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The Differential Value Relevance of S&P's Core Earnings Versus GAAP Earnings: The Role of Stock Option Expense

  • Matthew M. Wieland
    ,
  • Mark C. Dawkins(corresponding author)
    ,
  • Michael T. Dugan
*Corresponding author for this work
  • Indiana University Bloomington
    ,
  • University of Georgia
    ,
  • University of Southern Mississippi
Scholary Output:
Contribution to journal
Article
Peer-review

Abstract

In 2002, Standard & Poor's (S&P) introduced Core Earnings as a proprietary, uniform earnings metric, with the goal of improving financial reporting. The distinguishing feature of Core Earnings is its consistent treatment of seven adjustments to GAAP earnings for which there is no consensus adjustment by managers and analysts. We use stock price and return data to assess whether investors perceive Core Earnings to be more value relevant than GAAP earnings. The implementation of FASB 123R changed the calculation of GAAP and Core Earnings. This change allows us to assess the role of stock option expense in the valuation of earnings numbers by partitioning the sample into pre- and post-FASB 123R periods and creating consistent measures of GAAP and Core Earnings. Our price results indicate that Core Earnings is more value relevant than GAAP earnings in the pre-period after controlling for stock option expense, and in the post-FASB 123R periods. The price results provide empirical evidence consistent with S&P's expectation that a uniformly calculated earnings measure is a more consistent and useful indicator of current performance and future earnings.

Publication Information

Output type

Scholary Output:
Contribution to journal
Article
Peer-review

Original language

English (US)

Pages from-to (Number of pages)

Pages 55-81 (27 pages)

Journal (Volume, Issue Number)

Journal of Business Finance and Accounting (Volume 40, Issue 1-2)

Publication milestones

  • Published - 01/2013

Publication status

Published - 01/2013

ISSN

0306-686X

Publication IDs

  • Scopus: 84874347531

Publication metrics

Metrics

SciVal
citations
9
Fractional count
1
Fractional count
0.33
Fractional count
2
Fractional count
0.67
Fractional count
1
Fractional count
1
Scopus
citations
SciVal
FWCI
0.89
SciVal
Author count
3
SciVal
Paper percentile
64

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