A Life Expectancy-Period-Cohort Model to project private car fleet and traffic - Applied to France

In most industrialized countries, after decades of gradually slowed growth, car traffic stagnated in the 2000s. This phenomenon has been attributed not only to conventional economic factors (stagnation of incomes, upward volatility in fuel prices) and to re-urbanization linked to metropolisation, but also to demographic factors (ageing of the population, longer life cycle stages leading in particular to delay the passage of the driving license in the younger generations). The economic recovery, albeit rather slow, and a significant drop in the price of oil in 2014 favored a certain revival of traffic growth in several countries (U.S.A., Germany, France, ...); but what about the structural factors and how to predict medium-term developments? We have already dealt with these questions via Age-Period-Cohort models, and more often Age-Cohorts. In view of the over-determination generated by the mechanical link between these three factors, we propose a Life Expectancy-Period-Cohort model (EPC), replacing age by life expectancy at this age and at each date makes it possible to directly estimate the model by keeping three components, while making the approach more consistent with the extension of life cycle stages (extension of studies, women having their children in their thirties, postponement of retirement age, ...). Period effects are specified by introducing the income of the household and a fuel price index as explanatory variables. We will compare the results with the various previous models. We consider the adult population (i.e., of driving age) and consider three phases for automobile behavior: - to pass the driver's license, - to be the main user of a vehicle, - to ride (annual mileage) or frequency of use of the vehicle. Once the models are estimated on the data of the Parc-Auto Kantar-SOFRES 1994-2015 (often 2016) panel survey, we treat an example of medium-term projection of the annual mileage knowing that in the long term the technical innovations (autonomous vehicle, electric and hybrid engines) and organizational (car sharing, carpooling, ...) are likely to fundamentally change the conditions of use of the car.