Exploratory analysis of young adults' trajectories through the UK driving license acquisition process

The UK is one of many high-income countries to experience a decline in driving license acquisition among young adults in the 2000s. This paper draws on newly available nationally representative microdata that captures the progress of individual drivers through the UK driving license acquisition process, to establish socio-demographic correlates.

Using the 2016 and 2017 editions of England's National Travel Survey data, a series of binary logit models were employed to identify factors associated with progression through the various phases of the UK's driving license acquisition process. Factors that are associated with (1) the frequency of taking the driving license tests, (2) the number of times having failed the theory and driving tests are then identified.

The socio-demographic explanators considered were each found to be associated with driving license holding in intuitive ways that are consistent with prior literature. However, relatively few factors are significantly associated with progress through the steps of the license acquisition process, and the goodness-of-fit for progress through these intermediate phases are generally lower (indicating that other unobservable idiosyncratic personal or contextual characteristics are dominant in these processes). A consistent theme is the strong relationship with labor market participation. Links between income and the intermediate phases, however, were generally weaker. Age is negatively associated with progress through the early phases when respondents are applying for provisional license and taking theory test, but this relationship turns positive in later stages of the acquisition process.

To the authors' knowledge, this study is the first opportunity to evaluate this novel data resource covering the UK's driving license acquisition process. This is an important research direction to help policymakers understand young adults' delay in acquiring licenses, particularly the extent to which there may be structural inequalities. The main finding is that socio-demographic factors appear to be relatively poor predictors, with employment status the strongest single correlate of the variables that were tested. This paper is concluded with suggestions for designers of household travel surveys in regions where youth license-acquisition is of increasing focus, as well as a brief discussion of future research needs.