Correlation aversion and insurance demand

This research deals with decision problems under two-dimensional risk that can be interpreted as risk to income and health. It presents a basic theoretical insurance model for income and health. An index of absolute correlation aversion allows us to classify bivariate preferences with respect to attitudes towards such a risk. We present the comparative statics of a one-period model for changes in correlation aversion.  We also suggest an improvement to the measurement of the intensity of correlation aversion, and an extension to multi-period models. The concept of correlation aversion is an extension of risk aversion, and is first defined by Richard (1975). A generalized definition for multi-attribute utility functions is then first suggested by Lichtendahl et al. (2012), who also show that a correlation-averse decision maker is risk averse in one dimension. Quite remarkably, despite the significant amount of literature on the concept, the first attempt at the development of an index for the (absolute) correlation aversion was not made until Crainich et al. did so in 2014, almost forty years after the first paper was published on the topic. Our suggestion for the measurement of the intensity of correlation aversion improves the index of Crainich et al. (2014) and captures differences in the degree of correlation aversion for a wide variety of utility functions that are not captured by the index proposed by Crainich et al. (2014). The introduction of such an index sheds more light not only on insurance models and applications, but also on a wide range of multidimensional risk problems.