Evidence of asymmetric information in the automobile insurance market: Dichotomous versus multinomial measurement of insurance coverage

In the empirical analysis of information asymmetry in automobile insurance markets, prior research used a dichotomous measurement approach that induces excessive bundling in coverage measurements and sample selection biases. To improve on the conditional correlation method for testing information asymmetry, we propose a multinomial measurement approach that constructs coverage categories at ordered multinomial levels. With this approach, we find robust evidence of information asymmetry in both coverage area and coverage amount choices, which we could not find with the dichotomous measurement approach. It thus demonstrates the sensitivity of the empirical findings to the method used to measure insurance coverage.