Round Number Reference Points and Irregular Patterns in Reported Gross Margins

68 Pages Posted: 24 Nov 2020

See all articles by Matthew C. Cedergren

Matthew C. Cedergren

Santa Clara University

Valerie Li

San Diego State University

Date Written: October 10, 2020


We observe irregular patterns in the distribution of firms’ reported quarterly gross margin percentages. Specifically, we find that there are significantly more firm-quarter observations just above whole percentage integers (e.g., between 55.0% and 55.1%) than there are just below whole percentage integers (e.g., between 54.9% and 55.0%), as compared to what would be expected by mere chance. These patterns are especially pronounced at percentage integers that are particularly “round” (e.g., multiples of 10, such as 30%, 40%, etc.) or are neatly “divisible” (e.g., 25%, 50%, 75%). Further investigation reveals that some investors reward firms with gross margins just above these psychological benchmarks at the time of the earnings announcement, but the presence of more sophisticated and informed investors mitigates such tendencies. In addition, firms reporting gross margins just above round numbers show deteriorated future operating performance. We find no evidence that the irregular patterns of gross margins are related to the presence of management or analyst forecasts of gross margins, nor are they related to these forecasts themselves being round. Our findings are consistent with round numbers being used as implicit psychological reference points for gross margins, as suggested by the theory of reference-dependent preferences, and with gross margins likely being managed to meet or beat these psychological benchmarks.

Keywords: reference dependence, prospect theory, gross margins, gross profit

JEL Classification: M4, M41, G41

Suggested Citation

Cedergren, Matthew C. and Li, Valerie, Round Number Reference Points and Irregular Patterns in Reported Gross Margins (October 10, 2020). Available at SSRN: or

Matthew C. Cedergren (Contact Author)

Santa Clara University ( email )

500 El Camino Real
Santa Clara, CA 95053
United States

Valerie Li

San Diego State University ( email )

San Diego, CA 92182
United States

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