Identifying demand with multidimensional unobservables
Subtitle: a random functions approach
By: Jeremy T. Fox, Amit Gandhi
Contributors: Gandhi, Amit; National Bureau of Economic Research
Series: NBER working paper series -- working paper 17557; Working paper series (National Bureau of Economic Research : Online) -- working paper no. 17557.
Publisher: National Bureau of Economic Research
Published: 2011
Place of publication: Cambridge, MA
Language: eng
Format: Electronic resource
Description: "We explore the identification of nonseparable models without relying on the property that the model can be inverted in the econometric unobservables.  In particular, we allow for infinite dimensional unobservables.  In the context of a demand system, this allows each product to have multiple unobservables.  We identify the distribution of demand both unconditional and conditional on market observables, which allows us to identify several quantities of economic interest such as the (conditional and unconditional) distributions of elasticities and the distribution of price effects following a merger.  Our approach is based on a significant generalization of the linear in random coefficients model that only restricts the random functions to be analytic in the endogenous variables, which is satisfied by several standard demand models used in practice.  We assume an (unknown) countable support for the the distribution of the infinite dimensional unobservables"--National Bureau of Economic Research web site.
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