New Evidence on Financial Analyst Superiority in Forecasting Earnings
Kenneth S. Lorek, Northern Arizona University
Donald P. Pagach, North Carolina State University
ABSTRACT. Prior research demonstrates that analyst advantage (AA) (relative to a univariate time-series ARIMA model) in the prediction of quarterly earnings-per-share (EPS) is associated with certain firm characteristics. We re-examine the linkage between AA and a broader set of economic determinants in light of relatively recent changes in firms’ reporting requirements attributed to FASB’s SFAS No. 131 on segmental disclosure and the SEC’s pronouncement pertaining to Regulation Fair Disclosure. We develop a pooled cross-sectional time-series regression model that evidences improved explanatory power due primarily to the employment of a new treatment variable - quarterly earnings persistence - as well as more precise measurement of the control variable - lines of business - consistent with the relatively new reporting requirements of SFAS No. 131. Both of these variables are significantly positively related to AA.
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