The Dutch national car park model SPARK
The Dutch national car park model SPARK was developed by Significance in 2021 and 2022. It is a new forecasting tool to estimate the size and composition of the passenger car fleet at the national level for different scenarios and various (fiscal) policy measures.
Objectives
| SPARK is a new forecasting tool to estimate the size and composition of the passenger car fleet at the national level for different scenarios and various (fiscal) policy measures and to provide input for the National Model System (LMS) for passenger transport. |
| SPARK was commissioned by the Dutch Ministry of Infrastructure and Water Management and the Netherlands Environmental Assessment Agency (PBL) and developed by Significance with Demis. It aims to provide national level forecasts under various scenarios, for the short, intermediate and long term (up to 2060). The aim of this model is not only to replace the various currently used car ownership models, but also to be able to incorporate emerging trends such as the rapid uptake of electric vehicles or private lease. |
Model components
| SPARK contains the following submodules: |
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| • A dynamic household simulator to generate the input variables on households and persons (e.g. income, age, occupation) from year to year into the future;. |
| • Dynamic transaction models for forecasting changes in the number of passenger cars per household in a year (+1, -1, replace, no change). |
| • Negative binomial regression models to forecast the annual number of vehicle kilometres driven (and also the corresponding emissions). |
| • Discrete choice models to forecast car type choice: petrol/diesel/battery electric/plugin hybrid, market segment (size), brand group, vintage, imported or not; These choice models are combined with diffusion curves for the likely penetration over time electric cars. |
Model use: inputs and outputs
After the estimation of the SPARK submodels, the model was implemented in Python and recalibrated to observed data for the base situation at 31 December 2018 and the actual transitions during 2019.
SPARK can be used to simulate the impact of different demographic and socio-economic scenarios and for doing runs for changes in key input variables relevant to policy makers (keeping everything else constant). Examples of these are a ban on the purchase of new fossil cars, changes in purchase tax, road tax, subsidies on the purchase of battery electric cars, fuel tax and distance-based road user charging.
The outputs of SPARK consist of: the number of passenger cars in the short and long term, the number of kilometres travelled in a year (and corresponding emissions), and the distribution of the new sales and the car fleet by, for example, car market segment (A-E) and energy source (petrol, diesel, LPG, battery electric, plugin hybrid). Outcomes for different segments of the population (e.g. by region or income band) are also possible, as are results for the revenues from car taxes of the government.
