ABSTRACT Users of I/B/E/S data generally act as if I/B/E/S reported actual earnings represent the earnings analysts were forecasting when they issued their earnings estimates. For example, when assessing analyst forecast accuracy, users of I/B/E/S data compare analysts' forecasts of EPS with I/B/E/S reported actual EPS. I/B/E/S states that it calculates actuals using a “majority rule,” indicating that its actuals often do not represent the earnings that all individual analysts were forecasting. We introduce a method for measuring analyst inferred actuals, and we assess how often I/B/E/S actuals do not represent analyst inferred actuals. We find that I/B/E/S reported Q1 actual EPS differs from analyst inferred actual Q1 EPS by at least one penny 39 percent of the time during our sample period, 36.5 percent of the time when only one analyst follows the firm (hence, this consensus forecast is based on the “majority rule”), and 50 percent of the time during the last three years of our sample period. We document two adverse consequences of this phenomenon. First, studies failing to recognize that I/B/E/S EPS actuals often differ from analyst inferred actuals are likely to obtain less accurate analyst earnings forecasts, smaller analyst earnings forecast revisions conditional on earnings surprises, greater analyst forecast dispersion, and smaller market reaction to earnings surprises than do studies adjusting for these differences. Second, studies failing to recognize that I/B/E/S EPS actuals often differ from analyst inferred actuals may make erroneous inferences.

Abstract Exclusions from street earnings can include both expected exclusions, forecasted ex ante by analysts, and unexpected exclusions, revealed after earnings are reported. While prior research largely examines total exclusions from street earnings, unexpected exclusions reflect the news or surprise in exclusions. We investigate the properties and informativeness of unexpected exclusions for future profitability, benchmark beating, analyst forecast errors, and future stock returns. We find that unexpected exclusions represent a mix of transitory and recurring items and are informative about future street earnings. In an analysis of hand‐collected analysts' reports, we find that unexpected exclusions are more likely to reflect misestimated recurring items when analysts forecasted exclusions, and unexpected transitory items when analysts did not forecast exclusions. We also examine benchmark‐beating behavior, in which street earnings meet street forecasts but GAAP earnings miss GAAP forecasts. We observe that benchmark beating is more likely to occur when analysts forecast exclusions than when they do not. Moreover, we find unexpected exclusions are more persistent when street earnings meet street forecasts but GAAP earnings miss GAAP forecasts. These findings are consistent with recurring earnings amounts being opportunistically shifted to excluded items to meet analysts' street forecasts. Finally, we find some evidence that analysts and investors react to, but do not fully incorporate, the information in unexpected exclusions, based on forecast revisions and stock price reactions.

ABSTRACT We compare the earnings information produced by the five largest forecast data providers (FDPs)—Bloomberg, Capital IQ, FactSet, I/B/E/S, and Zacks—and observe substantial differences across FDPs in both forecasted and actual street earnings values, and thus the earnings surprise, for the same firm‐quarter. We provide evidence that differences in the earnings surprise across FDPs for the same firm‐quarter (i.e., “FDP differences”) have economically meaningful implications for price responsiveness and liquidity around earnings announcements. We also find that, for announcements where FDPs disagree about whether the announcing firm missed or beat earnings expectations, investors are more likely to side with higher‐quality FDPs but may not fully impound the implications of FDP quality differences during the announcement window. On average, relative to the other FDPs, I/B/E/S ranks highly in our measure of FDP quality, such that investor reactions are likely to align with I/B/E/S earnings information, validating its use as a representative FDP in academic research. Taken together, our results are consistent with FDPs pursuing differentiated information production strategies that generate capital market frictions when these strategies lead to material FDP differences.

We examine the impact of the Global Settlement on affiliation bias in analyst recommendations. Using a broad measure of investment bank-firm relationships, we find a substantial reduction in analyst affiliation bias following the settlement for sanctioned banks. In contrast, we find strong evidence of bias both before and after the settlement for affiliated analysts at non-sanctioned banks. Our results suggest that the settlement led to an increase in the expected costs of issuing biased coverage at sanctioned banks, while concurrent self-regulatory organization rule changes were largely ineffective at reducing the influence of investment banking on analyst research at large non-sanctioned banks.

ABSTRACT We investigate the extent to which market participants use compensation payouts released in the DEF 14A proxy statement (DEF14A) to assess future firm performance by examining sell‐side analysts' earnings forecasts. Consistent with prior work, we confirm that CEO compensation unexplained by current observable economic factors is positively associated with future firm performance. We find that both the likelihood that analysts revise their forecasts following release of the DEF14A and the magnitude and direction of analysts' forecast revisions are positively associated with unexplained CEO compensation. These associations are stronger after the SEC required additional compensation‐related disclosures in late 2006 but lower if the firm has weak corporate governance or more precise other information. Analysts' reactions are not complete, however. Analysts' forecast errors measured months after the DEF14A release are associated with past unexplained compensation, especially in the pre‐2006 period and for analysts who do not revise at the DEF14A release. Taken together, our results suggest that compensation payouts released in the DEF14A contain useful forward‐looking information that is recognized by at least some sophisticated market participants and that the increased disclosure regulations assisted market participants in incorporating this information.

ABSTRACT We describe variation in the reporting quality (i.e., accuracy and bias of reported net asset values (NAVs)) of private equity (PE) funds across types of external monitors (investors and auditors) and third-party service providers (valuation specialists, marketers, and administrators). In contrast to public markets, we find only limited evidence that reporting quality varies with the composition and types of investors in PE funds. We observe, however, that reporting quality varies with auditor involvement and the use of third-party service providers; these associations often differ across buyout (BO) and venture capital (VC) funds and from those observed in public markets. Our evidence is important to investors and regulators, especially now that PE supersedes public markets as the main vehicle to raise capital and as regulators increase their focus on private markets. Data Availability: Data used in this study are available from public sources listed in the paper. JEL Classifications: G1; G14; G30; M4; M41.

ABSTRACT We provide new evidence about how analysts incorporate and improve on management ETR forecasts. Quarterly ETR reporting under the integral method provides mandatory point-estimate forecasts by management, but firms must record certain “discrete” tax items fully in the quarter in which they occur, polluting these forecasts. We investigate management ETR accuracy, analysts' decisions to mimic management's estimate, analysts' accuracy relative to each other or to management, and dispersion. Our comprehensive analysis reveals that analysts deviate from management more and are more accurate relative to management as complexity increases, with real effects on EPS accuracy and dispersion. In contrast to prior research that analysts ignore or are confused by taxes, we provide evidence that analysts pay attention to taxes and improve on management estimates. Based on our evidence that management's quarterly ETRs have less predictive value in the presence of discrete items, we suggest standard-setters reexamine the discrete item exception to require more disclosure.