This thesis aims to understand the determinants of car ownership in the Swedish regions containing the largest cities: Skåne, Stockholm, and Västra Götaland. This is done by performing a fixed effects regression analysis as well as creating and comparing different predictive models. Both socioeconomic and spatial factors are looked at. The data used in the study is on a Demographic Statistic Zone level for the years 2016-2021. The data consists of approximately 90 variables that are narrowed down to 12 variables based on the level of existing multicollinearity, which are used in the final models. The results from the fixed effects regression show that variables such as population density, age, income, house owning type, and house type are the main influencers on car ownership. These results are similar for the specific regions; however, some differences are discovered, pointing out the disadvantages in creating a generalized model. The results of the predictive models shows that a Long Short-Term Memory model performs better than Random Forrest Regression and OLS, however the performance of the latter two models is considered satisfying enough making them superior as they are easier to interpret and more established within the industry. The region-specific predictive models perform equally well as the ones created from all the data. In conclusion, it can be said that the determinants of car ownership that are mentioned align well with the previous studies made and are considered reliable. Regarding which predictive model to use OLS should be considered sufficient even if more complex methods perform better.

L’automobile occupe une place fondamentale dans notre société, au point qu’on a pu parler de « civilisation de l’automobile ». En dépit des critiques qui lui sont régulièrement adressées, celle-ci n’a cessé de se renforcer, avec toujours davantage de voitures par adulte et une proportion croissante de déplacements effectués en voiture. Cependant, depuis le tournant du millénaire, on assiste à un retournement de tendance. Pour la première fois, la mobilité en voiture baisse dans les grandes agglomérations, tandis que la circulation automobile plafonne à l’échelle nationale. Cette évolution, du reste, n’est pas spécifique à la France mais s’observe dans l’ensemble des pays développés, une tendance parfois désignée sous le terme de « peak car (travel) ». Parmi les explications les plus convaincantes de ce retournement, figurent l’augmentation du prix du carburant, suivie de la récession de 2008. La volonté des ménages de maîtriser leurs budgets-temps de transport y contribue également, dans un contexte d’allongement des déplacements vers le travail et de dégradation des vitesses de déplacements. En outre, la diffusion de l’automobile se rapproche de la saturation. Si à long terme, la croissance du kilométrage moyen par adulte est indexée sur le taux de motorisation, cependant à moyen terme l’utilisation des véhicules fluctue en fonction du pouvoir d’achat énergétique, et un modèle basé sur ces deux variables suggère qu’on observerait une réaction normale à une augmentation exceptionnelle du prix du carburant. Les facteurs de croissance du taux de motorisation tiennent eux-mêmes principalement à la succession de générations de plus en plus motorisées, surtout chez les femmes, compte tenu d’un accès de plus en plus large au permis de conduire, à l’activité professionnelle, et d’une urbanisation de plus en plus diffuse, qui ont augmenté le besoin d’une seconde voiture. Pour modéliser l’auto-mobilité, on propose une approche emboîtée, individuelle et longitudinale, segmentée en fonction du genre. L’auto-mobilité peut en effet être vue au niveau individuel comme une succession de choix emboîtés, puisque la détention du permis conditionne l’accès à un véhicule personnel, de même que la motorisation conditionne l’usage d’un véhicule. L’avantage d’une approche longitudinale réside dans la possibilité de distinguer entre mesures d’hétérogénéité et de sensibilité, qui ne sont pas équivalentes. Pour chaque niveau de choix, l’approche est structurée autour d’une analyse de type âge-cohorte-période. Globalement, les taux de motorisation sont plus hétérogènes chez les femmes, un résultat qui est susceptible de recevoir une double interprétation, économique ou sociétale. On peut le voir en termes d’inégalités de genre. Mais il peut également s’interpréter comme le reflet d’un statut encore intermédiaire du second véhicule, dont l’opportunité serait davantage évaluée au regard des besoins et des contraintes réels du ménage. A l’inverse, l’usage des véhicules est à la fois plus élevé et plus hétérogène chez les hommes, compte tenu de la fonction collective du véhicule principal et des arbitrages internes aux ménages quant aux choix du lieu de résidence et des lieux de travail des conjoints. Pour finir, on estime à partir de modèles sur données de panel des effets marginaux et des élasticités par rapport au revenu, au prix du carburant et à la densité, qui sont ensuite comparées avec la littérature. Dans l’ensemble, les résultats sont cohérents avec l’analyse descriptive, ainsi qu’avec la littérature. Le modèle permet également de rendre compte du déclin tendanciel des élasticités, traduisant l’approche de la saturation. Pour finir, une évaluation a posteriori confirme l’opportunité d’une modélisation séquentielle, indiquant que les choix de motorisation sont indépendants des niveaux d’usage de la voiture. / Car ownership and use are a decisive part of our society, which was sometimes designed as the “civilization of the car”. Despite many critics, the car has become ever-more central in the modern way of life, with an ever-increasing number of cars per adult and proportion of trips realized by car. However, from the beginning of the millennium, there was a reversal in the trend towards ever-more car use. For the first time, the average number of daily trips realized by car has been falling down in French conurbations, and nationwide traffic by car is leveling off. This situation, nonetheless, is not specific to France but is common to many developed countries, and is often referred to as the “peak car (travel)”. The main explanations for such a downturn include rising fuel prices from the late 1990’s, followed by the recession in 2008, but also household’s willingness to control their travel time budgets, in a context of increasing commuting distances and reduced travel speeds. Besides, the diffusion of car ownership is approaching saturation. While on the long-run, average car travel per adult is indexed on motorization, mid-term fluctuations of average car use per vehicle are related to the energetic purchasing power, and a simple model based on these two variables is suggesting that the stagnation of car use from the 2000’s could be a reaction of a usual kind to an exceptional rise in fuel prices. The growth in motorization is itself principally caused by the follow-up of ever-more motorized generations, especially among women, given their increasing access to driving license, job participation and ever-more diffuse land use patterns, which have increased the need for a second car within households. In order to model auto-mobility, a nested, individual and longitudinal approach is implemented, segmented by gender. Auto-mobility can indeed be seen as a follow-up of nested choices, as driving license is necessary for holding a car, while access to a personal vehicle is itself required for car use. The advantage of a longitudinal approach consists in the ability to distinguish between measures of heterogeneity and sensitivity, which can be shown not to be equivalent. For every given level of choice, the approach is based on an age-cohort-period-type analysis. Motorization rates happen to be more heterogeneous among women, a result which is likely to receive an interpretation either of a social or economic nature. According to the first interpretation, it should be regarded as the illustration of gender inequalities. However, it could also be regarded as reflecting the still-intermediary status of the second vehicle, which opportunity is assessed depending upon household’s specific needs and constraints. On the contrary, car use is at the same time higher and more heterogeneous among men, given the collective function of the first vehicle and household’s internal trade-offs in residential and job choices. Finally, average partial effects and elasticities are estimated from panel data models, either with respect to income, fuel prices or density. Generally, results are consistent with the descriptive part, as with the literature. The model also rationally gives account of the decreasing trend for elasticities, which was often noticed in the literature and reflects the approach of saturation. As a conclusion, an a posteriori evaluation of the assumption of a sequential decision process is made, confirming that choices of motorization and car use are mutually independent.

The quest towards resolving concerns about transportation energy consumption and emissions across nations has created more interests to investigate factors responsible for households’ car ownership. While literature holds an extensive body of investigation usually compartmentalised in individual different disciplines, limited efforts have been made to promote inter-linkages of this strand of research across different disciplines. To fill this gap, this study developed an integrating Multinomial logit (MNL) model to examine the impact of some rarely-investigated and conventional explanatory variables, including: ethnicity, accommodation tenure, settlement nature, mental belief, environmental concern, geographical regions, household structure, driving licence, number of household income earners and household income, on car ownership. Analysis based on rich data sets of British Household Survey and US Consumer Expenditure Survey found not only the conventional explanatory variables to be significantly linked to the number of cars in the US and UK households, but also the rarely-investigated psychological variables were found to be significantly linked as well. As Socio-demography, Geography and Psychology impact on how people and households process information and assess market offers (e.g., products and services), this study presents findings which have beneficial implications for policymakers and transportations planners, including those who would like to alter people’s behaviour from private car ownership to public transportation use, car sellers in terms of how to identify and reach potential customers, provision of alternative forecasting approaches to car ownership scholars as well as possible consideration for general car ownership decision making. Caution should be taken when interpreting the relationship between psychological factors and car ownership since the psychological factors adopted are measure representatives from databases used with limitations in the factor structure for a representative sample of the countries’ population.