Estimating local car ownership models

Abstract

Many studies in the transport demand literature have shown that income is an important factor in determining how many cars a household owns. When the models used to measure the strength of this relationship are estimated on cross-sectional data, they typically yield one overall value as the estimate. Local circumstances will, however, vary. This paper illustrates the use of the Geographically Weighted Regression technique to estimate the individual strength of this relationship for each of the United Kingdom electoral wards. Use of this type of model enables a wards’ income elasticity to be based on both the local estimate of the strength of this relationship and the current local level of car ownership. How the use of this local elasticity changes future forecasts of the size of the vehicle fleet is illustrated.