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).

Large earnings surprises and negative earnings surprises represent more egregious errors in analysts' earnings forecasts. We find evidence consistent with our expectation that egregious forecast errors motivate analysts to work harder to develop or acquire relatively more private information in an effort to avoid future forecasting failures. Specifically, we find that after large or negative earnings surprises there is a greater reduction in the error in individual analysts' forecasts of future earnings, and these individual forecasts are based more heavily on individual analysts' private information. This increased reliance on private information reduces the error in the mean forecast of upcoming earnings (even after controlling for the effect of reduced error in individual forecasts). As reliance on private information increases, more of each individual forecast error is idiosyncratic, and thus averaged out in the computation of the mean forecast.

This study documents that M&A delistings are associated with a deterioration in the quality of analysts’ information environment for industry peer firms, measured by an increase in analysts’ absolute forecast errors and dispersion. This effect persists for six quarters and is larger when the delisting target firm contributes relatively more to the industry information environment. Further, we find that, among analysts forecasting earnings for an industry peer firm, those who also followed the delisted target firm in the pre-M&A period experience a larger increase in their absolute forecast errors. A comparison based on public versus private target firms also suggests that the loss of target firms’ public disclosures plays a role in the deterioration in the quality of analysts’ information environment. In additional analyses, we find evidence consistent with this effect resulting from a deterioration in analysts’ ability to exploit across-firm information complementarities.

This study explores whether an increase in the size of firms’ reporting networks (the number of industry peer firms reporting in comparable standards) improves the quality of analysts’ information environments. We exploit the effect of the 2005 mandatory adoption of IFRS around the world on U.S. firms, as IFRS adoption did not directly affect U.S. firms but increased the size of their reporting networks. We document that mandatory IFRS adoption is associated with a significantly larger improvement in the quality of analysts’ information environment for U.S. firms with relatively few domestic industry peers than for other U.S. firms. Further, we show that there is a larger increase in the frequency with which analysts’ research reports for U.S. firms with few domestic peers mention IFRS-adopting EU industry peer firms. Our results provide evidence that mandatory reporting regulations that increase reporting comparability can result in positive information externalities from information network effects.