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Informativeness of Performance Measures: Coefficients or R-Squareds?

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  • Ken Li

    (DeGroote School of Business, McMaster University, 1280 Main Street West, Hamilton, ON L8S 4M4, Canada)

Abstract

Measuring the informativeness of earnings is of fundamental importance to accounting research. Both coefficients and R-squareds have been proposed as candidates for measuring the informativeness of earnings. However, recent research has focused substantially more on using coefficients, rather than R-squareds, to draw inferences. This paper first documents in a small theoretical model that under some circumstances, R-squareds map more closely to informativeness than coefficients. Second, this paper documents that in archival data, coefficients and R-squareds can draw opposite inferences regarding the informativeness of earnings and other performance measures up to 50% of the time. Third, this paper proposes an approach to provide statistical inference using R-squareds. Taken together, this paper suggests that rather than solely relying on coefficients, as is common in prior literature, R-squareds can also be used to measure the informativeness of earnings and other performance measures.

Suggested Citation

  • Ken Li, 2024. "Informativeness of Performance Measures: Coefficients or R-Squareds?," JRFM, MDPI, vol. 17(11), pages 1-21, October.
    • Handle: RePEc:gam:jjrfmx:v:17:y:2024:i:11:p:481-:d:1505939
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    References listed on IDEAS

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