Show simple item record

dc.creatorBhat, Chandra R.en
dc.creatorAstroza, Sebastianen
dc.creatorSidharthan, Raghuprasaden
dc.creatorJobair Bin Alam, Mohammaden
dc.creatorKhushefati, Waleed H.en
dc.date.accessioned2013-08-19T21:01:23Zen
dc.date.available2013-08-19T21:01:23Zen
dc.date.issued2013-07en
dc.identifier.urihttp://hdl.handle.net/2152/21077en
dc.descriptionAt the time of publication Chandra R. Bhat, Sebastian Astroza, and Raghuprasad Sidharthan were at the University of Texas at Austin, and Mohammad Jobair Bin Alam and Waleed H. Khushefati were at King Abdulaziz University.en
dc.description.abstractThis paper formulates a multidimensional choice model system that is capable of handling multiple nominal variables, multiple count dependent variables, and multiple continuous dependent variables. The system takes the form of a treatment-outcome selection system with multiple treatments and multiple outcome variables. The Maximum Approximate Composite Marginal Likelihood (MACML) approach is proposed in estimation, and a simulation experiment is undertaken to evaluate the ability of the MACML method to recover the model parameters in such integrated systems. These experiments show that our estimation approach recovers the underlying parameters very well and is efficient from an econometric perspective. The parametric model system proposed in the paper is applied to an analysis of household-level decisions on residential location, motorized vehicle ownership, the number of daily motorized tours, the number of daily non-motorized tours, and the average distance for the motorized tours. The empirical analysis uses the NHTS 2009 data from the San Francisco Bay area. Model estimation results show that the choice dimensions considered in this paper are inter-related, both through direct observed structural relationships and through correlations across unobserved factors (error terms) affecting multiple choice dimensions. The significant presence of self-selection effects (endogeneity) suggests that modeling the various choice processes in an independent sequence of models is not reflective of the true relationships that exist across these choice dimensions, as also reinforced through the computation of treatment effects in the paper.en
dc.language.isoengen
dc.subjectmultivariate dependencyen
dc.subjectself-selectionen
dc.subjecttreatment effectsen
dc.subjectmaximum approximate composite marginal likelihooden
dc.subjectland-use and built environmenten
dc.subjecttravel behavioren
dc.titleA Joint Count-Continuous Model of Travel Behavior with Selection Based on a Multinomial Probit Residential Density Choice Modelen
dc.typeTechnical Reporten
dc.description.departmentCivil, Architectural, and Environmental Engineeringen


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record