Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/202389
Authors: 
Romeo, Charles J.
Year of Publication: 
2013
Series/Report no.: 
EAG Discussion Paper 10-3
Abstract: 
The random parameters logit model for aggregate data introduced by Berry, Levinsohn, and Pakes (1995) has been a driving force in empirical industrial organization for more than a decade. While these models are identified in theory, identification problems often occur in practice. In this paper we introduce the means of included demographics as a new set of readily available instruments that have the potential to substantially improve numerical performance in a variety of contexts. We use a set of endogenous price simulations to demonstrate that they are valid, and we use a real data illustration to demonstrate that they improve the numerical properties of the GMM objective function. In addition, we develop a metric that decomposes the explanatory power of the model into the proportion of market share variation that is explained by mean utility and that which is explained by the heterogeneity specification.
Subjects: 
random coefficients
instrumental variables
identification
GMM
Beer
JEL: 
C33
C35
L66
Document Type: 
Working Paper

Files in This Item:
File
Size





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.