IDEAS home Printed from https://ideas.repec.org/a/wsi/serxxx/v69y2024i02ns0217590822410028.html
   My bibliography  Save this article

How Informative Are Quantified Survey Data? Evidence From Rbi Household Inflation Expectations Survey

Author

Listed:
  • GAURAV KUMAR SINGH

    (Indian Institute of Management Ahmedabad (IIMA), India)

  • TATHAGATA BANDYOPADHYAY

    (Indian Institute of Management Ahmedabad (IIMA), India)

Abstract

Quantification1 of the ordinal survey responses on inflation expectations is an important preliminary step for undertaking further macroeconomic analysis of the data. In this paper, we briefly describe the standard quantification methods along with the underlying assumptions. We also propose two new methods for quantification. We then apply these methods to quantify the IESH2 data collected by the Reserve Bank of India. An interesting fact that emerges from this exercise is that simpler quantification methods are found to perform better than more complex methods for IESH data. Also, the methods with time-varying weights or time-varying thresholds, as the case may be, work significantly better.

Suggested Citation

  • Gaurav Kumar Singh & Tathagata Bandyopadhyay, 2024. "How Informative Are Quantified Survey Data? Evidence From Rbi Household Inflation Expectations Survey," The Singapore Economic Review (SER), World Scientific Publishing Co. Pte. Ltd., vol. 69(02), pages 619-635, March.
    • Handle: RePEc:wsi:serxxx:v:69:y:2024:i:02:n:s0217590822410028
    DOI: 10.1142/S0217590822410028
    as

    Download full text from publisher

    File URL: http://www.worldscientific.com/doi/abs/10.1142/S0217590822410028
    Download Restriction: Access to full text is restricted to subscribers
    File URL: https://libkey.io/10.1142/S0217590822410028?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    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:wsi:serxxx:v:69:y:2024:i:02:n:s0217590822410028. 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: Tai Tone Lim (email available below). General contact details of provider: http://www.worldscinet.com/ser/ser.shtml .

    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.