Visualizing Adverse Selection: An Economic Approach to the Law of Insurance Underwriting
Posted: 30 Jan 2003
This article attempts to clarify the tradeoffs involved in sculpting laws governing the ability of insurers to access predictive information. It does so first by filling a gap in the literature by coupling economic theory to computer-based visualization technology to facilitate a clear yet rigorous understanding of adverse selection. It uses a relatively simple model implemented in the Mathematica programming language to create an "adverse selection laboratory" in which one can explore the dynamics of an insurance market with varying characteristics. Although the article and model is employs are motivated significantly by an interest in the debate over access by life and health insurers to genetic test information, the analysis it develops is in fact far more general and applies to all forms of insurance and risk transfer contracts. The diagrams and analyses employed should help those involved in the field, ranging from students to teachers to courts and legislatures, to better understand when it is sensible for law to support insurance classification of individuals according to perceived risk and when it is sensible for law to oppose such efforts. To demonstrate the power of this method, I conclude the article by showing that denying life insurers access to genetic test information is more dangerous than denying such information to health insurers. I further suggest that even within the health insurance market, it is unwise to regulate insurer access to genetic test information through highly general laws. Rather, regulation in this field needs to take into account the salient features of both the genetic test and the particular risks it is intended to predict.
Keywords: Insurance, Adverse Selection, Genetic Testing, Life Insurance, Health Insurance, Visualization of Information, Mathematica, Risk Aversion, Underwriting
JEL Classification: C61, C63, D30, D63, D81, D82, K29
Suggested Citation: Suggested Citation