IDEAS home Printed from https://ideas.repec.org/a/taf/oaefxx/v6y2018i1p1443372.html
   My bibliography  Save this article

The comparison of the hedonic, repeat sales, and hybrid models: Evidence from the Chinese paintings market

Author

Listed:
  • Fang Wang
  • Xu Zheng

Abstract

With the objective of evaluating the accuracy of price index models, we adopt a series of techniques to compares the performances of the hedonic, repeat sales, and hybrid models based on the data from the Chinese most representative painter, Qi Baishi during the period from 2000 to 2016. When applying the mean squared error (MSE) technique, the repeat sales model outperforms alternative models. However, according to the correlations and width confidence intervals, the hybrid model provides the most reliable estimates of price indices. The study also shows that the repeat sales model obtains relatively a lower total return estimate as well as a higher volatility than other two models. Our findings have important implications in identifying the precision of index models and provide supplements to art investment studies..

Suggested Citation

  • Fang Wang & Xu Zheng, 2018. "The comparison of the hedonic, repeat sales, and hybrid models: Evidence from the Chinese paintings market," Cogent Economics & Finance, Taylor & Francis Journals, vol. 6(1), pages 1443372-144, January.
  • Handle: RePEc:taf:oaefxx:v:6:y:2018:i:1:p:1443372
    DOI: 10.1080/23322039.2018.1443372
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/23322039.2018.1443372
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/23322039.2018.1443372?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. Vecco, Marilena & Chang, Simeng & Zanola, Roberto, 2022. "The more you know, the better: A Heckman repeat-sales price index," The Quarterly Review of Economics and Finance, Elsevier, vol. 85(C), pages 194-199.
    2. Alan G Phipps & Dingding Li, 2019. "Calibration and evaluation of Quigley’s hybrid housing price model in Microsoft Excel," PLOS ONE, Public Library of Science, vol. 14(4), pages 1-18, April.

    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:taf:oaefxx:v:6:y:2018:i:1:p:1443372. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/OAEF20 .

    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.