Similarities and differences between stockpiling and reference effects

Robert Slonim and Ellen Garbarino
Additional contact information
Robert Slonim: Discipline of Economics, Faculty of Economics and Business, University of Sydney, Sydney, Australia, Postal: Discipline of Economics, Faculty of Economics and Business, University of Sydney, Sydney, Australia
Ellen Garbarino: Discipline of Marketing, Faculty of Economics and Business, University of Sydney, Sydney, Australia, Postal: Discipline of Marketing, Faculty of Economics and Business, University of Sydney, Sydney, Australia

Managerial and Decision Economics, 2009, vol. 30, issue 6, pages 351-371

Abstract: The correlation of past prices and demand is commonly attributed to reference effects. Although reference dependence is robust, support for loss aversion is mixed; some find demand more sensitive to price increases, consistent with loss aversion, others find no difference or greater sensitivity to price decreases. Stockpiling offers an explanation for these mixed findings. Combining theory, analytical models and simulations, stockpiling and reference dependence predict similar effects and the more stockable the product, the greater sensitivity of demand to price decreases, the opposite of loss aversion. We show that a model combining stockpiling and reference effects best aligns with previous findings and under what conditions each effect should dominate. Copyright © 2008 John Wiley & Sons, Ltd.

Date: 2009
View list of references

Downloads: (external link)
http://hdl.handle.net/10.1002/mde.1453 Link to full text; subscription required (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: http://EconPapers.repec.org/RePEc:wly:mgtdec:v:30:y:2009:i:6:p:351-371

Access Statistics for this article

Managerial and Decision Economics is edited by Paul H. Rubin

More articles in Managerial and Decision Economics from John Wiley & Sons, Ltd.
Series data maintained by Christopher F. Baum ().