Quality Differentiation with Flavors: Demand Estimation of Unobserved Attributes

Toro-González Daniel (), R. Karina Gallardo (), Jia Yan and Jill McCluskey
Additional contact information
Toro-González Daniel: Universidad Tecnológica de Bolívar, Cartagena, Bolívar, Colombia
Authors registered in the RePEc Author Service: Daniel Toro González ()

Journal of Agricultural & Food Industrial Organization, 2013, vol. 11, issue 1, 101-111

Abstract: This article estimates the demand for mint-flavored gum products using grocery store sales data and accounting for consumers’ valuation of quality. Unobserved product attributes, such as flavor quality, are important elements to consider when estimating the demand for gum. The estimation results suggest that gum is an inelastic product. A positive relationship between willingness to pay and unobserved quality was identified, implying that gum industry should be able to command a premium for higher quality mint-flavored products.

Keywords: quality differentiation; unobserved product attributes; gum (search for similar items in EconPapers)
Date: 2013
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
https://doi.org/10.1515/jafio-2013-0002 (text/html)
For access to full text, subscription to the journal or payment for the individual article is required.

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: https://EconPapers.repec.org/RePEc:bpj:bjafio:v:11:y:2013:i:1:p:11:n:5

Ordering information: This journal article can be ordered from
https://www.degruyter.com/journal/key/jafio/html

DOI: 10.1515/jafio-2013-0002

Access Statistics for this article

Journal of Agricultural & Food Industrial Organization is currently edited by Azzeddine Azzam

More articles in Journal of Agricultural & Food Industrial Organization from De Gruyter
Bibliographic data for series maintained by Peter Golla ().