Cardiff University | Prifysgol Caerdydd ORCA
Online Research @ Cardiff 
WelshClear Cookie - decide language by browser settings

Evaluating the properties of analysts' forecasts: a bootstrap approach

Clatworthy, Mark Anthony, Peel, David A. and Pope, Peter F. 2007. Evaluating the properties of analysts' forecasts: a bootstrap approach. The British Accounting Review 39 (1) , pp. 3-13. 10.1016/

Full text not available from this repository.


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.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Business (Including Economics)
Subjects: H Social Sciences > H Social Sciences (General)
H Social Sciences > HC Economic History and Conditions
H Social Sciences > HF Commerce
H Social Sciences > HF Commerce > HF5601 Accounting
Uncontrolled Keywords: Analysts’ forecasts; Wild bootstrap; Deflation; Heteroskedasticity
Publisher: Elsevier
ISSN: 0890-8389
Last Modified: 09 Feb 2020 16:24

Citation Data

Cited 4 times in Google Scholar. View in Google Scholar

Cited 7 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item Edit Item