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Empirical studies on earnings quality use various measures that capture particular dimensions of earnings quality. This paper provides a theoretical foundation to evaluate and compare several common earnings quality measures: value relevance; persistence; predictability; smoothness; and discretionary accruals. We use a rational expectations framework in which a manager has market price, earnings, and smoothing incentives and can bias earnings reports. Taking the information content of reported earnings as a natural benchmark, we determine how variations of management incentives, operating risk, and accounting noise affect earnings quality and examine whether the different measures point in the same or in the opposite direction. We find that value relevance and persistence are measures that are closely aligned with each other and with our benchmark, followed by predictability and smoothness. Discretionary accruals measures are less aligned because they are based on the level of accruals, which confounds their information content. Our results also support the notion that smoother earnings and higher discretionary accruals are associated with greater earnings quality.
