Testing for Hidden Information and Action in Automobile Insurance Market

I test the presence of hidden information and action in the automobile insurance market using a data set from several Colombian insurers. To identify the presence of hidden information I find a common knowledge variable providing information on policyholder s risk type which is related to both experienced risk and insurance demand and that was excluded from the pricing mechanism. Such unused variable is the record of policyholder s traffic offenses. I find evidence of adverse selection in six of the nine insurance companies for which the test is performed. From the point of view of hidden action I develop a dynamic model of effort in accident prevention given an insurance contract with bonus experience rating scheme and I show that individual accident probability decreases with previous accidents. This result brings a testable implication for the empirical identification of hidden action and based on that result I estimate an econometric model of the time spans between the purchase of the insurance and the first claim, between the first claim and the second one, and so on. I find strong evidence on the existence of unobserved heterogeneity that deceives the testable implication. Once the unobserved heterogeneity is controlled, I find conclusive statistical grounds supporting the presence of moral hazard in the Colombian insurance market.

Measuring and testing for the systemically important financial institutions

This paper analyzes the measure of systemic importance ∆CoV aR proposed by Adrian and Brunnermeier (2009, 2010) within the context of a similar class of risk measures used in the risk management literature. In addition, we develop a series of testing procedures, based on ∆CoV aR, to identify and rank the systemically important institutions. We stress the importance of statistical testing in interpreting the measure of systemic importance. An empirical application illustrates the testing procedures, using equity data for three European banks.

Genetic testing with primary prevention and moral hazard

We develop a model where a free genetic test reveals whether the individual tested has a low or high probability of developing a disease. A costly prevention effort allows high-risk agents to decrease the probability of developing the disease. Agents are not obliged to take the test, but must disclose its results to insurers. Insurers offer separating contracts which take into account the individual risk, so that taking the test is associated to a discrimination risk. We study the individual decisions to take the test and to undertake the prevention effort as a function of the effort cost and of its e¢ ciency. We obtain that, if effort is observable by insurers, agents undertake the test only if the effort cost is neither too large nor too low. If the effort cost is not observable by insurers, they face a moral hazard problem which induces them to under-provide insurance. We obtain the counterintuitive result that moral hazard increases the value of the test if the effort cost is low enough. Also, agents may perform the test for lower levels of prevention e¢ ciency when effort is not observable