Asymmetric Information and Learning: Evidence from the Automobile Insurance Market
利用汽车保险数据检验逆向选择模型，发现新客户选择高保额与更多事故相关，且这种关联仅存在于有足够驾驶经验的投保人中，部分源于客户向新保险公司少报过往索赔记录。
This paper tests the predictions of adverse-selection models using data from the automobile insurance market. I find that, in contrast to what recent research suggests, the evidence is consistent with the presence of informational asymmetries in this market: new customers choosing higher insurance coverage are associated with more accidents. Consistent with the possibility of policyholders' learning about their risk type, such a coverage-accidents correlation exists only for policyholders with enough years of driving experience. The informational advantage that new customers with driving experience have over the insurer appears to arise in part from customers' underreporting their past claim history: policyholders switching to new insurers are disproportionately ones with a poor claims history, and new customers tend to underreport their past claims history when joining a new insurer. © 2005 President and Fellows of Harvard College and the Massachusetts Institute of Technology.