Analyst Forecast Error: Evidence from Restated Earnings and Analyst Affiliation Pei-Gin Hsieh

1. Analyst Forecast Error: Evidence from Restated Earnings and Analyst Affiliation Pei-Gin Hsieh

2. This Study • Examines the issue of using forecast error as the benchmark for analyst performance. • Increased earnings restatements in recent years. • Significance of analyst conflict of interest issues. • What are the differences between the forecast error of affiliated vs. unaffiliated analysts for restatement firms vs. non-restatement firms?

3. Management Incentives-Meet or Beat Analyst Forecasts • Obtain rewards [Kasznik and McNichols (2002), Chan et al. (2003), Dopuch et al. (2003)] and avoid punishment [Skinner (1994), Kasnick and Lev (1995), Chang (1991), Ip (1998), Myers and Skinner (1999)] from investors via abnormal returns at the time of earnings announcements. • Management Compensation

4. Management Behavior • Manipulate reported earnings upward [GAO (2002)]. • Guide street earnings (the bases of calculating analyst forecast error and earnings surprises) upward [Abarbanell and Lehavy (2002), Ciccone (2002), Doyle and Soliman (2002)]. • Guide analyst forecasts downward [Matsumoto (2002), Richardson et al. (1999), Chan et al. (2003)]. • Goal: Achieve small positive earnings surprises.

5. Consequences of GAAP Earnings Manipulation • Earnings restatements [GAO, 2002]. • Class action lawsuits [Griffin, Grundfest, Perino (2003)]. • Negative market reaction to both types of events [GAO (2002), Richardson et al. (2002), Griffin, Grundfest, Perino (2003)].

6. Analyst Information Sources, Incentives, and Behavior • Information sources: 1. Private Information. 2. Management Guidance. • Incentives: Underwriting [Liu and Song (2001), Lin and McNichols (1998b), DeChow, Hutton, and Sloan (2000)] • Behavior based on Incentives: Put more weight on management guidance. • Goal: Funding and commission.

7. Analyst Forecast Error Research • Analyst forecasts are slightly below earnings [Brown (1997, 1998, 2001), Bagnoli, Beneish, and Watts (1999), Richardson et al. (1999)] due to analyst conflict of interest issues [Chan, Karceski, Lakonishok (2003)]. • Liu and Song (2001) find that affiliated (via lead underwriting relationships) analysts of internet companies are more pessimistic than unaffiliated analysts before the burst of internet bubble in 2000. The former provided pessimistic forecasts, while the later provided optimistic forecasts. However, both types of analysts provide pessimistic forecasts after the bubble burst. • Hansen and Sarin (1996) find insignificant difference between the forecast error of affiliated (via SEOs) vs. unaffiliated analysts. • DeChow, Hutton, and Sloan (2000), Lin and McNichols (1998a) find that analysts’ long-term earnings forecasts are more optimistic for stocks their employers underwrite. • Zhang (2004) find that analyst forecast optimism hurts analysts’ career outcome rather than helps it. • Bajari and Krainer (2004) find that analysts are influenced more by market performance and peer pressure than by investment banking incentives.

8. This Study • Managers • Manipulate GAAP [GAO (2002)] and Street Earnings [Abarbanell and Lehavy (2002), Ciccone (2002), Doyle and Soliman (2002)] Upward. • Guide Analyst Forecasts Downward [Matsumoto (2002), Richardson et al. (1999), Chan et al. (2003)]. • Compensation Incentives [Healy (1985)]. • Analysts • Follow Management Guidance [Matsumoto (2002)]. • Underwriting Incentives [Lin and McNichols (1998b), DeChow, Hutton, and Sloan (2000), Liu and Song (2001)], although prior studies have inconsistent conclusions.

9. Model for Analyst Forecasts • Analyst forecast = a*management guidance + (1-a)*private information • a = f (analysts’ company related incentives).

10. Unanswered Research Questions • How do forecast errors differ when using street earnings versus final earnings (i.e. restated earnings for restatement firms, reported earnings for non-restatement firms) as the basis? • How do forecast errors differ between restatement firms versus non-restatement firms? • How do forecast errors of affiliated analysts differ from those of unaffiliated analysts? • How do forecast errors of the above combinations differ?

11. Definition of Earnings • Street Earnings: continuing operating annual earnings • GAAP (reported, restated, final) Earnings: earnings per share before extraordinary items. • Final Earnings: reported earnings for non-restatement firms; restated earnings for restatement firms

12. Definition of Forecasts and Analysts • The last forecast before each annual earnings announcement [Bernhardt and Campello (2002), Brown and Kim (1991)]. • Affiliated analysts: Analysts whose employers are underwriters of IPOs or SEOs of covered firms within a 6 year window around earnings announcements.

13. Hypotheses 1 • H1a: Street earnings are greater than reported earnings. • H1b: Street earnings are greater than reported earnings for restatement firms. • H1c: The difference between street earnings and reported earnings is greater for restatement firms than for non-restatement firms. • H1d: The difference between street earnings and final earnings is greater than the difference between reported earnings and final earnings for restatement firms.

14. Summary of Sub-Hypotheses 2 & 3

15. Data Sources • Institutional Brokers Estimates System (I/B/E/S) • Compustat • Center for Research in Security Prices (CRSP) • GAO-03-395R, EDGAR, Lexis-Nexis Newswire • SDC

16. Time Period • Earnings restated: 1997-mid 2002. • Misstated and restated earnings: 1992-2001. • Reported earnings, street earnings, analyst forecasts: 1992-2001.

17. Data Analyses

18. Supplemental Analyses Based on the Same Framework for H1-H3 • Magnitude and Direction of Street Earnings Guidance relative to reported earnings and final earnings -Restatement Firms vs. Non-Restatement Firms • Forecast Bias using street earnings, final earnings as the bases -Affiliated vs. Unaffiliated Analysts of Restatement Firms vs. Non-Restatement Firms

19. Summary • Managers of restatement firms manipulate Street Earnings upwards from GAAP Earnings. However, this is not so for non-restatement firms. • For non-restatement firms, there is no difference between the forecast error and forecast bias of affiliated and those of unaffiliated analysts. Hence, there is no evidence of conflict of interest issues for these firms. • For restatement firms, both affiliated and unaffiliated analysts are unable to warn investors about the existence of earnings manipulation. • Affiliated analysts of restatement firms issue forecasts that are greater than Street Earnings. Although the cause for this evidence is unknown, it is not due to conflict of interest issues.

20. Implications and Contributions • There is no need for concern regarding analyst conflict of interest issue. • Academics and Regulators need to help investors identify firms that manipulate earnings. • Regulators need to provide cost effective ways to solve the “restatement firms” problems.