Earnings Quality

Earnings Quality

This report analyzes earnings quality relating measures to decision usefulness as well as Hicksian income, or true income. The earnings quality constructs and measures are derived from four classes of constructs which will be discussed below.

Earnings quality can be measured by looking at the constructs derived from the time-series properties of earnings including persistence, predictability and variability. Persistence captures the extent to which a given innovation remains into the future, or that the trend will continue moving in its present direction, for example a strong upward or a strong downward trend. A random walk pattern is highly persistence where a mean-reverting series has no persistence. Predictability is the ability of past earnings to predict future earnings and is a decreasing function of variability. When earnings are difficult to predict, the predictability construct is disconnected from Hicksian income because they would be viewed as high-quality from a Hicksian income standpoint, but viewed as low-quality from the predictability standpoint. Variability measures the time-series variance of innovations directly. Smoothness is often associated with high-quality earnings; however this could be due to management engaging in smoothing practices. Artificially smoothed earnings are not representationally faithful and therefore there is a disconnect between variability and Hicksian income.

Analyzing earnings quality using qualitative concepts encompasses three terms: relevance, reliability and comparability. Using these terms to show if earnings have merit is a significant challenge for this construct. These terms need to be taken as a whole when using them for financial information and not analyzed individually. Trade-offs among certain terms is sometimes reasonable and necessary. For example, a company will need to express timely information within its financials emphasizing relevance, but this may be a trade-off with...