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Willingness-to-Pay for Reshuffling Geographical Indications

Published online by Cambridge University Press:  16 June 2020

Monia Saïdi
Affiliation:
CESAER, AgroSup Dijon, INRAE, Université Bourgogne Franche-Comté, 26 boulevard Docteur Petitjean, 21000Dijon, France; e-mail: monia.saidi@agrosupdijon.fr.
Jean-Sauveur Ay*
Affiliation:
CESAER, AgroSup Dijon, INRAE, Université Bourgogne Franche-Comté, 26 boulevard Docteur Petitjean, 21000Dijon, France.
Stéphan Marette
Affiliation:
Université Paris-Saclay, INRAE, AgroParisTech, UMR Economie Publique, Avenue Lucien Brétignière, 78850, Thiverval Grignon, France; e-mail: marette@agroparistech.fr.
Christophe Martin
Affiliation:
INRAE, UMR Centre des Sciences du Goût et de l'Alimentation, 17 rue Sully, 21000Dijon, France; e-mail: christophe.martin@inrae.fr.
*
e-mail: jean-sauveur.ay@inrae.fr (corresponding author)

Abstract

This article presents a new experimental protocol for estimating consumers’ willingness-to-pay (WTP) for products involved in a reshuffle of geographical indications (GIs), e.g., a change of hierarchical levels within a restricted area. Although the collective reputation of a given GI depends on its temporal stability, reshuffling a GI area could make it better aligned with product quality or consumers’ perception. We first provide a simple theoretical model in which consumers put a negative value on within-GI quality variance, thereby showing that reshuffling the GI designation scheme may increase WTP without any change in product quality. Using the experimental protocol, we evaluate consumer perceptions of different reshuffling scenarios for the vineyards of Marsannay, Burgundy, France. The results reveal a significant increase in WTP for the current distribution of products’ quality. Elicited WTP values are then used to simulate the optimal GI reshuffle. (JEL Classifications: L66, Q18, Q28)

Type
Articles
Copyright
Copyright © American Association of Wine Economists, 2020

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Footnotes

We thank an anonymous referee and the editor for their useful comments that greatly improved the quality of this article. Experimental protocol, data, and replication material are available on the remote repository https://github.com/jsay/reshufGI. This work was supported by the project DIETPLUS ANR-17-CE21-0003.

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