Measuring Competitive Bidding in the Audit Market and Its Relation to Market Concentration, Audit Quality, and Audit Fees: Evidence from Auditor Views of Company SEC Filings

63 Pages Posted: 23 Feb 2018 Last revised: 7 Feb 2020

See all articles by Nicholas Hallman

Nicholas Hallman

University of Texas at Austin

Antonis Kartapanis

Texas A&M University - Mays Business School; The University of Texas at Austin

Jaime J. Schmidt

University of Texas at Austin

Date Written: January 2020

Abstract

Prior research provides mixed evidence about whether sufficient audit market competition exists and whether competition impairs or improves audit quality. A major impediment to this stream of research is the unobservable nature of the bidding process by which auditors compete for clients. In this study, we apply a machine learning algorithm to non-incumbent (i.e., competitor) auditor views of public companies’ SEC filings to estimate the probability of bidding at the company-year level. We validate our probability estimates using a proprietary sample where all instances of bidding are known. We then investigate the association between the probability of bidding and previously documented measures of auditor competition (i.e., market concentration), audit quality, and audit pricing. Consistent with concerns that market concentration impedes competition, we find that bidding is less likely in industry-concentrated markets. However, contrary to conclusions in the prior literature, we find no evidence that local market concentration is associated with competitive bidding. We also find that bidding is associated with higher quality auditing but does not constrain audit fees.

Keywords: auditor competition, audit market concentration, audit quality, audit fees

Suggested Citation

Hallman, Nicholas and Kartapanis, Antonis and Schmidt, Jaime J., Measuring Competitive Bidding in the Audit Market and Its Relation to Market Concentration, Audit Quality, and Audit Fees: Evidence from Auditor Views of Company SEC Filings (January 2020). Available at SSRN: https://ssrn.com/abstract=3124722 or http://dx.doi.org/10.2139/ssrn.3124722

Nicholas Hallman

University of Texas at Austin ( email )

2317 Speedway
Austin, TX 78712
United States

Antonis Kartapanis

Texas A&M University - Mays Business School ( email )

Wehner 401Q, MS 4353
College Station, TX 77843-4218
United States

The University of Texas at Austin ( email )

2317 Speedway
Austin, TX 78712
United States

Jaime J. Schmidt (Contact Author)

University of Texas at Austin ( email )

Austin, TX 78712
United States

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