In London, ownership has diverged from the national upward trend and stabilised, and, in some places, declined. Transport for London (TfL) required a better understanding of the reasons behind this trend, the variation across the conurbation, how demand for different vehicle types can be influenced by policy levers, and the implications for policy and decision-making in delivering desired environmental, economic and social outcomes.
We undertook three stages of econometric analysis to identify the best model for forecasting aggregate demand for cars, and market share for vehicle types:
- an exploratory study tested a suite of possible explanatory variables to explain car ownership at a spatially fine-grain level of detail;
- a full model development stage extended this to include time-series variables, such as costs, and delivered a flexible policy analysis tool to the client; and
- an extension incorporated a, nested logit, choice model to predict the market share for vehicle types by Vehicle Excise Duty (VED) band fuel type, and subsequent use.
Pre-existing forecasts of the market share for low emission vehicles made heavy use of supply side, production-led, forecasts. Our approach reversed this to a consumer, demand-led, model, with sensitivity to key explanatory variables such as monetary costs and supply side measures.
We delivered the final model to TfL to provide them with an analytical tool to support the Mayor’s Transport Strategy (MTS). By combining vehicle type and use data, the model allowed TfL to estimate CO2 emissions, and thus the contribution of different policy decisions to MTS goals and outcomes.