One of the main applications of discrete choice models in transportation research is the estimation of the value of travel time savings and other relevant willingness-to-pay (WTP) measures. Since WTP indicators are of great importance in transport appraisal it is crucial to avoid bias in the estimates. The newest methodology in estimation is based on mixed logit models, which allows for flexible representation of taste heterogeneity, but at the same time opens an array of pitfalls for the modeller. One of the pitfalls is to assume rigid correlation structures between coefficients based on convenience. Mabit and Nielsen (2006) investigated correlated WTP in public transport. In the conclusion they note that the investigation suffered from two important limitations: small sample size and few background variables. The primary objective of this paper is to overcome these two limitations using a new Danish 2004 data set. These data have a size that makes the investigation of correlated WTP possible for the different modes independently. Furthermore, the data contain a host of background variables so that their interaction with the correlation can be thoroughly investigated. The secondary objective of the study is to apply the newest developments within the mixed logit field in an applied model. Preliminary results show that only the access-egress and headway coefficients have significant mass points at zero. The remaining coefficients only have support on the negative half axis. Furthermore, the results show that the primary source of correlation between coefficients can be attributed to random scale in the sample. The data used contain the modes bus, s-train, metro, and train. They consist of binary stated preference observations with attributes cost, in-vehicle time, access-egress time, headway, wait time, and number of interchanges. There are 7751 observation for bus, 1855 observations for s-train, 876 observations for metro, and 3455 observations for train. For the covering abstract see ITRD E137145.
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