Aggregate earnings for the property-casualty insurance industry have exhibited cyclical behavior for decades. I develop a dynamic model of the insurance industry with endogenous premium setting, risk aversion, and other feedbacks; and use the model to identify strategies to mitigate the cycle. In addition to documenting the insurance industry model this work introduces several strategies for building confidence in system dynamics models when only some data is available. Simulation results suggest that the relative strength of the inputs signals in the premium setting process is the important driver of the stability of insurance industry profits.
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