References (30)


Citations (2)



Dueling Experts and Imperfect Verification

Kenton K. Yee

Mellon Capital Management

December 6, 2008

International Review of Law and Economics, Vol. 28, No. 4, pp. 246-255, 2008

In the Dueling Experts Game, adversarial experts strategically produce "good" or "bad" evidence to support their partisan testimony. Good evidence is probative while bad evidence has no evidential value. The new feature of this Game is that Judge sometimes erroneously identifies good evidence as bad evidence and vice versa. Along the Game's equilibrium path, each partisan expert produces only good evidence if it supports his side. When favorable good evidence is unavailable, an expert produces bad evidence to support his testimony. Hence, dueling experts always contradict one another. Despite their conflicting testimony, one of the experts invariably produces the available good evidence for Judge. Therefore, Judge always receives the available good evidence. A central result is that the quality of experts, including their ability to persuade judges using available good evidence, and the quality of judges - their ability to distinguish good from bad evidence - determine the accuracy of verdicts. Remarkably, the likelihood that experts are endowed with good evidence does not matter provided that this likelihood is not identically zero or one.

Number of Pages in PDF File: 33

Keywords: equity valuation, shareholder litigation, expert testimony, judicial error

JEL Classification: C70, D80, G20, K00, K22, K41, M40

Open PDF in Browser Download This Paper

Date posted: December 7, 2008  

Suggested Citation

Yee, Kenton K., Dueling Experts and Imperfect Verification (December 6, 2008). International Review of Law and Economics, Vol. 28, No. 4, pp. 246-255, 2008. Available at SSRN: https://ssrn.com/abstract=1312222

Contact Information

Kenton K. Yee (Contact Author)
Mellon Capital Management ( email )
50 Fremont Street, #3819
San Francisco, CA 94105
United States
415-975-3565 (Phone)
Feedback to SSRN

Paper statistics
Abstract Views: 3,086
Downloads: 250
Download Rank: 96,129
References:  30
Citations:  2
Paper comments
No comments have been made on this paper