Penalties, Manipulation, and Investment Efficiency

49 Pages Posted: 29 Sep 2017 Last revised: 21 Jul 2018

See all articles by Lin Nan

Lin Nan

Purdue University

Xiaoyan Wen

Texas Christian University

Date Written: June 15, 2018

Abstract

In this study we examine whether imposing a penalty based on an earlier positive signal and a bad realized outcome can be welfare-improving. We find that imposing a penalty helps to improve investment efficiency, but it also brings a deadweight cost of potential penalty for entrepreneurs with good projects. We show that when a good project has a much larger chance to achieve a good outcome than a bad project, or when a large proportion of the penalty can be reimbursed to the investor, it is optimal to impose a penalty to deter entrepreneurs with bad projects from reporting positive signals to the greatest degree, as the benefit from reducing the investment inefficiency outweighs the expected deadweight cost. Otherwise, it is optimal not to impose any penalty.

We also find that a larger penalty may induce more manipulation by a good entrepreneur. This is because, although a larger penalty directly discourages manipulation for both good and bad types by increasing the expected penalty cost, it also encourages upward manipulation by lowering the implicit financing cost upon a high signal. The encouraging effect is mostly pronounced for the good entrepreneur when he has a much larger chance of success than the bad entrepreneur, or when the reimbursement proportion is very high.

Keywords: penalty, manipulation, investment efficiency

JEL Classification: G18, G32, M41

Suggested Citation

Nan, Lin and Wen, Xiaoyan, Penalties, Manipulation, and Investment Efficiency (June 15, 2018). Available at SSRN: https://ssrn.com/abstract=3044082 or http://dx.doi.org/10.2139/ssrn.3044082

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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