IDEAS home Printed from https://ideas.repec.org/a/bla/jrinsu/v86y2019i4p861-885.html
   My bibliography  Save this article

A Better Trigger: Indices for Insurance

Author

Listed:
  • Tse‐Ling Teh
  • Christopher Woolnough

Abstract

Index triggers have enabled the extension of insurance to a wide range of risks, by providing a simple mechanism to determine payment. However, the resulting coverage generates basis risk, the variability over time in the level of insurance payouts relative to the level of losses. We analyze basis risk to rank binary and multivalue indices for any risk‐averse individual. Our ranking provides methods to select an index that is optimal for a heterogeneous group and illustrates that higher correlation between loss and index, does not necessarily equate to a better index.

Suggested Citation

  • Tse‐Ling Teh & Christopher Woolnough, 2019. "A Better Trigger: Indices for Insurance," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 86(4), pages 861-885, December.
    • Handle: RePEc:bla:jrinsu:v:86:y:2019:i:4:p:861-885
    DOI: 10.1111/jori.12242
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/jori.12242
    Download Restriction: no
    File URL: https://libkey.io/10.1111/jori.12242?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Robert Hartwig & Greg Niehaus & Joseph Qiu, 2020. "Insurance for economic losses caused by pandemics," The Geneva Risk and Insurance Review, Palgrave Macmillan;International Association for the Study of Insurance Economics (The Geneva Association), vol. 45(2), pages 134-170, September.
    2. Zhixia Wu & Xiazhong Zheng & Yijun Chen & Shan Huang & Wenli Hu & Chenfei Duan, 2023. "Urban Flood Loss Assessment and Index Insurance Compensation Estimation by Integrating Remote Sensing and Rainfall Multi-Source Data: A Case Study of the 2021 Henan Rainstorm," Sustainability, MDPI, vol. 15(15), pages 1-18, July.
    3. Schmidt, Lorenz & Odening, Martin & Schlanstein, Johann & Ritter, Matthias, 2022. "Exploring the weather-yield nexus with artificial neural networks," Agricultural Systems, Elsevier, vol. 196(C).

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bla:jrinsu:v:86:y:2019:i:4:p:861-885. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/ariaaea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.