Asymmetric Information – Evidence from the Home Insurance Market

In this paper I test whether asymmetric information is present in the home insurance market. To detect the existence of asymmetric information I apply the so-called positive correlation test to a dataset containing approximately 500,000 home insurance contracts gathered from a Norwegian insurer. In addition to the standard formulations of the positive correlation test I propose a method that encompasses joint modeling of frequency and severity. The results from these formulations show that frequency of claims increases in cover while claim costs are independent of cover. Asymmetric information may be driven by adverse selection or moral hazard and the empirical insurance contract literature has suggested different ways to disentangle these. I suggest two methods that can distinguish between these two possible explanations. The first method utilizes detailed claim information that allows me to separate out claims that most likely are driven by moral hazard. Second, I also conduct an instrumental variable regression that utilizes an exogenous reform that had an effect on the insurance price in this market. Both approaches indicate that adverse selection is the prime driver of the information problem. In a final step, I test whether risk aversion affects the results from the positive correlation test. Through detailed socio-economic information (SES) I construct proxies for risk aversion. These proxies turn out to be very important for understanding deductible choice but only marginally important for claim probability. The information problem increases when I control for risk aversion – indicating a small omitted variable bias in the positive correlation test