A Content Based Assessment of the Relative Quality of Leading Accounting Journals

Cready, William
Liu, Bo
Wang, Di
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This analysis advances faithful representation of statistical evidence as a substantive basis for assessing accounting journal research quality. The analysis builds upon recent work by Cready et al. (2019) indicating that accounting research articles commonly misrepresent null outcomes in their abstracts. Our analysis exploits this reporting deficiency to objectively assess journal reporting quality. The analysis determines misrepresentation rates for five leading general interest academic accounting journals based on direct review of article abstract contents. While all five of these journals commonly publish articles containing such misrepresentations, the relative frequencies with which they do so differ considerably. Moreover, the resulting rankings vary from those commonly reported in existent accounting journal quality and impact assessments. The analysis also finds that financial and archival studies are less prone to statistical evidence misrepresentation while audit and experimental studies are more prone to engaging in such misrepresentation.
Representational Faithfulness, Accounting Quality, Journal Impact Assessment
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