In this study we examine changes in the precision and the commonality of information contained in individual analysts' earnings forecasts, focusing on changes around earnings announcements. Using the empirical proxies suggested by the Barron et al. (1998) model that are based on the across-analyst correlation in forecast errors, we conclude that the commonality of information among active analysts decreases around earnings announcements. We also conclude that the idiosyncratic information contained in these individual analysts' forecasts increases immediately after earnings announcements, and that this increase is more significant as more analysts revise their forecasts. These results are consistent with theories positing that an important role of accounting disclosures is to trigger the generation of idiosyncratic information by elite information processors such as financial analysts (Kim and Verrecchia 1994, 1997).

This study examines the association between firms’ intangible assets and properties of the information contained in analysts’ earnings forecasts. We hypothesize that analysts will supplement firms’ financial information by placing greater relative emphasis on their own private (or idiosyncratic) information when deriving their earnings forecasts for firms with significant intangible assets. Our evidence is consistent with this hypothesis. We find that the consensus in analysts’ forecasts, measured as the correlation in analysts’ forecast errors, is negatively associated with a firm’s level of intangible assets. This result is robust to controlling for analyst uncertainty about a firm’s future earnings, which we also find to be higher for firms with high levels of internally generated (and expensed) intangibles. Given that analyst uncertainty increases and analyst consensus decreases with the level of a firm’s intangible assets, we also expect and find that the degree to which the mean forecast aggregates private information and is more accurate than an individual analyst’s forecast increases with a firm’s intangible assets. Finally, additional analysis reveals that lower levels of analyst consensus are associated with high‐technology manufacturing companies, and that this association is explained by the relatively high R&D expenditures made by these firms. Overall, our results are consistent with financial analysts augmenting the financial reporting systems of firms with higher levels of intangible assets (in terms of contributing to more accurate earnings expectations), particularly R&D‐driven high‐tech manufacturers.

This study examines whether dispersion in analysts' earnings forecasts reflects uncertainty about firms' future economic performance. Prior research examining this issue has been inconclusive. These studies have concluded that forecast dispersion is likely to reflect factors other than uncertainty about future cash flows, such as uncertainty about the price irrelevant component of firms' financial reports (Daley et al. [1988]; Imhoff and Lobo [1992]). Abarbanell et al. (1995) argue that, if forecast dispersion after (i.e., conditional on) an earnings announcement reflects uncertainty about firms' future cash flows and this uncertainty causes investors to desire additional information, then dispersion will be positively associated with both (a) the level of demand for more information and (b) the magnitude of price reactions around the subsequent earnings release. In this study, we construct a measure of informational demand using the incidence of analyst forecast updating after dispersion is measured. We find a positive association between dispersion in earnings forecasts after an earnings release and this measure of informational demand. We also find a positive association between forecast dispersion and the magnitude of price reactions around subsequent earnings releases. These associations are most apparent when potentially stale (or outdated) forecasts are removed from measures of forecast dispersion. These associations also persist after controlling for other measures of uncertainty (e.g., beta and the variance of daily stock returns), consistent with dispersion in analysts' earnings forecasts serving as a useful indicator of uncertainty about the price relevant component of firms' future earnings.

This study examines the predictive value of Management Discussion and Analysis (MD&A) information. More specifically, this study tests the association between properties •:;f aaaiysts' earnings forecasts and MD&A quality, where MD&A quality is measured by ';be fiecOTlties Exchange Commission (SEC). We find that high MD&A ratings are associated with less error and less dispersion in analysts' eamings forecasts after controHing for many other expected influences on analysts' forecasts. We also find that esdmated regression coefficients are consistent with MD&A information having a substandal etTect on eamings forecasts. Finally, we fmd our results are driven by forwardlooking disclosures about capital expenditures and operations, and also by historical disclosures about capital expenditures. These findings are consistent with the suggestion by many constituencies (including the SEC) that the type of information found in high quailiy MD&A is particularly relevant for predicting eamings. CondenseSelen la Securities Exchange Commission (SEC) des Etats-Unis, les etats fmanciers a eux seals lie permettent pas de juger de « la probabilite que la performance passee soit revfiktdce de la performance h venir » (SEC 1980 ; 1987 [traduction]). Aussi la SEC exiget-elte que les entreprises dont les titres sont inscrits h la cote foumissent aux interesses sur le marche nn texte appele le rapport de gestion qui contribue a revaluation de la relation entre les MnMces actuels et les b6n6fices futurs. Au depart, la SEC a applique les * Accepted

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