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 paper examines the effect of the mandatory adoption of International Financial Reporting Standards (IFRS) by the European Union on financial analysts’ information environment. To control for the effect of confounding concurrent events, we use a control sample of firms that had already voluntarily adopted IFRS at least two years prior to the mandatory adoption date. We find that analysts’ absolute forecast errors and forecast dispersion decrease relative to this control sample only for those mandatory IFRS adopters domiciled in countries with both strong enforcement regimes and domestic accounting standards that differ significantly from IFRS. Furthermore, for mandatory adopters domiciled in countries with both weak enforcement regimes and domestic accounting standards that differ significantly from IFRS, we find that forecast errors and dispersion decrease more for firms with stronger incentives for transparent financial reporting. These results highlight the important roles of enforcement regimes and firm‐level reporting incentives in determining the impact of mandatory IFRS adoption.

This study examines how financial disclosures with earnings announcements affect sell‐side analysts' information about future earnings, focusing on disclosures of financial statements and management earnings forecasts. We find that disclosures of balance sheets and segment data are associated with an increase in the degree to which analysts' forecasts of upcoming quarterly earnings are based on private information. Further analyses show that balance sheet disclosures are associated with an increase in the precision of both analysts' common and private information, segment disclosures are associated with an increase in analysts' private information, and management earnings forecast disclosures are associated with an increase in analysts' common information. These results are consistent with analysts processing balance sheet and segment disclosures into new private information regarding near‐term earnings. Additional analysis of conference calls shows that balance sheet, segment, and management earnings forecast disclosures are all associated with more discussion related to these items in the questions‐and‐answers section of conference calls, consistent with analysts playing an information interpretation role with respect to these disclosures.

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.

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.

IPOs and direct listings (DLs) offer two different mechanisms for firms to go public. In contrast to IPOs, DLs do not employ an underwriter or raise new capital. Using a sample of IPOs and DLs on major stock markets in the European Union, we document that firms that choose to go public via DLs are larger, more profitable, and less levered, on average, than IPO firms. These pre‐listing differences suggest that DL firms should be less risky than IPO firms; however, controlling for this selection effect, we find that DLs have higher aftermarket price volatility than IPOs. This is consistent with some policy‐makers' concerns that, because they lack an underwriter, DLs expose investors to higher risk than IPOs in the immediate post‐listing period. We show that this heightened price volatility persists, on average, for the first 20 trading days after listings, and is larger in industries where listed peer firms provide relatively low‐quality disclosures. Our results provide new evidence regarding the types of firms that choose to list via DLs versus IPOs and the riskiness of IPOs versus DLs in the immediate post‐listing period; additionally, our results are consistent with underwriters improving the quality of information available to investors for IPO firms in the pre‐listing period.

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.