Nonparametric identification of endogenous and heterogeneous aggregate demand models: Complements, bundles and the market level

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dc.contributor.authorDunker, Fabian
dc.contributor.authorHoderlein, Stefan
dc.contributor.authorKaido, Hiroaki
dc.date.accessioned2015-08-04T09:13:19Z
dc.date.available2015-08-04T09:13:19Z
dc.date.issued2015
dc.description.abstractThis paper studies nonparametric identification in market level demand models for differentiated products. We generalize common models by allowing for the distribution of heterogeneity parameters (random coefficients) to have a nonparametric distribution across the population and give conditions under which the density of the random coef- ficients is identified. We show that key identifying restrictions are provided by (i) a set of moment conditions generated by instrumental variables together with an inversion of aggregate demand in unobserved product characteristics; and (ii) an integral transform (Radon transform) that maps the random coefficient density to the aggregate demand. This feature is shown to be common across a wide class of models, and we illustrate this by studying leading demand models. Our examples include demand models based on the multinomial choice (Berry, Levinsohn, Pakes, 1995), the choice of bundles of goods that can be substitutes or complements, and the choice of goods consumed in multiple units.en
dc.identifier.urihttp://hdl.handle.net/2003/34181
dc.identifier.urihttp://dx.doi.org/10.17877/DE290R-7734
dc.language.isoende
dc.relation.ispartofseriesDiscussion Paper / SFB 823;28/2015en
dc.subject.ddc310
dc.subject.ddc330
dc.subject.ddc620
dc.titleNonparametric identification of endogenous and heterogeneous aggregate demand models: Complements, bundles and the market levelen
dc.typeTextde
dc.type.publicationtypeworkingPaperde
dcterms.accessRightsopen access

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