Investigating the competitive assumptions of multinomial logit models for brand choice by nonparametric modelling
type: Item
instance of: scholarly article
title: Investigating the competitive assumptions of multinomial logit models for brand choice by nonparametric modelling
zbMATH Open document ID: 1063.62101
DOI: 10.1007/BF02753916
author: Makoto Abe
author: Lutz Hildebrandt
author: Yasemin Boztuğ
published in: Computational Statistics
publication date: 2005-05-20T00:00:00Z
review text: The goal of this paper is to investigate explicitly whether the multinomial logit model (MNL) structure of inter-brand competition is a reasonable assumption so that its nonparametric relaxation is not warranted when the utility function is estimated nonparametrically. For this purpose, the authors compare the performance of two comparable nonparametric choice models that differ in one aspect: one assumes an MNL competitive structure and the other infers the pattern of brands' competition nonparametrically from the data. Results of a simulation study are presented and application of both models to German scanner panel data of brand choice in a health care product category are discussed.
Mathematics Subject Classification ID: 62J12
Mathematics Subject Classification ID: 90B60
Mathematics Subject Classification ID: 62P99
Mathematics Subject Classification ID: 65C05
zbMATH DE Number: 2169430
zbMATH Keywords: nonparametric modelling
zbMATH Keywords: generalised additive model
zbMATH Keywords: brand choice
zbMATH Keywords: multinomial logit model
zbMATH Keywords: panel data
zbMATH Keywords: utility function
describes a project that uses: R
describes a project that uses: S-PLUS
MaRDI profile type: Publication
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full work available at URL: https://doi.org/10.1007/bf02753916
OpenAlex ID: W2080230678
description: scientific article; zbMATH DE number 2169430