing are attempts to reduce abnormal variations of earnings in such circumstances. This book is a valuable resource for those interested in wider perspectives on EQ and it adds to the research studies on this topic in the context of financial reporting.

Researchers have used various measures as indications of "earnings quality" including persistence, accruals, smoothness, timeliness, loss avoidance, investor responsiveness, and external indicators such as restatements and SEC enforcement releases. For each measure, we discuss causes of variation in the measure as well as consequences. We reach no single conclusion on what earnings quality is because "quality" is contingent on the decision context. We also point out that the "quality" of earnings is a function of the firm's fundamental performance. The contribution of a firm's fundamental performance to its earnings quality is suggested as one area for future work.

The fiscal market is an unpredictable torrent of information that modern organizations strive to understand. Business professionals dedicate themselves to understanding uncertain results around economic performance to improve management, reporting standards, and predict trends in financial statements. International Financial Reporting Standards and New Directions in Earnings Management is an essential reference source that discusses identifying the behavioral patterns of managers and the accounting policies they use in different opportunistic circumstances. Featuring research on topics such as earnings quality, risk reports, and investor protection, this book is ideal for regulatory authorities, accountants, impression managers, auditors, academics, students, and researchers seeking coverage on the theoretical, empirical, and experimental studies that relate to the different themes within earnings management.

This monograph reviews economic models that study earnings management and conservatism in an information economics framework. Both introduce a deliberate or a mandatory bias in financial reports. The fundamental issue this monograph addresses is what economic effects these biases have on earnings quality. We focus on models of managers in firms interacting with rational capital market participants, and briefly consider some contracting models. The models allow us to analyze earnings management and rational inferences by market participants in equilibrium in a variety of settings and to pinpoint costs and benefits of earnings management. We discuss how investors can elicit the maximum information from the biased reports and what potential remedies actually achieve in equilibrium. For example, accounting standards that reduce discretion for earnings management may be detrimental from a welfare point of view. In rational expectations models earnings quality can be defined as the information content in reported earnings. We discuss the earnings response coefficient, value relevance, and accounting-based earnings quality measures and how they reflect changes in earnings quality. Further, we review analytical work on conservatism of accounting standards and why conservatism can be welfare-enhancing even though it introduces a bias in the earnings reports. It is exactly through this bias that the benefit arises. Therefore, a differentiated view of earnings management and conservatism is warranted; neither is principally desirable or undesirable, but this depends on the circumstances. The benefit of equilibrium models is that they offer a rigorous explanation for the phenomena and show that sometimes conventional wisdom does not apply. There exist subtle interactions between accounting standards, the institutional environment, and earnings management that lead to several insights that challenge conventional wisdom. The models describe the economics behind these results and the particular circumstances.

Now in its second edition, this edited book presents recent progress and techniques in partial least squares path modeling (PLS-PM), and provides a comprehensive overview of the current state-of-the-art in PLS-PM research. Like the previous edition, the book is divided into three parts: the first part emphasizes the basic concepts and extensions of the PLS-PM method; the second part discusses the methodological issues that have been the focus of recent developments, and the last part deals with real-world applications of the PLS-PM method in various disciplines. This new edition broadens the scope of the first edition and consists of entirely new original contributions, again written by expert authors in the field, on a wide range of topics, including: how to perform quantile composite path modeling with R; the rationale and justification for using PLS-PM in top-tier journals; psychometric properties of three weighting schemes and why PLS-PM is a better fit to mode B; a comprehensive review of PLS software; how to perform out-of-sample predictions with ordinal consistent partial least squares; multicollinearity issues in PLS-PM using ridge regression; theorizing and testing specific indirect effects in PLS and considering their effect size; how to run hierarchical models and available approaches; and how to apply necessary condition analysis (NCA) in PLS-PM. This book will appeal to researchers interested in the latest advances in PLS-PM as well as masters and Ph.D. students in a variety of disciplines who use PLS-PM methods. With clear guidelines on selecting and using PLS-PM, especially those related to composite models, readers will be brought up to date on recent debates in the field.