Fair and Intelligent Transport
Overview
Background & policy context:
The existing road tax regime was not originally intended as a transport policy tool, but rather as a means of generating tax revenue for the government. However road taxation could also serve as an effective transport policy tool that could help to direct the use of the transport system for greater efficiency, to reduce the negative externalities of traffic, and to finance the development and maintenance of the transport system. In other words it might be possible by means of economic regulation to influence the volume and quality of road traffic.
Objectives:
This report investigates the impacts that would result from an overhaul of passenger car taxation so that taxes would be based exclusively on car use. In practice this would mean substituting fixed taxes (the motor car tax and annual vehicle tax) with taxes based on kilometres driven. The kilometre tax would be a more flexible transport policy tool than the current tax system. It would also better serve the achievement of transport and environmental policy objectives than the existing tax regime. On the other hand the kilometre-based system would be less cost effective.
Methodology:
The impact assessment is based on the national strategic transport models developed in the Finnish Transport Agency’s methods development programme. The analyses of projected impacts are described in more detail in a separate report.
The impact assessments use computational models to provide broad and diverse
information about the kilometre tax system and its effects on individual passengers and the transport system as a whole. For this purpose two separate, mutually complementary assessment models have been developed: the individual model and the transport forecasting model. The individual model simulates the choices made by individual people in different parts of the country, while the transport forecasting model assesses the national impacts at the transport system level. The forecasting model therefore is effectively a change model that only predicts changes in the relative proportion of different modes of transport as a result of changes in transport supply and costs. This is the primary objective of the forecasting model because it is easy to change and analyse the model’s description of transport system especially in future scenarios. The individual model, then, is based on small grid cells, allowing local demand to be modelled with much greater accuracy. At the same time, however, it is much harder to provide a detailed description of transport systems. The two-model approach therefore effectively combines the strengths of different methods.
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