Scrutiny and Information Influencing

Posted: 24 Apr 2013 Last revised: 27 Sep 2017

See all articles by Lin Nan

Lin Nan

Purdue University

Xiaoyan Wen

Texas Christian University

Date Written: September 14, 2015

Abstract

In this paper we investigate the effectiveness of imposing scrutiny to fight firms' information garbling. We study a setting in which both firms with good and bad projects are able to influence the informativeness of a public signal regarding their project types through unobservable efforts, and scrutiny will be imposed if the outcome of the project is bad while the previously signal about the project type was good.

We show that a scrutiny threat is indeed effective in deterring bad firms' garbling behavior. However, in most cases it is optimal not to impose scrutiny at all, even if part of the scrutiny cost is reimbursable to investors. This is because scrutiny not only deters bad firms from garbling, but also hurts good firms by punishing them for "bad luck." A good firm may be accidentally punished if the signal is accurate about its type but the outcome unfortunately turns out to be bad. In most cases, the benefit of suppressing garbling is outweighed by the cost of hurting and discouraging good firms, and imposing scrutiny is not efficient. We also find that when a sufficiently large proportion of the scrutiny cost can be reimbursed to investors, a good firm's effort to improve information quality may even increase in the scrutiny cost.

Keywords: scrutiny, information garbling, earnings management

JEL Classification: G18, G32, M41

Suggested Citation

Nan, Lin and Wen, Xiaoyan, Scrutiny and Information Influencing (September 14, 2015). Available at SSRN: https://ssrn.com/abstract=2255724 or http://dx.doi.org/10.2139/ssrn.2255724

Lin Nan

Purdue University ( email )

100 S Grant St
West Lafayette, IN 47907
United States
7654960551 (Phone)

Xiaoyan Wen (Contact Author)

Texas Christian University ( email )

M.J. Neeley School of Business
TCU Box 298530
Fort Worth, TX 76129
United States

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