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We use employee predictions of their companies' six-month business outlook from Glassdoor.com to assess the information content of employee social media disclosures. We find that average employee outlook is incrementally informative in predicting future operating performance. Its information content is greater when the disclosures are aggregated from a larger, more diverse, more knowledgeable employee base, consistent with the wisdom of crowds phenomenon. Average outlook predicts bad news events more strongly than good news events, suggesting that employee social media disclosures are relatively more important as a source of bad news. Consistent with the organizational theory, we find systematic differences in the quantity and nature of the information in employee disclosures when the disclosures are grouped based on employee attributes and job responsibilities. Finally, average outlook predicts future returns of firms that attract less attention by analysts and investors, suggesting that investors in these firms use outlook inefficiently.

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SYNOPSIS: We investigate the implications of recommendation-forecast consistency for the informativeness of stock recommendations and earnings forecasts and the quality of analysts' earnings forecasts. Stock recommendations and earnings forecasts are often issued simultaneously and evaluated jointly by investors. However, the two signals are often inconsistent with each other. Defining a recommendation-forecast pair as consistent if both of them are above or below their existing consensus, we find that 58.3 percent of recommendation-forecast pairs are consistent in our sample. We document that consistent pairs result in much stronger market reactions than inconsistent pairs. We show that analysts making consistent recommendation forecasts make more accurate and timelier forecasts than do analysts making inconsistent recommendation forecasts, suggesting that consistent analysts make higher-quality earnings forecasts. We extend the literature on informativeness of analyst research by showing that recommendation-forecast consistency is an important ex ante signal regarding both firm valuation and earnings forecast quality. Investors and researchers can use consistency as a salient, ex ante signal to identify more informative analyst research and superior earnings forecasts. Data Availability: All data are available from public sources.