BROWSE

Related Researcher

Author's Photo

Lee, Jin Hyuk
School of Business Administration
Research Interests
  • Industrial Organization
  • Applied Microeconomics
  • Applied Econometrics

ITEM VIEW & DOWNLOAD

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

DC Field Value Language
dc.contributor.author Lee, Jin Hyuk ko
dc.contributor.author Seo, Kyoungwon ko
dc.date.available 2015-03-16T00:09:21Z -
dc.date.created 2015-03-11 ko
dc.date.issued 2015-03 ko
dc.identifier.citation RAND JOURNAL OF ECONOMICS, v.46, no.1, pp.86 - 102 ko
dc.identifier.issn 0741-6261 ko
dc.identifier.uri https://scholarworks.unist.ac.kr/handle/201301/10846 -
dc.description.abstract 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 computational advantages of ABLP include (i) the linear approximation enables us to adopt an analytic inversion of the market share equations instead of a numerical inversion that BLP propose, (ii) ABLP solves the market share equations only at the optimum, and (iii) it minimizes over a typically small dimensional parameter space. We show that the ABLP estimator is equivalent to the BLP estimator in large data sets. Our Monte Carlo experiments illustrate that ABLP is faster than other approaches, especially for large data sets ko
dc.description.statementofresponsibility close -
dc.language 영어 ko
dc.publisher WILEY-BLACKWELL ko
dc.title A computationally fast estimator for random coefficients logit demand models using aggregate data ko
dc.type ARTICLE ko
dc.identifier.scopusid 2-s2.0-84922515501 ko
dc.identifier.wosid 000349031000004 ko
dc.type.rims ART ko
dc.description.wostc 0 *
dc.description.scopustc 0 *
dc.date.tcdate 2015-03-11 *
dc.date.scptcdate 2015-11-04 *
dc.date.scptcdate 2015-11-04 *
dc.identifier.doi 10.1111/1756-2171.12078 ko
dc.identifier.url http://onlinelibrary.wiley.com/doi/10.1111/1756-2171.12078/abstract;jsessionid=CD12F6673E797C6D3F027065E160EEFB.f04t04 ko
Appears in Collections:
SBA_Journal Papers
Files in This Item:
There are no files associated with this item.

find_unist can give you direct access to the published full text of this article. (UNISTARs only)

Show simple item record

qrcode

  • mendeley

    citeulike

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

MENU