Estimating Values of Time on National travel survey data

The Value of Travel Time (VTT) is fundamental in transport economics. Since 1984 (MVA et al., 1984) best practice for VTT estimation has been to use Stated Choice (SC) data. However, there is now plenty of evidence of reference dependence and gain-loss asymmetry in SC data, implying that such data do not reveal long-term stable preferences. This is a serious problem since the value of time is often applied in welfare analyses, where long-term stability of the preferences is a key assumption. A potential reason for the strong reference dependence found in SC data is the emphasis on a short-term reference point often used in SC data to reduce hypothetical bias. In the long-run there is no stable reference point. Also, the use of Stated Choice data always raises the issue of the credibility of hypothetical responses. An alternative to SC data is to use revealed preference (RP) data and a mode choice model to estimate the VTT. Observed behaviour has adapted to the (more stable) travel conditions and should thus be ruled by more long-term preferences. Many countries collect NTS (national travel survey) data and spend considerable resources on making them representative, which is an argument for using them for VTT estimation. However, a key problem in the use of NTS data for VTT estimation is measurement errors in the travel time and travel cost variables. Time and cost in NTS data is either self-reported or derived from a network assignment model. In this paper we estimate the distribution of the VTT whilst controlling for errors in the self-reported and model computed time and cost variables.QC 20180828