IDEAS home Printed from https://ideas.repec.org/a/bla/obuest/v81y2019i2p437-455.html
   My bibliography  Save this article

Forecast Evaluation Under Asymmetric Loss: A Monte Carlo Analysis of the EKT Method

Author

Listed:
  • Jens J. Krüger
  • Julian LeCrone

Abstract

This paper contributes to the literature on forecast evaluation by conducting an extensive Monte Carlo experiment using the evaluation procedure proposed by Elliott, Komunjer and Timmermann. We consider recent developments in weighting matrices for GMM estimation and testing. We pay special attention to the size and power properties of variants of the J‐test of forecast rationality. Proceeding from a baseline scenario to a more realistic setting, our results show that the approach leads to precise estimates of the degree of asymmetry of the loss function. For correctly specified models, we find the size of the J‐tests to be close to the nominal size, while the tests have high power against misspecified models. These findings are quite robust to inducing fat tails, serial correlation and outliers.

Suggested Citation

  • Jens J. Krüger & Julian LeCrone, 2019. "Forecast Evaluation Under Asymmetric Loss: A Monte Carlo Analysis of the EKT Method," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 81(2), pages 437-455, April.
    • Handle: RePEc:bla:obuest:v:81:y:2019:i:2:p:437-455
    DOI: 10.1111/obes.12268
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/obes.12268
    Download Restriction: no
    File URL: https://libkey.io/10.1111/obes.12268?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. Conrad, Christian & Lahiri, Kajal, 2023. "Heterogeneous expectations among professional forecasters," ZEW Discussion Papers 23-062, ZEW - Leibniz Centre for European Economic Research.
    2. Siddhartha S. Bora & Ani L. Katchova & Todd H. Kuethe, 2021. "The Rationality of USDA Forecasts under Multivariate Asymmetric Loss," American Journal of Agricultural Economics, John Wiley & Sons, vol. 103(3), pages 1006-1033, May.
    3. Yoichi Tsuchiya, 2022. "Evaluating plant managers’ production plans over business cycles: asymmetric loss and rationality," SN Business & Economics, Springer, vol. 2(8), pages 1-29, August.
    4. Giovannelli, Alessandro & Pericoli, Filippo Maria, 2020. "Are GDP forecasts optimal? Evidence on European countries," International Journal of Forecasting, Elsevier, vol. 36(3), pages 963-973.

    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:obuest:v:81:y:2019:i:2:p:437-455. 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/sfeixuk.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.