Semiparametric multinomial logit models for analysing consumer choice behaviour

Arbeitspapier

The multinomial logit model (MNL) is one of the most frequently used statistical models in marketing applications. It allows 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 proper scoring rules and compare parametric and semiparametric approaches for a number of brand choice data sets.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: Discussion Paper ; No. 501

Classification and Topics

• Subject: mixed models ; multinomial logit model ; brand choice ; penalised splines ; proper scoring rules ; semiparametric regression ; Markenartikel ; Konsumentenverhalten ; Logit-Modell ; Nichtparametrisches Verfahren ; Konsumtheorie

Contributors, Location and Time

• Event: Geistige Schöpfung
• (who): Kneib, Thomas ; Baumgartner, Bernhard ; Steiner, Winfried J.
• Event: Veröffentlichung
• (who): Ludwig-Maximilians-Universität München, Sonderforschungsbereich 386 - Statistische Analyse diskreter Strukturen
• (where): München
• (when): 2006

Further information

• DOI: doi:10.5282/ubm/epub.1866
• Handle: http://hdl.handle.net/10419/31083
• URN: urn:nbn:de:bvb:19-epub-1866-4
• Last update: 10.03.2025, 11:42 AM CET