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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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Published in:RAND Journal of Economics (Wiley-Blackwell) Vol. 46; no. 1; pp. 86 - 103
Main Authors: Lee, Jinhyuk, Seo, Kyoungwon
Format: Article
Published: Wiley-Blackwell Spring2015
Subjects:
Logits
Biomathematics
Logarithms
Approximation theory
Functional analysis
Online Access:View this record in EBSCOhost