Adverse Selection vs Discrimination Risk with Genetic Testing. An Experimental Approach

We develop a theoretical analysis of two widely used regulations of genetic tests, disclosure duty and consent law, and we run several experiments in order to shed light on both the take-up rate of genetic testing and on the comparison of policy-holders’ welfare under the two regulations. Disclosure Duty forces individuals to reveal their test results to their insurers, exposing them to the risk of having to pay a large premium in case they are discovered to have a high probability of developing a disease (a discrimination risk). Differently, Consent Law allows them to hide this detrimental information, creating asymmetric information and adverse selection. We obtain that the take-up rate of the genetic test is low under Disclosure Duty, larger and increasing with adverse selection under Consent Law. Also, the fraction of individuals who are prefer Disclosure Duty to Consent Law increases with the amount of adverse selection under the latter. These results are obtained for exogenous values of adverse selection under Consent Law, and the repeated interactions experiment devised has not resulted in convergence towards an equilibrium level of adverse selection.

This paper reconsiders evidence from experimental common pool resource games from the perspective of a dynamic model of sampling. Despite being parameter-free, the model is able to replicate some striking features of the data: monotonic frequency distributions, the persistent use of strictly dominated actions, and stable heterogeneity in choices. We argue that these patterns cannot be fully accounted for by existing theories based on other-regarding preferences and norms, and that the dynamics of sampling provide a useful complementary explanation for behavior in social dilemmas.