This work is carried out by Statistics Netherlands in collaboration with the Netherlands Institute for Transport Policy Analysis (KiM)/Rijkswaterstaat as an extension to the trend series projects carried out in 2018-2022, in which time series multilevel models have been developed for estimating mobility trends. In the current extension, new data from the Dutch Travel Survey (DTS) over 2022 are added to the series, providing a fifth year of data under the new ODiN design of the DTS. This means there is more data on which estimates of the discontinuities associated with the latest redesign can be based. However, the mobility in 2020, 2021 and to a somewhat lesser extent also in 2022, was strongly influenced by the Covid-19 pandemic. For that reason, the model also includes Covid effects. The model has been updated to allow for different Covid effects for 2022 compared to those for 2021 and 2020.
We describe the updated models for the two target variables considered: the number of trip legs per person per day and the distance travelled per trip leg. The models are specified in a hierarchical Bayesian framework and estimated using a Markov Chain Monte Carlo simulation method. From the model outputs trend estimates are computed at various aggregation levels for the mean number of trip legs per person per day and the mean distance traveled per trip leg, as well as for derived quantities such as the mean distance per person per day. The model accounts for the discontinuities due to changes in measurement bias induced by various redesigns over the period between 1999-2023. The estimated trend series are benchmarked towards the measurement level of the latest (ODiN) design.
