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Reported earnings and analyst forecasts as competing sources of information: A new approach


  • Heather Anderson

    (Department of Econometrics and Business Statistics, Monash University, Australia)

  • Howard Chan

    (Department of Finance, The University of Melbourne, Australia)

  • Robert Faff

    (UQ Business School, University of Queensland, Australia)

  • Yew Kee Ho

    (Department of Finance and Accounting, National University of Singapore, Singapore)


We apply a new methodology, modified Granger causality tests, to further analyze the information flows between earnings and forecasts. Our application focuses on the dynamic interaction between reported earnings and analysts’ forecasts. Based on long time series of analyst earnings forecasts and reported earnings, we provide formal and compelling evidence of bi-directional ‘causality’. Further, we report that the lag structure in information flows is longer than has been documented in the previous literature. This is consistent with our expectation that, in addition to past earnings reports, the forecasts themselves make a significant contribution to the information that is reflected in future earnings. However, the presence of feedback also suggests that past earnings reports, as well as past forecasts, are incorporated into later forecasts. Collectively, our findings imply that the information in earnings reports has inherent positive value and that forecasts do not fully substitute for earnings releases.

Suggested Citation

  • Heather Anderson & Howard Chan & Robert Faff & Yew Kee Ho, 2012. "Reported earnings and analyst forecasts as competing sources of information: A new approach," Australian Journal of Management, Australian School of Business, vol. 37(3), pages 333-359, December.
  • Handle: RePEc:sae:ausman:v:37:y:2012:i:3:p:333-359

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    More about this item


    Analyst forecasts; Granger causality; information flows; reported earnings;

    JEL classification:

    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • M41 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Accounting - - - Accounting
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models


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