Earnings Uncertainty and Analyst Forecast Herding*

This study empirically investigates how a firm’s earnings uncertainty affects analysts’ herding behaviors in earnings forecasts. Trueman (1994) and Graham (1999) analytically predict that analysts have higher incentives to issue a herding forecast when a firm’s earnings uncertainty is low. We test this analytical prediction using a proxy for bold fore-casts used by Gleason and Lee (2003) and Clement and Tse (2005). We classify analysts’ earnings forecasts as bold when an analyst’s revised forecast is larger (or smaller) than both the analyst’s own prior forecast and the mean consensus forecast of other analysts immediately prior to the analyst’s forecast. Earnings uncertainty is measured by standard deviation of time-serial earnings forecast errors. A logit regression result shows a positive relation between bold forecasts and earnings uncertainty after controlling for analyst characteristics, which is consistent with the prediction by Trueman (1994) and Graham (1999). We also find that as earnings uncertainty increases, the accuracy of analysts ’ bold forecasts relative to consensus forecast accuracy also increases. These results imply that analysts are active in producing new relevant information about firms when earnings un-certainty is higher