EXTRACTION OF SURPLUS UNDER ADVERSE SELECTION - THE CASE OF INSURANCEMARKETS

We consider a principal-agent setting with two types of risk averse ag ents with different abilities to avoid losses. Abilities (types) are c haracterized by two distributions F and G which are agents' private in formation. All agents have the same increasing and strictly concave ut ility function U, under which G has a higher certainty equivalent. In this environment we derive a characterization of pairs of distribution s under which a first best outcome can be achieved or approximated. We prove that a first best outcome can be achieved if and only if the di stribution F is not absolutely continuous with respect to tile distrib ution G. If this condition is not satisfied, the first best outcome ca n be approximated (arbitrarily close) if and only if the likelihood ra tio dF/dG is unbounded. (C) 1996 Academic Press, Inc.