Analysts often provide forecasts of one-year ahead earnings, earnings two years ahead, as well as long-term earnings growth rates. In this paper, we assume that analysts make earnings forecasts consistent with abnormal earnings exhibiting linear information dynamics (LID) in Ohlson (1995). Under this assumption, each analysts' consensus earnings forecast is determined by three components: analysts' private/other information about future abnormal earnings (not in current abnormal earnings), the persistence in this private/other information, and the persistence in abnormal earnings. For firms with three contemporaneous multi-period earnings forecasts available, we develop a procedure to infer these three implied components from analysts' forecast for each individual firm year. We begin by examining whether analysts' earnings forecasts exhibit LID. We find that LID is not an appropriate description of analysts' information processing for 22% of our firm-year observations. For the remaining 78%, the two symmetrical combinations of the (median) persistence in other information and abnormal earnings are (0.79, 0.36) and (0.36, 0.79). Demonstrating that the two symmetrical combinations of the persistence parameters lead to the same price estimate, we then calculate the predicted firm value (incorporating analysts' private information). Our results show that the predicted firm value is statistically associated with the observed market value. In addition, when abnormal earnings are expressed as an ARMA (2,1) process, the median persistence in current abnormal earnings into forecasted future abnormal earnings is 0.94 and the median persistence in lagged abnormal earnings into forecasted future abnormal earnings is 0.15. Lastly, we show that the association between return and the innovations in other information is statistically significant.
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