The Impact of Offsetting Internal Attributions on Investor Judgments

Abstract

While prior research has primarily focused on how self-serving versus incentive-incompatible attributions impact investors’ judgments, we focus on how combining self-serving or incentive-incompatible attributions with offsetting internal attributions impact investors’ judgments. Offsetting internal attributions are causal explanations attributed to internal actions that impact earnings positively (negatively) in an overall negative (positive) news environment. Our first experiment demonstrates that when a firm has overall negative news, highlighting an offsetting, silver-lining attribution is viewed as more credible/forthcoming when it is accompanied by an overall incentive-incompatible versus self-serving attribution. Therefore, highlighting the silver-lining offset improves investors’ earnings estimates only when the management has also been highlighting incentive-incompatible versus self-serving attributions. Our second experiment finds that highlighting an offsetting, blemish attribution together with self-serving attributions increases credibility/forthcomingness assessments more than highlighting self-serving attributions alone. Our study extends research on management attributions and strategic disclosures and has practical implications.

Keywords:

• CEO social media
• incentive-incompatible attributions
• management attributions
• offsetting attributions
• self-serving attributions

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 In practice, companies can offer offsetting attributions that are due to external or internal factors. In this research, we focus on offsetting attributions that are due to internal factors such as new marketing strategies, changes in product mix, and cost-saving efforts, among others.

2 The Institutional Review Board at the affiliated university approved the use of human participants for the experiments reported in this paper. Data are available from authors upon request.

3 All p-values reported in the text are two-tailed unless otherwise noted.

4 A conventional ANOVA tests for two main effects and a disordinal interaction. It does not provide appropriate or powerful tests for hypothesized ordinal interactions, which are best tested with planned contrast coding (Buckless and Ravenscroft 1990, Guggenmos et al. 2018). While we provide the conventional ANOVA table for completeness, we caution against interpreting the effects from this analysis given our ordinal interaction prediction. Thus, we test H2 using a planned interaction contrast followed by simple main effects tests (Keppel and Wickens 2004).

5 We also asked participants to rate on a 0–10 point-scale how likely they think the firm will be able to improve its future performance under the CEO’s leadership. Results are not significantly different across conditions.

6 Untabulated ANOVAs also find that our manipulations have no between-group effects on investors’ competence ratings (F3,139 = 0.350, p = 0.789) or their ratings of the firm’s current performance (F3,139 = 0.835, p = 0.477), suggesting that our manipulations do not create perception differences in the CEO’s capability or the firm’s current economic data across conditions. These results provide some assurance that our main EPS results are not driven by our manipulations sending different signals about the firm’s current fundamental economics.

7 Untabulated ANOVA tests also suggest that our conditions have no overall effect on investors’ competence ratings (F3,152 = 1.434, p = 0.235) or their assessments of the firm’s current or future performance (F3,152 = 0.852, p = 0.468 and F3,152 = 0.610, p = 0.610, respectively).