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The Federal Planning Bureau (FPB) is an independent public agency. It draws up studies and projections on economic, social and environmental policy issues and on the integration of these policies within a context of sustainable development.
Laurent Franckx is an economist specializing in transport and environmental economics. He obtained his PHD at the KULeuven in 2001. Before joining the Federal Planning Bureau in 2017, he has been a consultant on Belgian and European policy studies.
As a member of the Energy and Transport team, he is mainly responsible for modelling the car fleet composition, and in particular the share of alternative fuels. Besides, he studies the impact of new technological developments (such as self-driving cars) and transportation business models (such as shared mobility) on transport demand in Belgium, and on the attractiveness of the various modes of transport.
In Belgium, the Law on Fiscal and Social Greening of Mobility of 25 November 2021 eliminates corporate tax deductibility for all company cars except those with zero CO2 emissions. The main effect of the tax reform is an accelerated electrification of the company car fleet and an accelerated decline in CO2 emissions. Compared to the no-reform scenario, the reform leads to an increase in net tax revenues of about 1 billion euro on an annual basis.
While automated car driving may bring important benefits in terms of traffic safety, we should not be blind to other effects: full automation is likely to lead to increases in car traffic, mostly for transport that is not related to commuting. This is likely lead to further reductions in road speed in the areas that already suffer the most from the congestion.
A policy mix of “stick” measures (generalised distance based road charge) and “carrot” measures (supporting carpooling) could induce an increase in the occupation rate of cars in Belgium from 1.44 to 1.50. This relatively modest increase can be explained by the relatively small share of trips for which an increase in the occupation rate is a realistic option, and by the inconveniences linked to the organisation of carpooling. Nevertheless, this policy mix can induce a notable improvement in the traffic situation during the peak periods in the regions that currently suffer the most from congestion.
We compare the TCO of fully electric cars (BEV) with those of diesel and gasoline cars. In the size class “small”, BEV only have a lower TCO for an expected lifetime that exceeds most estimates of the planning horizon people use when purchasing cars. In the size class “medium”, BEVs have a lower TCO than conventional cars if their expected lifetime mileage is high enough. “Big” electric cars have higher TCO than their conventional counterparts for any reasonable assumption regarding their use profiles.
The new Belgian CAr Stock MOdel, which is linked to the national transport demand model PLANET, is structured as follows: (a) The total desired car stock in each future year is a function of the country’s population and GDP per capita. (b) The probability that a car is scrapped is modelled as a function of its age and accumulated mileage. The desired car stock is then confronted with the remaining car stock to determine total car purchases. (c) Total sales are allocated to individual emission classes, using the parameter values of a Stated Preference discrete choice model. The model is then calibrated in order to reflect the current market and policy context in Belgium (d) The results are mapped into an inventory that is aggregated according to the EURO emission class. (e) In order to represent that the non-price barriers to electrified cars will decrease over time, we have implemented an alternative approach where the perceived acquisition costs decrease over time. Alternatively, this approach can be used to explore what would be the required decrease in subjective costs to reach a given future market share.
Within the framework of a cooperation agreement between the Federal Planning Bureau and the Federal Public Service Mobility and Transport, the Federal Planning Bureau produces, every three years, long-term projections of transport demand in Belgium. This exercise is the fourth of its kind so far. It aims to make a projection of no change in policy, indicating general long-term trends and allowing elements on which transport policy should be based to be identified and the impact of transport policy measures to be studied.
Deze paper geeft een niet-technische beschrijving van het PLANET-model, met een focus op beleidsanalyse in de transportsector. De werking van de verschillende modules, alsook van de belangrijkste gedragseffecten, modeldimensies en beleidsvariabelen wordt gepresenteerd. Er wordt ingegaan op een aantal specifieke gevallen die belangrijk zouden kunnen zijn voor de doorrekening van de verkiezingsprogramma’s, met name de behandeling van de fiscale uitgaven voor transport in de directe belastingen en de invoering van een geografische dimensie. Tot slot geven we de resultaten van enkele illustratieve beleidsscenario’s.
Le présent working paper donne une description non technique du modèle PLANET et met l’accent sur l’analyse de mesures dans le secteur du transport. Le fonctionnement des différents modules sont présentés, tout comme les principaux effets sur le comportement, les dimensions du modèle et les variables de mesures politiques. Cette présentation aborde un certain nombre de spécificités qui pourraient être importantes pour le chiffrage des programmes électoraux, notamment le traitement des dépenses fiscales de transport au niveau des impôts directs et l’introduction d’une dimension géographique. Enfin, plusieurs scénarios de politique et leurs résultats sont présentés à titre d’illustration.
Transport models used for long-term projections should reflect the impact of shared, automated and electric mobility modes. The objective of the current paper is to derive lessons from the existing literature on vehicle ownership modelling to find options to further improve the PLANET model, which is used for projections of transport demand in Belgium.
PLANET is already well equipped to represent the impacts of shared and automated cars on the opportunity cost of travel time, the load factors and the annual mileage of cars.
Federal Planning Bureau
