Disentangling Adverse Selection and Moral Hazard: Evidence from China’s Automobile Insurance Market

Abstract

Adverse selection and moral hazard are different types of information asymmetry in the insurance market, but their empirical evidence cannot be separated using the traditional positive risk-coverage correlation test. In this paper, we use a new method to disentangle adverse selection and moral hazard, which is to test for the correlation between the past and current claim numbers under experience rating. We conduct the test on the auto insurance data from a Chinese large domestic insurer from 2010-2013. We expect that the serial correlation of claim numbers would be negative under moral hazard but positive under adverse selection because the experience-based rating could incentivize drivers to take more precautions after a claim occurs, which can reduce the number of claims in the next period. However, drivers with high risk should have a consistently high number of claims over time because their risk type does not change dramatically in a short period. Our empirical result shows a negative correlation between the past and current claim numbers, indicating that moral hazard is more critical than adverse selection in this auto insurance market. Besides, the negative coefficient has a larger magnitude for drivers whose no-claim discount rate is higher since these drivers would face a more significant increase in premiums once a claim occurs. We further examine the design of insurance product in this market to investigate why moral hazard is significant. We find that the option of waiving coinsurance liability is underpriced so that over 90 percent of drivers in the sample choose to buy full insurance. Hence, we propose that the regulators should have less stringent regulation on product design and rate.