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|Title:||A comparison of automobile insurance premium savings under selected policy regimes: A simulation model|
|Author(s):||Lynn, Billy Gene|
|Doctoral Committee Chair(s):||Arnould, Richard J.|
|Department / Program:||Economics|
|Degree Granting Institution:||University of Illinois at Urbana-Champaign|
|Abstract:||The major goal of the study is to estimate insurance premium savings for three policy options related to restraint systems in automobiles. It uses a simulation model to estimate savings.
The theoretical model is based on the consumer of a risky product. Assuming the consumer can insure against all costs of a product failure, the model indicates the consumer will place a value on the safety device equal to or greater than the reduction in insurance cost. Previous studies had generally ignored insurance premium savings as a source of benefits for consumers of safety.
Automobile insurance is not a single product, so estimates premium changes for five different coverages--bodily injury, medical payments, comprehensive, collision, and property damage. The first two were of major interest since it is assumed that the major benefit of a passive restraint policy will be reduction of injuries and deaths and these two coverages will be impacted directly by reductions in these while the latter three will only be impacted indirectly.
Assuming that average loss cost is the product of average claim and frequency, a model of average claim was estimated for each of the coverages using cross-sectional insurance data from an unpublished source. A two-stage least squares model of bodily injury insurance and an ordinary least squares model of medical payments insurance is estimated incorporating deaths, injuries, and other explanatory variables in the model.
Given assumptions of usage and effectiveness for each policy, estimates of new levels of average claims were made using a simulation model. Frequency levels were estimated and average loss cost figures were calculated for each state and each coverage. Parameter estimates of an ordinary least squares regression of average loss cost on average premium were used to simulate new average premium estimates under each scenario and for a base case. Premium savings compared to the base case are shown.
|Rights Information:||Copyright 1991 Lynn, Billy Gene|
|Date Available in IDEALS:||2011-05-07|
|Identifier in Online Catalog:||AAI9124455|