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Auditor–Client Compatibility and Audit Firm Selection

Journal of Accounting Research 2016 54(3), 725-775 open access
ABSTRACT We examine auditor switching conditional on the compatibility of clients and their auditors using a unique text‐based measure of similarity of financial disclosures. We find clustering of clients within an audit firm based on this measure. We find that clients with the lowest similarity scores are significantly more likely (9.4%–10.6%) to switch auditors, and will change to an audit firm to which they are more similar. Regarding the effect on audit quality, we find that discretionary accruals are lower when similarity is higher. However, accounting restatements are more likely when text disclosures that are unaudited—business description, and management discussion and analysis (MD&A)—are more similar. We find no such similarity effect for the audited footnotes. Finally, we find that firms that are more similar are less likely to receive a going concern opinion (GCO), but the GCO reporting decision is more accurate. It is unclear if this reflects higher or lower audit quality since firms that are candidates for a GCO are intrinsically different from the average firm in an auditor's portfolio due to their financial distress. One implication of these results is that auditors might have greater involvement in the quality of the text disclosures that are currently not audited.

If You Want My Advice: Status Motives and Audit Consultations About Accounting Estimates

Journal of Accounting Research 2016 54(5), 1331-1364
Effective consultation is critical for improving the audit of estimates. In an experiment where audit managers acted as consultants to other auditors, we examine conditions in which consultants either recommend estimates that differ substantially from advice-seekers’ assessments (contrariness) or recommend narrower reasonable ranges of estimates (precision). Psychology theory argues that both of these attributes can improve estimates. We examine whether these attributes depend on consultants' status motives, that is, the desire to gain respect from or power over others. We find that active status motives lead consultants with higher specialized knowledge to provide recommendations that are less contrary, but more precise. However, consultants increase precision by tightening range bounds in a manner that is not counter to management's preference and thus unlikely to prompt the audit team to challenge the estimate. We also find that higher consultant decision authority constrains precision. Our findings suggest limits to consultation's potential effectiveness in improving estimates. For instance, our findings suggest that firms and standard setters direct consultants to focus scrutiny on the range bound that is most likely to constrain management opportunism.

Gathering Data for Archival, Field, Survey, and Experimental Accounting Research

Journal of Accounting Research 2016 54(2), 341-395 open access
ABSTRACT In the published proceedings of the first Journal of Accounting Research Conference, Vatter [1966] lamented that “Gathering direct and original facts is a tedious and difficult task, and it is not surprising that such work is avoided.” For the fiftieth JAR Conference, we introduce a framework to help researchers understand the complementary value of seven empirical methods that gather data in different ways: prestructured archives, unstructured (“hand‐collected”) archives, field studies, field experiments, surveys, laboratory studies, and laboratory experiments. The framework spells out five goals of an empirical literature and defines the seven methods according to researchers’ choices with respect to five data gathering tasks. We use the framework and examples of successful research studies in the financial reporting literature to clarify how data gathering choices affect a study's ability to achieve its goals, and conclude by showing how the complementary nature of different methods allows researchers to build a literature more effectively than they could with less diverse approaches to gathering data.