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dc.contributor.author
Aryal, Gaurab
dc.contributor.author
Gabrielli, Maria Florencia
dc.date.available
2021-08-11T13:04:26Z
dc.date.issued
2019-11
dc.identifier.citation
Aryal, Gaurab; Gabrielli, Maria Florencia; An empirical analysis of competitive nonlinear pricing; Elsevier; International Journal of Industrial Organization; 68; 11-2019; 1-21
dc.identifier.issn
0167-7187
dc.identifier.uri
http://hdl.handle.net/11336/138141
dc.description.abstract
We estimate a model of competitive nonlinear pricing with multidimensional preference heterogeneity using individual level data on advertisements bought by local businesses (e.g., doctors, electricians) from two Yellow Page Directories in one U.S. city-market. Variation in individual choices and payments allows us to identify the joint density of preferences, marginal costs of publishing and common utility parameters. Our estimates suggest substantial welfare loss due to asymmetric information. Comparing duopoly outcomes with (counterfactual) monopoly outcomes, we find that with less competition (i) producer surplus increases substantially; (ii) more “low-type” consumers are excluded; (iii) product variety increases, but benefits accrue only to the “high-type” consumers; (iv) total consumer surplus decreases; (v) but its distribution, across consumers, does not change.
dc.format
application/pdf
dc.language.iso
eng
dc.publisher
Elsevier
dc.rights
info:eu-repo/semantics/restrictedAccess
dc.rights.uri
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
dc.subject
ASYMMETRIC INFORMATION
dc.subject
COMPETITIVE NONLINEAR PRICING
dc.subject
MULTIDIMENSIONAL HETEROGENEITY
dc.subject.classification
Organización Industrial
dc.subject.classification
Economía y Negocios
dc.subject.classification
CIENCIAS SOCIALES
dc.title
An empirical analysis of competitive nonlinear pricing
dc.type
info:eu-repo/semantics/article
dc.type
info:ar-repo/semantics/artículo
dc.type
info:eu-repo/semantics/publishedVersion
dc.date.updated
2021-07-30T18:29:10Z
dc.journal.volume
68
dc.journal.pagination
1-21
dc.journal.pais
Estados Unidos
dc.journal.ciudad
Philadelphia
dc.description.fil
Fil: Aryal, Gaurab. University of Virginia; Estados Unidos
dc.description.fil
Fil: Gabrielli, Maria Florencia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza; Argentina. Universidad Nacional de Cuyo; Argentina
dc.journal.title
International Journal of Industrial Organization
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://linkinghub.elsevier.com/retrieve/pii/S0167718719300669
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1016/j.ijindorg.2019.102538
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