Economics at your fingertips  

Bayesian estimation of mixed multinomial logit models: Advances and simulation-based evaluations

Prateek Bansal, Rico Krueger, Michel Bierlaire, Ricardo A. Daziano and Taha H. Rashidi

Transportation Research Part B: Methodological, 2020, vol. 131, issue C, 124-142

Abstract: Variational Bayes (VB) methods have emerged as a fast and computationally-efficient alternative to Markov chain Monte Carlo (MCMC) methods for scalable Bayesian estimation of mixed multinomial logit (MMNL) models. It has been established that VB is substantially faster than MCMC at practically no compromises in predictive accuracy. In this paper, we address two critical gaps concerning the usage and understanding of VB for MMNL. First, extant VB methods are limited to utility specifications involving only individual-specific taste parameters. Second, the finite-sample properties of VB estimators and the relative performance of VB, MCMC and maximum simulated likelihood estimation (MSLE) are not known. To address the former, this study extends several VB methods for MMNL to admit utility specifications including both fixed and random utility parameters. To address the latter, we conduct an extensive simulation-based evaluation to benchmark the extended VB methods against MCMC and MSLE in terms of estimation times, parameter recovery and predictive accuracy. The results suggest that all VB variants with the exception of the ones relying on an alternative variational lower bound constructed with the help of the modified Jensen’s inequality perform as well as MCMC and MSLE at prediction and parameter recovery. In particular, VB with nonconjugate variational message passing and the delta-method (VB-NCVMP-Δ) is up to 16 times faster than MCMC and MSLE. Thus, VB-NCVMP-Δ can be an attractive alternative to MCMC and MSLE for fast, scalable and accurate estimation of MMNL models.

Keywords: Variational bayes; Bayesian inference; Mixed logit; Nonconjugate variational message passing (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1) Track citations by RSS feed

Downloads: (external link)
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link:

Ordering information: This journal article can be ordered from
https://shop.elsevie ... _01_ooc_1&version=01

DOI: 10.1016/j.trb.2019.12.001

Access Statistics for this article

Transportation Research Part B: Methodological is currently edited by Fred Mannering

More articles in Transportation Research Part B: Methodological from Elsevier
Bibliographic data for series maintained by Catherine Liu ().

Page updated 2021-06-30
Handle: RePEc:eee:transb:v:131:y:2020:i:c:p:124-142