英文摘要 |
The compulsory automobile liability insurance is a mandatory government program in which all automobile owners are required to buy the policy under the no fault liability principle. The premiums are based on the goal of “zero-profit-zero-loss” by spreading the risks among domestic co-insurers. Most literature evaluates the fairness of the premiums based on either the personal or vehicle factors, without due consideration of the dynamic relationship among various sources of risks and premium payments. This study integrates the concept of data envelopment analysis (DEA) and mean-variance portfolio frontier into a distance-function-based premium-indemnity efficient frontier. Premium (the insurance cost) is treated as an input while indemnity (the risk coverage) is treated as an output for each vehicle type. The efficient frontier is established to select the most preferred premium-indemnity combination among its boundary points by either maximizing total indemnities under given premiums or minimizing total premiums under given indemnities. The Malmquist index decomposition is then adopted to decompose the changes of total risks across two periods into the vehicle risk and travel risk components. The vehicle risk component measures the efficiency changes of the premium-indemnity combination and represents how much the risk coverage can be increased without changing the premium or how much the premium can be reduced without affecting the coverage. It can be further decomposed into changes of pure vehicle risk and scale risk. The empirical results indicate that the vehicle risk has increased over the past five years due to the sharp increase of scale risk, but travel risk has decreased at the same time due to better enforcement of safe driving habits. Therefore, a coupling of lower indemnity with higher fuel tax to reduce travel intensity is proposed as a policy solution to improve the efficiency of the compulsory insurance program. |