Art return rates from old master paintings to contemporary art
Federico Etro () and
Journal of Economic Behavior & Organization, 2021, vol. 181, issue C, 94-116
We study return rates on art investment using a complete dataset on repeated sales for Old Master Paintings, Modern art and Contemporary art auctioned worldwide at Christie's and Sotheby's from 2000 to 2018. We show that return rates do not depend systematically on past prices or the place of sale, but we emphasize substantial differences in returns across sectors. We also control for changes in transaction costs (buyers’ premiums and artists’ resale rights), characteristics of the sale (evening sales, price guarantees and past bought-ins) and news on the lots (changed attributions, public exhibitions or death of the author) that appear reflected in art returns. We confirm the absence of masterpiece effects in American, Chinese and Ethnic art. Finally, using historical data on prices during Renaissance, Baroque and Neoclassical periods, we find evidence that price changes are independent from initial prices also in the long run.
Keywords: Art market; Mei-Moses index; Masterpiece effect; Contemporary art auctions (search for similar items in EconPapers)
JEL-codes: C23 Z11 (search for similar items in EconPapers)
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed
Downloads: (external link)
Full text for ScienceDirect subscribers only
Working Paper: Art Return Rates from Old Master Paintings to Contemporary Art (2020)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:eee:jeborg:v:181:y:2021:i:c:p:94-116
Access Statistics for this article
Journal of Economic Behavior & Organization is currently edited by Houser, D. and Puzzello, D.
More articles in Journal of Economic Behavior & Organization from Elsevier
Bibliographic data for series maintained by Catherine Liu ().