IDEAS home Printed from https://ideas.repec.org/a/sae/globus/v20y2019i2p368-386.html
   My bibliography  Save this article

An Empirical Analysis of Forecast Performance of the GDP Growth in India

Author

Listed:
  • Monika Gupta
  • Mohammad Haris Minai

Abstract

This article evaluates the accuracy of a forecast based on the properties of the forecast error. To measure how close the predictions of GDP growth are to the actual outcome in India, we have calculated three measures of forecast accuracy: mean absolute error (MAE), root mean square error (RMSE) and Theil’s U statistic. To evaluate the performance of the forecasts, we have compared them with naive forecast and common rules of thumb, using moving averages (MAs) as rules of thumb. The results are inconclusive regarding biasedness and also inefficient. Further, the forecasts have a high degree of correlation among themselves. The findings of forecast errors suggest that the performance of Reserve Bank of India (RBI) forecasts is favourable compared to other organizations, as well as with respect to the general international standard.

Suggested Citation

  • Monika Gupta & Mohammad Haris Minai, 2019. "An Empirical Analysis of Forecast Performance of the GDP Growth in India," Global Business Review, International Management Institute, vol. 20(2), pages 368-386, April.
  • Handle: RePEc:sae:globus:v:20:y:2019:i:2:p:368-386
    DOI: 10.1177/0972150918825207
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/0972150918825207
    Download Restriction: no

    File URL: https://libkey.io/10.1177/0972150918825207?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
    ---><---

    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:sae:globus:v:20:y:2019:i:2:p:368-386. 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: SAGE Publications (email available below). General contact details of provider: http://www.imi.edu/ .

    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.