Studies of the information content of accounting earnings typically assume earnings response coefficients do not vary across firms. Valuation models relating earnings to security prices, however, predict that earnings response coefficients are positively associated with revision coefficients (coefficients relating current earnings to future earnings) and negatively associated with expected rates of return. A random coefficient regression model provides evidence consistent with these predictions. This evidence has implications for interpreting multiple regression models that relate abnormal returns to unexpected earnings and other information variables.

The paper analyzes the contemporaneous association between market returns and earnings for long return intervals. The research design exploits two fundamental accounting attributes: (i) earnings aggregate over periods, and (ii) expanding the interval over which earnings are determined, is likely to reduce ‘measurement errors’ in (aggregate) earnings. These concepts lead to the level of (aggregate) earnings as a natural earnings variable for explaining security returns. We hypothesize that the longer the interval over which earnings are aggregated, the higher the cross-sectional correlation between earnings and returns. The empirical findings support this hypothesis.