BENEFICIAL CHANGES IN RANDOM-VARIABLES UNDER MULTIPLE SOURCES OF RISK AND THEIR COMPARATIVE STATICS

The consequences of a change in a random parameter are determined for a decision model with more than one source of randomness. The two cases of independent and stochastically dependent sources of risk are discussed. Four comparative static theorems are given. These state the effect of first degree stochastically dominant shifts or risk decreases for one random variable while the other random variable is held fixed. Deterministic transformations are used to represent random parameter changes. The results are presented in the context of the coinsurance demand model with a risky insurable asset and background risk.