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.