A computationally fast estimator for random coefficients logit demand models using aggregate data.

This article proposes a computationally fast estimator for random coefficients logit demand models using aggregate data that Berry, Levinsohn, and Pakes (; hereinafter, BLP) suggest. Our method, which we call approximate BLP (ABLP), is based on a linear approximation of market share functions. The c...

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Detalles Bibliográficos

Publicado en:	RAND Journal of Economics (Wiley-Blackwell) Vol. 46; no. 1; pp. 86 - 103
Autores principales:	Lee, Jinhyuk, Seo, Kyoungwon
Formato:	Artículo
Publicado:	Wiley-Blackwell Spring2015
Materias:	Logits Biomathematics Logarithms Approximation theory Functional analysis
Acceso en línea:	Ver este registro en EBSCOhost