Prediction versus Inducement and the Informational Efficiency of Going Concern Opinions

48 Pages Posted: 3 Jul 2016 Last revised: 3 Nov 2016

See all articles by Joseph Gerakos

Joseph Gerakos

Tuck School of Business at Dartmouth College

P. Richard Hahn

Arizona State University (ASU) - School of Mathematical and Statistical Sciences

Andrei Kovrijnykh

Arizona State University (ASU)

Frank Zhou

University of Pennsylvania - The Wharton School

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Date Written: October 31, 2016

Abstract

We examine two distinct channels through which going concern opinions can be associated with the likelihood of bankruptcy: auditors have better access to information about their clients' bankruptcy risk and going concern opinions directly induce bankruptcies. Using a bivariate probit model that addresses omitted variable bias arising from auditors' additional information, we find support for both the information and inducement channels. The direct inducement effect of receiving a going concern opinion is a 0.84 percentage point increase in the probability of bankruptcy for firms that do not have a going concern opinion in the prior year. Despite the inducement effect acting as a "self-fulfilling" prophecy, going concern opinions do not correctly predict more bankruptcies than a statistical model based solely on observable data. This result suggests that auditors do not efficiently use information when generating going concern opinions.

Suggested Citation

Gerakos, Joseph and Hahn, P. Richard and Kovrijnykh, Andrei and Zhou, Frank, Prediction versus Inducement and the Informational Efficiency of Going Concern Opinions (October 31, 2016). Available at SSRN: https://ssrn.com/abstract=2802971 or http://dx.doi.org/10.2139/ssrn.2802971

Joseph Gerakos

Tuck School of Business at Dartmouth College ( email )

Hanover, NH 03755
United States

P. Richard Hahn

Arizona State University (ASU) - School of Mathematical and Statistical Sciences ( email )

Tempe, AZ 85287-1804
United States

Andrei Kovrijnykh

Arizona State University (ASU) ( email )

Farmer Building 440G PO Box 872011
Tempe, AZ 85287
United States
480-965-6216 (Phone)

Frank Zhou (Contact Author)

University of Pennsylvania - The Wharton School ( email )

3641 Locust Walk
Philadelphia, PA 19104-6365
United States

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