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University of Toronto

Using Peer Firms to Examine whether Auditor Industry Specialization Improves Audit Quality and to Enhance Expectation Models for Analytical Audit Procedures

Abstract

dc:description.abstract

This dissertation investigates how economically-comparable peer firms can be used to obtain inferences about a company’s accounting quality in two different research settings. The first Chapter examines whether auditor industry specialization, measured using auditor market share by industry, improves audit quality. After matching clients of specialist and non-specialist auditors according to industry, size and performance, there are no significant differences in audit quality between these two groups of auditors. In addition, this Chapter uses two analyses that do not rely primarily on matched samples. First, examining a sample of Arthur Andersen clients that switched auditors in 2002, there is no evidence of industry-specialization effects following the auditor change. Second, using a simulation approach, this study shows that client characteristics, and particularly client size, influence the observed association between auditor industry specialization and audit quality. Overall, these findings do not imply that industry knowledge is not important for auditors, but that the methodology used in extant studies examining this issue may not fully parse out the effects of auditor industry expertise from client characteristics. The second Chapter examines whether account-level expectation models for analytical audit procedures can be enhanced by using information from economically-comparable peer firms. This Chapter assesses the effectiveness of three main types of expectation models, with and without including information from peer firms: heuristic, time-series, and industry cross-sectional models. Information from peer firms improves the accuracy of all models and improves the detection power of time-series and industry cross-sectional models. Comparing between models, one-period heuristic models are generally unreliable, and industry cross-sectional models can be more effective than time-series models. These findings may help auditors of public companies and financial analysts in selecting expectation models and finding peer firms to assess the reasonability of a company’s financial information at the account-level.

Degree

thesis:*
Department dc:contributor.department
Management
Year dc:date.issued
2012

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Meza, Miguel Minutti
Advisors dc:contributor.advisor
  • Richardson, Gordon
  • Zhang, Ping

Subjects

dc:subject × 6

Rights

Language dc:language.iso
en_ca

Identifiers

dc:identifier.*
Handle dc:identifier.uri
http://hdl.handle.net/1807/31867
OAI identifier oai:identifier
oai:utoronto.scholaris.ca:1807/31867

Chain of custody

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University of Toronto
Base URL
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Last updated
2026-07-27
Source record
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citation

Meza, Miguel Minutti. Using Peer Firms to Examine whether Auditor Industry Specialization Improves Audit Quality and to Enhance Expectation Models for Analytical Audit Procedures. 2012. http://hdl.handle.net/1807/31867