IDEAS home Printed from https://ideas.repec.org/p/ebg/heccah/1037.html
   My bibliography  Save this paper

Unique Durable Assets

Author

Listed:
  • Lovo , Stefano
  • Spaenjers , Christophe

Abstract

This paper presents a model of trading in unique durable assets that provide idiosyncratic payoffs, such as art, luxury real estate, and firm subsidiaries. Agents make purchase and sale decisions in an auction market based on their private use value of the asset and on the expected resale revenues. Individuals with a relatively strong taste for the asset are willing to pay a high price and sell only when hit by a liquidity shock. By contrast, those deriving little pleasure from ownership aim to resell quickly at a profit if winning an auction despite their low bids. As a result, holding periods and financial returns are negatively correlated. Furthermore, speculative activity increases in economic expansions, leading to a positive correlation between prices and voluntary sales volume. The empirical predictions of our model find support in historical art transaction data.

Suggested Citation

  • Lovo , Stefano & Spaenjers , Christophe, 2014. "Unique Durable Assets," HEC Research Papers Series 1037, HEC Paris.
    • Handle: RePEc:ebg:heccah:1037
    as

    Download full text from publisher

    File URL: http://ssrn.com/abstract=2404339
    Download Restriction: no
    ---><---

    Citations

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


    Cited by:

    1. Goetzmann, William N. & Jones, Peter W. & Maggioni, Mauro & Walden, Johan, 2016. "Beauty is in the bid of the beholder: An empirical basis for style," Research in Economics, Elsevier, vol. 70(3), pages 388-402.
    2. Spaenjers, Christophe & Goetzmann, William N. & Mamonova, Elena, 2015. "The economics of aesthetics and record prices for art since 1701," Explorations in Economic History, Elsevier, vol. 57(C), pages 79-94.
    3. Lily Shen & Stephen L. Ross, 2019. "Information Value of Property Description: A Machine Learning Approach," Working papers 2019-20, University of Connecticut, Department of Economics, revised Sep 2020.
    4. Shen, Lily & Ross, Stephen, 2021. "Information value of property description: A Machine learning approach," Journal of Urban Economics, Elsevier, vol. 121(C).
    5. William Goetzmann & Elena Mamonova & Christophe Spaenjers, 2014. "The Economics of Aesthetics and Three Centuries of Art Price Records," NBER Working Papers 20440, National Bureau of Economic Research, Inc.

    More about this item

    Keywords

    auctions; durable goods; endogenous trading; private value; speculation;
    All these keywords.

    JEL classification:

    • D44 - Microeconomics - - Market Structure, Pricing, and Design - - - Auctions
    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • Z11 - Other Special Topics - - Cultural Economics - - - Economics of the Arts and Literature

    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:ebg:heccah:1037. 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: Antoine Haldemann (email available below). General contact details of provider: https://edirc.repec.org/data/hecpafr.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.