English  |  正體中文  |  简体中文  |  Items with full text/Total items : 54134/88902 (61%)
Visitors : 10552623      Online Users : 21
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library & TKU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version
    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/68342


    Title: Can Vehicle Maintenance Records Predict Automobile Accidents?
    Authors: 黃瑞卿;汪琪玲;曾郁仁
    Contributors: 淡江大學保險學系
    Date: 2009-10-31
    Issue Date: 2011-10-23 11:53:10 (UTC+8)
    Abstract: This article proposes that vehicle maintenance records can provide useful information for predicting the probability that an owner will have an automobile accident. To test the hypothesis, we use a unique data set that is merged from an insurance company and a vehicle manufacturer in Taiwan. We find weak evidence to support our hypothesis. Among all the proxies for proper maintenance, we indicate that proper maintenance defined by the recommended kilometers is significantly negatively correlated with the loss probability in compulsory automobile liability insurance. The average loss probability decreases by 0.23 percent when the insured vehicle is properly maintained according to the recommended number of kilometers in the previous years, whereas the average loss probability for the overall sample is 0.49 percent. We further find that proper maintenance is insignificantly correlated with loss severity.
    Relation: 2009年臺灣經濟計量學會年會
    Appears in Collections:[Graduate Institute & Department of Insurance Insurance] Proceeding

    Files in This Item:

    There are no files associated with this item.

    All items in 機構典藏 are protected by copyright, with all rights reserved.


    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library & TKU Library IR teams. Copyright ©   - Feedback