Urban Sprawl and Household Car Traffic Growth in France: Projections to the Years 2010 to 2020
A Berri, J-L Madre, INRETS-DEST, FR
Keywords : Car traffic ; urban sprawl ; long term projections ; Age-Cohort-Period model.
High population density is likely to lower car ownership and use. Indeed, alternative transport modes are more widely available in high population density areas compared to less dense ones. Besides, congestion problems may lead to a restrained use of cars, either by users themselves or by specific policy measures. Such an influence on car ownership is clearly evidenced when considering homogeneous zones with respect to population density (Dargay et al., 2000).
In this paper, we analyse household annual car mileage in 10 French zones, defined by crossing the criterion of distance to centre with that of conurbation population size, of which one groups rural areas. Using data from repeated cross-sections of the annual INSEE Household Conjuncture Survey (1977-94), pseudo-panels are constructed according to the birth year of the household head (Deaton, 1985). Applying an Age-Cohort-Period model, estimates are made for age and cohort effects, along with income and price effects reflecting the general economic context faced by households during the period considered. This approach is advantageous in that it avoids imposing a priori saturation levels, it accounts for both economic and demographic factors (thus accounting for changes in the population structure and for the replacement of generations), and it uses reliable variables (demographic projections) for long term forecasts. The results show differences in behaviour between the zones, both through the effects of age and generation and through those of the economic variables considered (household final consumption and fuel prices). For instance, the elasticity with respect to final consumption increases as one goes from the city centre to the periphery of the conurbation. Thus, the future of urban sprawl is likely to have consequences as to the possibility of a decoupling of traffic and economic growth (Madre et al., 2002).
Relying on the estimated effects and on demographic projections (number of households by age of the head in each zone), we carry out projections of the car traffic generated by households for the years 2005, 2010, 2015 and 2020 according to three scenarios of urban sprawl, in addition to scenarios of growth of consumption and fuel prices. The scenarios of urban sprawl are defined on the basis of INSEE projections (OMPHALE model) for each zone, calibrated on the 1999 census results (for the total number of households). The results of the 1999 census in France confirm the tendency to urban sprawl : between 1990 (previous census) and 1999, the urban population knew a 5.5% growth, attributable for almost the half to the absorption of new municipalities (Chavouet et al., 2000). However, even if the classic scheme of urban sprawl (i.e., a growth rate increasing as we go away from the centre) remains dominant, it has been attenuated. Two other forms of urban development are in action : for some areas, population growth is greater in city-centres than in inner suburbs ; for others, on the contrary, it is greater in inner suburbs compared to city-centres or outer suburbs (Bessy-Pietri, 2000). As to rural areas, they knew a demographic renewal due to a migration contribution greater than the natural deficit in most of the municipalities (Bessy-Pietri et al., 2000). Thus, we consider a (High) scenario extending the tendency to urban sprawl observed from 1975 to 1990, an (Intermediate) scenario accounting for the inflexion observed between the censuses of 1990 and 1999, and a (Low) scenario fixing the spatial distribution of the population at its observed situation at the 1999 census (thus, assuming a stop in the urban sprawl process in 1999).
As one would expect, the projected volume of household car traffic should be more important if the sprawl process were to continue at its past pace (High scenario) than if it were to stop (Low scenario), the results for the Intermediate scenario lying between the two. The reverse holds (with small relative differences) in the case of predominantly rural zones, which is not surprising given their demographic renewal pointed out above and the definition of the scenarios. The gap between the two extreme scenarios widens with time. Though it remains modest at the national level (4% in 2020), this gap increases as the conurbation size decreases. The growth of car traffic between 1990 and 2020 should be larger the smaller is the population size of the conurbation. The 5-year growth rates are lower the farther the horizon of projection in each of the scenarios, and their levels diminish as one moves from the High scenario to the Low one. Globally, the traffic generated by inhabitants of city centres should be more important in the case of a stop of urban sprawl (Low scenario). On the contrary, the traffic generated by inhabitants of inner and outer suburbs should be more important if urban sprawl followed its past tendency (High scenario).
As regards the economic scenarios, the projections are more sensitive to variations in household final consumption than in fuel prices. The relative differences between the extreme hypotheses are at the national level of the order of 8% and 1% in 2020, respectively. By conurbation size, the smaller differences between scenarios of consumption growth are recorded by the Paris region and the larger ones by the predominantly rural zones ; the large conurbations (other than Paris) and the small ones show similar differences of intermediate magnitude. As to the gaps between hypotheses regarding the growth in fuel prices, they are small and vary little according to conurbation size.
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