IDEAS home Printed from https://ideas.repec.org/a/oec/stdkaa/5lmqcr2jfbd3.html
   My bibliography  Save this article

Quantification of Qualitative Survey Data and Test of Consistent Expectations: A New Likelihood Approach

Author

Listed:
  • Christian M. Dahl
  • Lin Xia

Abstract

In this paper, we develop a likelihood approach for quantification of qualitative survey data on expectations and perceptions and we propose a new test for expectation consistency (unbiasedness). Our quantification scheme differs from existing methods primarily by using prior information (perhaps derived from economic theory or well established empirical relations) on the underlying process driving the variable of interest. To investigate the properties of our novel quantification scheme and to analyze the size and power properties of the new expectation consistency test, we perform Monte Carlo simulation studies. Overall, the simulation results are very encouraging and show that efficiency gains from including prior information can be substantial relative to existing quantification schemes. Finally, we provide an empirical illustration...

Suggested Citation

  • Christian M. Dahl & Lin Xia, 2004. "Quantification of Qualitative Survey Data and Test of Consistent Expectations: A New Likelihood Approach," Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2004(1), pages 71-92.
    • Handle: RePEc:oec:stdkaa:5lmqcr2jfbd3
    DOI: 10.1787/jbcma-v2004-art5-en
    as

    Download full text from publisher

    File URL: https://doi.org/10.1787/jbcma-v2004-art5-en
    Download Restriction: Full text available to READ online. PDF download available to OECD iLibrary subscribers.
    File URL: https://libkey.io/10.1787/jbcma-v2004-art5-en?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.

    Citations

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


    Cited by:

    1. Malgarini, Marco & Margani, Patrizia & Martelli, Bianca Maria, 2005. "Re-engineering the ISAE manufacturing survey," MPRA Paper 42440, University Library of Munich, Germany.
    2. Lahiri, Kajal & Zhao, Yongchen, 2015. "Quantifying survey expectations: A critical review and generalization of the Carlson–Parkin method," International Journal of Forecasting, Elsevier, vol. 31(1), pages 51-62.
    3. Kajal Lahiri & Yongchen Zhao, 2013. "Quantifying Heterogeneous Survey Expectations: The Carlson-Parkin Method Revisited," Discussion Papers 13-08, University at Albany, SUNY, Department of Economics.

    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:oec:stdkaa:5lmqcr2jfbd3. 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: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/oecddfr.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.