The estimation of the value of travel time (VTT) plays an important role in demand models and appraisal. In most models, it is essential to recognise that the VTT is heterogeneous in the population. This may be across several dimensions, e.g. mode and income. It can be difficult to separate such mode and user type effects. In many empirical studies the combined effect of the two effects is that individuals in cars are seen to have higher VTT than for example in buses. The question is then if this happens becausethe mode choice of car raises VTT or because individuals with higher VTT choose car? If the latter is true then we have a self-selection problem and if this is not incorporated into the modelling then the VTT estimates may suffer from selection bias. Self-selection and selection bias is recognised as an important concern in transport modelling. In this study a model is formulated where mode choice is introduced as part of the VTT estimation to separate mode and user type effects. VTT is estimated taking the model choice into account through a selection model that reflects the way people become part of the sample. The model consists of two sub models. A mixed logit (ML) model used to estimate VTT as is standard practice and a selection model to estimate the way individuals self select into the sample. Here the model type is generalised to allow for correlation between the selection equation and the coefficients in the ML model. How to generalise the selection model using random probit was investigated. A different sampleis also used to see if the results are more general or merely sample specific. The model is then applied to a recent stated preference panel data set. Re-examination of the model served to strengthen the general knowledgeabout how self-selection affects transport modelling and in particular itdevelops a model to separate user type effects from mode effects in the estimation of VTT. For the covering abstract see ITRD E145999
Samenvatting