Estimating demand for opera using sales system data: the case of Finnish National Opera
Jani-Petri Laamanen ()
Journal of Cultural Economics, 2013, vol. 37, issue 4, 417-432
Using detailed data for 2001–2009 from the sales system of the Finnish National Opera, we estimate the determinants of demand for opera tickets. We find that operas in their premiere season are more popular than reprises. Demand is lower for classical operas and higher for domestic operas and for performances with a famous opera singer. Press reviews and the overall popularity of the opera piece have the expected effects. There is also evidence of seasonal effects. By excluding temporarily discounted tickets, controlling for performance characteristics and quality and using a method that takes into account capacity constraints, we are able to credibly estimate the price elasticity of demand. The overall elasticity is close to unity: on average, a 1 % increase in prices would result in 1.16 % decrease in demand. Copyright Springer Science+Business Media New York 2013
Keywords: Demand estimation; Opera; Performing arts; Z11; L32; L82 (search for similar items in EconPapers)
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (11) Track citations by RSS feed
Downloads: (external link)
Access to full text is restricted to subscribers.
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:kap:jculte:v:37:y:2013:i:4:p:417-432
Ordering information: This journal article can be ordered from
http://www.springer. ... cs/journal/10824/PS2
Access Statistics for this article
Journal of Cultural Economics is currently edited by Kathryn Graddy and Samuel Cameron
More articles in Journal of Cultural Economics from Springer, The Association for Cultural Economics International Contact information at EDIRC.
Bibliographic data for series maintained by Sonal Shukla ().