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Household structure and car ownership

Norway Flag
Complete with results
Geo-spatial type
STRIA Roadmaps
Vehicle design and manufacturing (VDM)
Transport mode
Road icon
Transport policies
Societal/Economic issues
Transport sectors
Passenger transport


Background & Policy context

From 1980 to 2001 the increase of the number of residents in Norway has been about 10%. In the same period the increase of the number of households is over 30%, and the number of privately owned cars has increased by over 50%. The number of persons per household has decreased by 15%, but the average number of cars per household has increased by 18%.

The tendency for the future is that the increase in the number of households will probably for some time be larger than the increase in the number of residents. Forecasts and assessments about future car ownership are mainly focused on the potential that multi-car ownership represents, and not on the force that the increasing number of households, and the decreasing household sizes represent.


The main objective of this study is to investigate to which extent the change in household structure has influenced the stock of cars in Norway, and the use of the cars.


First the historic situation will be studied. In this part of the study, data from the Norwegian 'Population and Housing Census' conducted in 1980, 1990 and 2001 (number of households of different types over time), and data from the 'National Travel Surveys' conducted in 1985, 1992, 1997 and 2001 (average car ownership and car use in different households over time) is combined. The data is divided into several categories in terms of urbanisation.

The second part of the study deals with the future development. A car ownership model system is used to forecast the future car accessibility in Norway. The result is divided into the same categories of urbanisation as the historic data.


Parent Programmes
Institution Type
Public institution
Institution Name
Ministry of Transport and Communications
Type of funding
Public (national/regional/local)


In the first part of the study, the change in the car stock is de-composed by household effects (keeping car ownership at a constant 1985 level) and "other" (socio-economic, i.e. changes in income, costs, etc.) effects leading to increased car ownership per household type (keeping the number of households in different categories at a constant 1985 level). The main conclusion is that increased car ownership per household gives the strongest influence on the overall car stock at an aggregate level (all households and urbanisation categories) in the period that was studied. From the early 90s however, the changes in household structure started to have an increased influence on the overall car stock.

In the largest cities the increase in the car stock is quite moderate compared with less urbanised categories, and the changes in household structure, seems to be the strongest influence factor, especially after 1990. The data is analysed with respect to different combinations of household types and urbanisation categories and the results are quite plausible. For some combinations the changes in the car stock is mainly driven by household effects and for other combinations the socio-economic influence is greater. For the "single adult household" category the development has been quite extreme (28 % of the households in 1980, and 38 % in 2001). The car stock in these households has doubled nationwide from 1985 to 2001, but the increase has been more moderate in the largest cities.

The use of the cars in terms of vehicle-km has increased by 60 % in Norway from 1985 to 2001, but only 27 % in the largest cities. Households without children produce 40 % of the vehicle km in 2001 (32 % in 1985), and the "couple with children" household type produce 39 % (52 % in 1985).

In the second part of the study a model system was used to forecast future car accessibility. Compared to the first part of the study the model has at least one weakness that need to be pointed out. The model system takes population forecasts for future years as exogenous data, and keeps the distribution of the population on household types at a fixed 2001 level. As the population forecast changes the distribution on age and gender the number of residents in different households categories will change in the model system, but not nearly as much as we have seen the recent decades in Norway.

The model calculations show however, that changes in the demographic structure will be the single most important drivin

Policy implications



Lead Organisation
EU Contribution
Partner Organisations
EU Contribution


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