Testing in Models of Asymmetric Information

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Abstract
This paper explores the role of testing in models of asymmetric information. We demonstrate conditions under which testing for underlying characteristics can overcome adverse selection problems and lead to a full-information competitive equilibrium. This paper provides a more general statement of Mirrlees result on the optimal use of infinite fines. Where testing cannot fully resolve the problems associated with asymmetric information, we outline the source of the difficulties. Our results, developed in the context of a labour market, can be directly extended to other environments. In problems with asymmetric information, testing to discover an agent's chosen action or underlying characteristics may significantly reduce the cost of moral hazard and adverse selection.

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