This study examines the predictive value of Management Discussion and Analysis (MD&A) information. More specifically, this study tests the association between properties of analysts' earnings forecasts and MD&A quality, where MD&A quality is measured by the Securities Exchange Commission (SEC). We find that high MD&A ratings are associated with less error and less dispersion in analysts' earnings forecasts after controlling for many other expected influences on analysts' forecasts. We also find that estimated regression coefficients are consistent with MD&A information having a substantial effect on earnings forecasts. Finally, we find our results are driven by forward‐looking 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 quality MD&A is particularly relevant for predicting earnings.

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.