The reform of the Flemish registration and annual road taxes. An ex post analysis of their impact on the CO2 emission factors of new cars

The Flemish Region in Belgium reformed its registration tax for passenger cars and its annual road tax in 2012 and 2016 respectively. We find that those reforms have caused an accelerated, but small, decrease in the CO2 emission factors of new cars sold in Flanders.

Description and use of the PLANET and CASMO models

This paper gives a non-technical description of the PLANET and CASMO models. The main results of the models are presented using the reference scenario for the costing exercise. Several policy scenarios and their results are also presented, for illustration purposes. 

Total cost of ownership of car powertrains in Belgium

We present a total cost of ownership (TCO) analysis per market segment and powertrain of new cars sold in Belgium. We differentiate our results between cars sold to private households and company cars. Even though the median TCO of electric cars is lower than the median TCO of conventional powertrains in several market segments, there is a significant overlap in the TCOs of different powertrains in each market segment. It is therefore important to consider the whole distribution of the TCO.

Ex ante evaluation of the reform of company car taxation in Belgium

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. 

Total cost of ownership of electric cars compared to diesel and gasoline cars in Belgium

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. 

Future evolution of the car stock in Belgium: CASMO, the new satellite of PLANET

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.

Perspectives de la demande de transport en Belgique à l’horizon 2040
Vooruitzichten van de transportvraag in België tegen 2040

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.

Description et utilisation du modèle PLANET
Beschrijving en gebruik van het PLANET-model

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.

Vehicle stock modelling in long term projections - Survey of the literature

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.