A new estimation approach for the multiple discrete–continuous probit (MDCP) choice model
This paper develops a blueprint (complete with matrix notation) to apply Bhat’s (2011) Maximum Approximate Composite Marginal Likelihood (MACML) inference approach for the estimation of cross-sectional as well as panel multiple discrete–continuous probit (MDCP) models. A simulation exercise is undertaken to evaluate the ability of the proposed approach to recover parameters from a cross-sectional MDCP model. The results show that the MACML approach does very well in recovering parameters, as well as appears to accurately capture the curvature of the Hessian of the log-likelihood function. The paper also demonstrates the application of the proposed approach through a study of individuals’ recreational (i.e., long distance leisure) choice among alternative destination locations and the number of trips to each recreational destination location, using data drawn from the 2004 to 2005 Michigan statewide household travel survey.
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/issn/01912615
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Supplemental Notes:
- Abstract reprinted with permission from Elsevier.
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Authors:
- Bhat, Chandra R
- Castro, Marisol
- Khan, Mubassira
- Publication Date: 2013-9
Language
- English
Media Info
- Media Type: Digital/other
- Features: References; Tables;
- Pagination: pp 1-22
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Serial:
- Transportation Research Part B: Methodological
- Volume: 55
- Issue Number: 0
- Publisher: Elsevier
- ISSN: 0191-2615
- Serial URL: http://www.sciencedirect.com/science/journal/01912615
Subject/Index Terms
- TRT Terms: Estimation theory; Probits; Recreational trips; Travel surveys
- Uncontrolled Terms: Discrete-continuous models; Log-likelihood estimation
- Geographic Terms: Michigan
- Subject Areas: Highways; Planning and Forecasting; I71: Traffic Theory;
Filing Info
- Accession Number: 01493708
- Record Type: Publication
- Files: TRIS
- Created Date: Sep 20 2013 4:31PM