The Interdependent Use of Earnings and Dividends in Financial Analysts' Earnings Forecasts

This paper examines how analysts combine earnings and dividend information when they predict future earnings. Because both earnings and dividends are noisy indications of future earnings, we posit that analysts use the two corroboratively, to confirm the information reflected in each, and that analysts will substitute away from earnings when it is noisy and toward dividends. Using regressions of analysts' earnings forecast revisions on unexpected earnings, unexpected dividends, and five variables that reflect whether the signs of unexpected earnings and dividends confirm or contradict each other, we find evidence of both corroboration and substitution. Analysts' earnings forecast revisions are significantly related to the five corroborative variables, and this relation has statistically significant explanatory power beyond that in the magnitudes of unexpected earnings and unexpected dividends. Consistent with expectations, we find that the evidence of corroboration varies across the noisiness of earnings information; there is more evidence of corroboration when earnings are more variable. We also find evidence consistent with analysts substituting away from earnings, toward dividend information for firms with noisy earnings information (high variance). Overall, the results imply that analysts use earnings and dividends information interdependently, with some interdependency determined by the noisiness of earning announcements