Earnings Management Revisited: A Synthesis of Theory, Evidence, and Measurement from the 100 Most Influential Studies

This paper provides a theory-informed synthesis of earnings management research through a review of the 100 most cited studies in the accounting literature. Rather than functioning as a purely bibliometric review, the study integrates theoretical, empirical, methodological, and survey-based contributions to examine how influential research has conceptualized, measured, and interpreted earnings management. Citation data were collected from Web of Science and Google Scholar as of 5 January 2025 using predefined search criteria, filtering procedures, and classification protocols. While citation counts are used to identify influential studies, they are not treated as direct indicators of research quality due to concerns regarding citation bias, publication visibility, and proxy limitations. The review organizes the literature around major themes, including corporate governance, audit quality, managerial incentives, institutional environments, market reactions, and regulatory change. The analysis highlights enduring debates concerning proxy validity, endogeneity and identification challenges, the distinction between statistical detection and economic significance, and the trade-off between accrual-based and real earnings management. The synthesis also incorporates emerging research streams involving family firms, gender diversity, ESG reporting, textual analysis, and AI-assisted analytics within broader agency and institutional theory perspectives. A central contribution of the paper is the development of an integrative analytical framework linking proxy validity, strategic substitution between reporting mechanisms, and institutional constraints within a unified interpretation of earnings management behavior. The review shows that advances in empirical design, textual analysis, machine learning, and predictive analytics extend rather than replace foundational insights, while persistent limitations in causal inference and measurement remain unresolved. Overall, the findings suggest that earnings management is best understood as a strategic response to incentives, monitoring, and institutional constraints rather than as a uniform indicator of opportunistic behavior. The paper concludes by outlining future research directions focused on theory-driven empirical design, methodological triangulation, AI-assisted detection approaches, and improved measurement frameworks across diverse reporting environments.