Kneib, Thomas and Baumgartner, Bernhard and Steiner, Winfried J. (2007) Semiparametric multinomial logit models for analysing consumer choice behaviour. ASTA-ADVANCES IN STATISTICAL ANALYSIS, 91 (3). pp. 225-244. ISSN 1863-8171,
Full text not available from this repository. (Request a copy)Abstract
The multinomial logit model (MNL) is one of the most frequently used statistical models in marketing applications. It allows one to relate an unordered categorical response variable, for example representing the choice of a brand, to a vector of covariates such as the price of the brand or variables characterising the consumer. In its classical form, all covariates enter in strictly parametric, linear form into the utility function of the MNL model. In this paper, we introduce semiparametric extensions, where smooth effects of continuous covariates are modelled by penalised splines. A mixed model representation of these penalised splines is employed to obtain estimates of the corresponding smoothing parameters, leading to a fully automated estimation procedure. To validate semiparametric models against parametric models, we utilise different scoring rules as well as predicted market share and compare parametric and semiparametric approaches for a number of brand choice data sets.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | STRUCTURED ADDITIVE REGRESSION; SPACE-TIME DATA; BRAND CHOICE; EMPIRICAL-ANALYSIS; PRICE; PURCHASE; SPLINES; brand choice; conditional logit model; mixed models; multinomial logit model; penalised splines; proper scoring rules; semiparametric regression |
| Subjects: | 600 Technology > 650 Management & auxiliary services |
| Divisions: | Business, Economics and Information Systems > Institut für Betriebswirtschaftslehre > Lehrstuhl für Marketing (Prof. Dr. Harald Hruschka) |
| Depositing User: | Dr. Gernot Deinzer |
| Date Deposited: | 11 Jan 2021 09:41 |
| Last Modified: | 11 Jan 2021 09:41 |
| URI: | https://pred.uni-regensburg.de/id/eprint/33338 |
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