Transitory and persistent earnings components as reflected in analysts' short-term and long-term earnings forecasts: Evidence from a nonlinear model

This study uses a nonlinear framework to examine the relative proportion of transitory and persistent earnings components in financial analysts' earnings forecasts for three different time horizons (one quarter ahead, one year ahead, and three-to-five years ahead). We find that the proportion of transitory earnings components in analysts' forecasts decreases as the forecast horizon is extended. Using a nonlinear multivariate model, we find that both short-term and long-term forecast revisions are important for explaining stock price changes. Our study is important to investors because its results are consistent with analysts using short-term earnings forecasts to signal their expectations about a firm's reported GAAP earnings, and longer-term forecasts to convey their expectations about a firm's more persistent earnings. Moreover, both short-term and long-term forecasts are shown to provide value-relevant information to investors. Our study is important to researchers because it suggests that a nonlinear model is more appropriate for describing the relation between returns and analysts' forecast revisions. Prior studies, using linear models, have underestimated the value-relevance of forecast revisions, especially short-term ones.