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The Accuracy, Bias and Efficiency of Analysts’ Long Run Earnings Growth Forecasts

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  • Richard D. F. Harris

Abstract

This paper evaluates the accuracy, bias and efficiency of analysts’ long run earnings growth forecasts for US companies. It is shown that forecast accuracy is extremely low. Analysts’ long run earnings growth forecasts are less accurate than the forecasts of a naive model in which earnings growth is forecast to be zero. Consistent with their short run and interim forecasts, analysts’ long run forecasts are shown to be both biased and inefficient. Furthermore, there is evidence that analysts do not fully incorporate information about future earnings that is contained in current share prices. However, the bias and inefficiency of analysts’ forecasts contributes very little to their inaccuracy, which is shown to be primarily the result of random error. It is also shown that the performance of analysts’ long run earnings growth forecasts varies substantially both with the characteristics of the company whose earnings are being forecast and of the forecast itself. The most reliable earnings growth forecasts are low forecasts issued for large companies with low price‐earnings ratios and high market‐to‐book ratios.

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  • Richard D. F. Harris, 1999. "The Accuracy, Bias and Efficiency of Analysts’ Long Run Earnings Growth Forecasts," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 26(5‐6), pages 725-755, June.
    • Handle: RePEc:bla:jbfnac:v:26:y:1999:i:5-6:p:725-755
    DOI: 10.1111/1468-5957.00273
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    Cited by:

    1. Lin, Vera Shanshan & Goodwin, Paul & Song, Haiyan, 2014. "Accuracy and bias of experts’ adjusted forecasts," Annals of Tourism Research, Elsevier, vol. 48(C), pages 156-174.
    2. Lambert, David & Matolcsy, Zoltan & Wyatt, Anne, 2015. "Analysts' earnings forecasts and technological conditions in the firm's investment environment," Journal of Contemporary Accounting and Economics, Elsevier, vol. 11(2), pages 104-120.
    3. Michael Lacina & Byung Ro, 2013. "Market implied future earnings and analysts’ forecasts," Review of Quantitative Finance and Accounting, Springer, vol. 41(2), pages 295-341, August.
    4. Sandrine LARDIC & Karine MICHALON & François DOSSOU, 2008. "Can earnings forecasts be improved by taking into account the forecast bias?," Economics Bulletin, AccessEcon, vol. 7(11), pages 1-20.
    5. Clatworthy, Mark A. & Peel, David A. & Pope, Peter F., 2007. "Evaluating the properties of analysts’ forecasts: A bootstrap approach," The British Accounting Review, Elsevier, vol. 39(1), pages 3-13.
    6. repec:ebl:ecbull:v:7:y:2008:i:11:p:1-20 is not listed on IDEAS
    7. Tetsuya Adachi & Takashi Asano & Tatsushi Okuda, 2016. "Simultaneous Estimation of Cost of Equity and Expected Earnings of Individual Firms with the Residual Income Model," Monetary and Economic Studies, Institute for Monetary and Economic Studies, Bank of Japan, vol. 34, pages 1-38, November.
    8. Chung, Richard & Kryzanowski, Lawrence, 2000. "Market timing using strategists' and analysts' forecasts of S&P 500 earnings per share," Financial Services Review, Elsevier, vol. 9(2), pages 125-144, 00.

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