PETRA - The COHORT model: PETRA working paper no. 5 - Jordal-Jørgensen, Jørgen; Fosgerau, Mogens (Proceedings from the Annual Transport Conference at Aalborg University, 1996)
This paper describes the COHORT model for licence holdings which forms part of the PETRA model complex. Licence holding at household level is described in the LICENCE model , based on cross-section data.However, cross-section analysis is not capable of accounting for all factors affecting future licence holding rates. In particular, long term effects arising from the difference in behaviour between generations cannot be seen on this basis. Therefore, the COHORT model is used to modify the forecasts from the LICENCE model in order to incorporate these effects. A predominant feature of licence holding is the slow market penetration that has occurred in the past and which is still taking place. The generation born in 1930 has, at all ages, had a significantly lower propensity to acquire a licence than later generations. For each age level, the propensity to acquire a licence, the entry rate, has been increasing with the coming of new generations. As the entry rates increase so do the licence holding rates. Today, the population consists of generations having had lower entry rates during their life than new generations have now. Thus, the licence holding rate today is lower than it will be when later genera- tions with higher entry rates replace the previous generations. It takes a lifetime for such effects to penetrate fully. For men, penetration is close to completion with almost 90% of adult men having a licence and a saturation level of about 98%. from 90% to 98% means that the prediction of future licence holding rates can be rather exact. Women lag somewhat behind. Today, licence holding rates are high for younger women and low for old women, resulting in an average licence holding rate of approximately 61% for women. Consequently, licence holding is going to increase in the future as the generations change, independ- ently of other factors. This has implications for the prediction of future car ownership and transport demand.