Modeling methods for discrete choice analysis

Moshe Ben-Akiva*, Daniel Mcfadden, Makoto Abe, Ulf Böckenholt, Denis Bolduc, Dinesh Gopinath, Takayuki Morikawa, Venkatram Ramaswamy, Vithala Rao, David Revelt, Dan Steinberg

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

57 Scopus citations

Abstract

This paper introduces new forms, sampling and estimation approaches for discrete choice models. The new models include behavioral specifications of latent class choice models, multinomial probit, hybrid logit, and non-parametric methods. Recent contributions also include new specialized choice based sample designs that permit greater efficiency in data collection. Finally, the paper describes recent developments in the use of simulation methods for model estimation. These developments are designed to allow the applications of discrete choice models to a wider variety of discrete choice problems.

Original languageEnglish (US)
Pages (from-to)273-286
Number of pages14
JournalMarketing Letters
Volume8
Issue number3
DOIs
StatePublished - 1997

Keywords

  • Discrete choice models
  • Multinomial probit
  • Sample design
  • Simulation estimation

ASJC Scopus subject areas

  • Business and International Management
  • Economics and Econometrics
  • Marketing

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