EconPapers    
Economics at your fingertips  
 

An Expectation-Maximization Algorithm to Estimate the Integrated Choice and Latent Variable Model

Keemin Sohn ()
Additional contact information
Keemin Sohn: Department of Urban Engineering, Chung-Ang University, Seoul 156-756, Korea

Transportation Science, 2017, vol. 51, issue 3, 946-967

Abstract: As computing capability has grown dramatically, the transport choice model has rigorously included latent variables. However, integrated latent and choice variable (ICLV) models are hampered by a serious problem that is caused by the maximum simulated likelihood method. The method cannot properly reproduce the true coefficients, which is a problem that is often referred to as a lack of empirical identification. In particular, the problem is exacerbated particularly when an ICLV model is calibrated based on cross-sectional data. An expectation-maximization (EM) algorithm has been successfully employed to calibrate a random coefficient choice model, but it has never been applied to the calibration of an ICLV model. In this study, an EM algorithm was adapted to calibrate an ICLV model, and it successfully reproduced the true coefficients in the model. The main contribution of adopting an EM algorithm was to simplify the calibration procedure by decomposing the procedure into three well known econometric problems: a weighted linear regression, a weighted discrete choice problem, and a weighted ordinal choice problem. Simulation experiments also confirmed that an EM algorithm is a stable method for averting the problem of lack of empirical identification.

Keywords: choice model; latent variable; simulated maximum likelihood; expectation-maximization (EM) algorithm (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

Downloads: (external link)
https://doi.org/10.287/trsc.2016.0696 (application/pdf)

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: https://EconPapers.repec.org/RePEc:inm:ortrsc:v:51:y:2017:i:3:p:946-967

Access Statistics for this article

More articles in Transportation Science from INFORMS Contact information at EDIRC.
Bibliographic data for series maintained by Chris Asher ().

 
Page updated 2025-03-19
Handle: RePEc:inm:ortrsc:v:51:y:2017:i:3:p:946-967