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Rating Under Asymmetric Information

88 Pages Posted: 16 Jun 2017 Last revised: 31 Dec 2017

Christian Hilpert

Zhongshan University - Lingnan College, Sun Yat-Sen University, China

Stefan Hirth

University of Southern Denmark (SDU)

Alexander Szimayer

University of Hamburg - Faculty of Economics and Business Administration

Date Written: June 15, 2017

Abstract

We study a dynamic signaling game where a firm, by its decision to stay solvent, signals its quality to a rating agency with the rating feeding back into the firm’s cost of capital. Observing the firm’s true cash flow blurred by a persistent measurement error, the error-minimizing rating agency learns dynamically through the firms solvency decision. Firms with higher measurement error default earlier, inducing directional learning by successively eliminating overestimated measurement errors. In a partially separating perfect Bayesian equilibrium in Markov strategies, the firm employs a measurement-error dependent cut-off strategy. We discuss the extensive economic consequences of such a learning mechanism.

Keywords: Rating, Performance Sensitive Debt, Asymmetric Information, Learning, Markov Perfect Bayesian Equilibrium

JEL Classification: G12, G14, G32

Suggested Citation

Hilpert, Christian and Hirth, Stefan and Szimayer, Alexander, Rating Under Asymmetric Information (June 15, 2017). Available at SSRN: https://ssrn.com/abstract=2986850

Christian Hilpert (Contact Author)

Zhongshan University - Lingnan College, Sun Yat-Sen University, China ( email )

Guangzhou
China

Stefan Hirth

University of Southern Denmark (SDU) ( email )

DK-5230 Odense
Denmark

Alexander Szimayer

University of Hamburg - Faculty of Economics and Business Administration ( email )

Von-Melle-Park 5
Hamburg, 20146
Germany

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