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Incentive and constraint regulations of rating inflation in collusion over the separation of economic cycles - Markov rating shopping dual reputation model

机译:经济周期分离中勾结中的评级通货膨胀的激励和约束规定-马尔可夫评级购物双重声誉模型

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摘要

Economic cycles may lead to changes in corporate bond credit ratings. This paper utilizes the Markov model to describe transition probability matrixes of economic states for the separation of economic cycles. We develop a new model, which we term the Markov rating shopping dual reputation model, incorporating two reputation effects. This model is well suited to analyze the conditions of the dual rating incentive regulation and the constraint regulation for preventing rating inflation in collusion among credit rating agencies. Then, we apply the Markov regime switching-vector auto-regression (MS-VAR) to estimate the transition probability matrixes of America, England, Japan and China. Based on the numerical analysis and the simulations, the results show that a dual rating regulation can prevent the collusion of inflated ratings, as well as increased rating fees with the separation of economic cycles; additionally, when separating the economic cycles, a constraint regulation is more effective at reducing the risk of rating inflation in collusion and regulatory cost.
机译:经济周期可能导致公司债券信用评级发生变化。本文利用马尔可夫模型描述了经济周期分离的经济状态转变概率矩阵。我们开发了一个新模型,我们将其称为马尔可夫购物评级双重声誉模型,其中包含两个声誉效应。该模型非常适合分析双重评级激励规制和约束规制的条件,以防止信用评级机构之间的合谋中出现评级膨胀。然后,我们应用马尔可夫政权切换向量自回归(MS-VAR)来估计美国,英国,日本和中国的转移概率矩阵。基于数值分析和模拟,结果表明双重评级规则可以防止虚假评级的串通,以及随着经济周期的分离而增加评级费用;另外,当分离经济周期时,约束性规制在降低合谋和规制成本中评级膨胀的风险方面更为有效。

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