2016
DOI: 10.1016/j.jacceco.2016.03.002
|View full text |Cite
|
Sign up to set email alerts
|

Do accountants make better chief financial officers?

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
2
1

Citation Types

4
113
1
1

Year Published

2017
2017
2024
2024

Publication Types

Select...
7

Relationship

0
7

Authors

Journals

citations
Cited by 148 publications
(119 citation statements)
references
References 71 publications
4
113
1
1
Order By: Relevance
“…The smallest Γ-value for the six outcome variables is 1.29 (CEO Incentive pay), and the largest Γ-value is 2.31 (Restatement). While there is no objective benchmark for determining whether a given Γ-value is large or small (Armstrong et al, 2010, p. 253), our Γ-values are in line with or even larger than the reported Rosenbaum bounds in Armstrong et al 2010and Hoitash et al (2016). However, as our results are sensitive to Panel A (Panel B) reports results when strong (weak) clawback adopters are propensity-matched to non-adopters using the estimated propensity scores from our ordered logistic regression model as presented in Table 2.…”
Section: Sensitivity To Hidden Biassupporting
confidence: 71%
See 1 more Smart Citation
“…The smallest Γ-value for the six outcome variables is 1.29 (CEO Incentive pay), and the largest Γ-value is 2.31 (Restatement). While there is no objective benchmark for determining whether a given Γ-value is large or small (Armstrong et al, 2010, p. 253), our Γ-values are in line with or even larger than the reported Rosenbaum bounds in Armstrong et al 2010and Hoitash et al (2016). However, as our results are sensitive to Panel A (Panel B) reports results when strong (weak) clawback adopters are propensity-matched to non-adopters using the estimated propensity scores from our ordered logistic regression model as presented in Table 2.…”
Section: Sensitivity To Hidden Biassupporting
confidence: 71%
“…The larger the boundary value Γ, the more robust our inferences are to a potential hidden bias. We follow Hoitash et al (2016) and assess the sensitivity of the difference in outcome variables between strong and weak clawback adopters, based on the bounds of the Hodges-Lehmann (HL) point estimate of the average treatment effect. We do so by obtaining the critical Γ-value for which the upper and lower bounds for the HL estimate bracket zero, indicating an insignificant treatment effect among strong and weak adopters.…”
Section: Sensitivity To Hidden Biasmentioning
confidence: 99%
“…However, if managers' preferences are unrelated to their skill set and are correlated with our variables of interest, we could be attributing our results to the matching of firms' needs with managers' skills when, in fact, it is due to some unidentified managerial preference. One such potential preference might stem from risk aversion (e.g., Hoitash et al 2016). For example, if CPA CFOs are generally more risk averse than non CPA CFOs, they might have stronger preferences to avoid working for distressed firms.…”
Section: Determinants Of Hiring a Cpa Cfo (P1)mentioning
confidence: 99%
“…In contrast to standard agency models, a growing body of evidence suggests that the characteristics of corporate executives matter for firm policies and outcomes (e.g., Bertrand and Schoar 2003;Ge et al 2011;Hoitash et al 2016). In this vein, the accounting literature provides evidence that hiring an accounting expert CFO can improve financial reporting outcomes (e.g., Li et al 2010).…”
Section: Introductionmentioning
confidence: 99%
See 1 more Smart Citation