Author ORCID Identifier
Date Available
7-30-2019
Year of Publication
2019
Degree Name
Doctor of Philosophy (PhD)
Document Type
Doctoral Dissertation
College
Business and Economics
Department/School/Program
Accounting
First Advisor
Dr. David A. Ziebart
Abstract
In August, 2014, the Financial Accounting Standards Board issued an update concerning the disclosure of uncertainties about an entity’s ability to continue as a going concern. The standard requires an entities management to evaluate whether there is substantial doubt about the entity’s ability to continue as a going concern and to provide related footnote disclosures in certain circumstances. One consequence of this regulation is the need for guidance for audit testing of management’s assessments in each phase of the audit.
This research evaluates the usefulness of bankruptcy prediction models as analytical tools in the planning stage of an audit for going concern assertions and questions the use of precision as the only measure of a model’s effectiveness. I use simulation to manipulate the fundamental accounting data within five bankruptcy prediction models, explore failure rates in an environment with materiality concerns, and consider the total change in market value due to simulated errors. Given the inherent limitations of the information environment and/or current prediction models, my results indicate auditors’ current failure rates are not an indication of audit failure. The results suggest that bright-line testing using bankruptcy prediction models are sensitive to materiality and that the cost trade-off between Type I and Type II errors is an important indicator of model choice.
Digital Object Identifier (DOI)
https://doi.org/10.13023/etd.2019.457
Recommended Citation
Bundy, Sid, "BINARY BRIGHT-LINE DECISION MODELS FOR GOING CONCERN ASSESSMENT: ANALYSIS OF ANALYTICAL TOOLS FOR BANKRUPTCY PREDICTION CONSIDERING SENSITIVITY TO MATERIALITY THRESHOLDS" (2019). Theses and Dissertations--Accountancy. 12.
https://uknowledge.uky.edu/accountancy_etds/12
