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Evaluating the properties of analysts’ forecasts: A bootstrap approach

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  • Clatworthy, Mark A.
  • Peel, David A.
  • Pope, Peter F.

Abstract

Previous research has reported that analysts’ forecasts of company profits are both optimistically biased and inefficient. However, many prior studies have applied ordinary least-squares regression to data where heteroskedasticity and non-normality are common problems, potentially resulting in misleading inferences. Furthermore, most prior studies deflate earnings and forecasts in an attempt to correct for non-constant error variances, often changing the specification of the underlying regression equation. We describe and employ the wild bootstrap—a technique that is robust both to heteroskedasticity and non-normality—to assess the reliability of prior studies of analysts’ forecasts. Based on a large sample of 23,283 firm years covering the period 1981–2002, our main results confirm the findings of prior research. Our results also suggest that deflation may not be a successful method of correcting for heteroskedasticity, providing a strong rationale for using the wild bootstrap in future work in this, and other areas of accounting and finance research.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:bracre:v:39:y:2007:i:1:p:3-13
    DOI: 10.1016/j.bar.2006.08.002
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    2. Shu, Yan & Broadstock, David C. & Xu, Bing, 2013. "The heterogeneous impact of macroeconomic information on firms' earnings forecasts," The British Accounting Review, Elsevier, vol. 45(4), pages 311-325.
    3. Clatworthy, Mark A. & Peel, Michael J., 2016. "The timeliness of UK private company financial reporting: Regulatory and economic influences," The British Accounting Review, Elsevier, vol. 48(3), pages 297-315.

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