Analysts' Incentives and Systematic Forecast Bias

40 Pages Posted: 19 Mar 2008

See all articles by Senyo Y. Tse

Senyo Y. Tse

Texas A&M University - Lowry Mays College & Graduate School of Business

Hong Yan

Shanghai Jiao Tong University (SJTU) - Shanghai Advanced Institute of Finance (SAIF)

Date Written: March 15, 2008

Abstract

The likelihood that earnings announcements meet or beat analyst expectations differs substantially and systematically across firms. Prior research explores managers incentives to meet analyst expectations. In this paper, we examine analysts incentives to issue systematically biased earnings forecasts and thereby influence the likelihood that firms report good earnings news. We first document that forecast biases are systematically different, as large firms and firms with low forecast dispersion - labeled high-information firms - are more likely to report positive earning surprises, while small firms and firms with large forecast dispersion - labeled low-information firms - tend to have optimistically biased forecasts that often lead to negative earnings surprises. We also show that potential financing needs induce more optimistic forecasts for low-information firms, but this effect is greatly mitigated for high-information firms. We find that career concerns help explain analysts' systematic forecast bias. An analyst's career longevity is enhanced by issuing pessimistic forecasts for high-information firms and optimistic forecasts for low-information firms. Optimistic forecast bias for high-financing-need firms has no consequence for an analyst's career longevity, but optimistic bias for low-financing-need firms hurts. Our results suggest that career concerns contribute to a systematic pattern of forecasting that aligns with managerial preferences.

Keywords: forecast bias, forecast accuracy, firm characteristics, analyst attributes, career concerns

JEL Classification: G29, M41, G24

Suggested Citation

Tse, Senyo Y. and Yan, Hong, Analysts' Incentives and Systematic Forecast Bias (March 15, 2008). Available at SSRN: https://ssrn.com/abstract=1107770 or http://dx.doi.org/10.2139/ssrn.1107770

Senyo Y. Tse

Texas A&M University - Lowry Mays College & Graduate School of Business ( email )

Wehner 401Q, MS 4353
456C
College Station, TX 77843-4218
United States
979-845-3784 (Phone)

Hong Yan (Contact Author)

Shanghai Jiao Tong University (SJTU) - Shanghai Advanced Institute of Finance (SAIF) ( email )

Shanghai Jiao Tong University
211 West Huaihai Road
Shanghai, 200030
China

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