Comparison of car ownership models

Car ownership models found in the academic literature (with a focus on the recent literature and on models developed for transport planning) are classified into a number of model types. The different model types are compared on a number of criteria: inclusion of demand and supply side of the car market, level of aggregation, dynamic or static model, long‐ or short‐run forecasts, theoretical background, inclusion of car use, data requirements, treatment of business cars, car‐type segmentation, inclusion of income, of fixed and/or variable car cost, of car quality aspects, of licence holding, of sociodemographic variables and of attitudinal variables, and treatment of scrappage.     

Modelling car ownership in Great Britain

Over the last 50 years there has been a tenfold increase in the number of cars in Great Britain, rising from 2.6 million vehicles in 1951 to 27 million vehicles in 2001. Over the same period there has been a steady reduction in the proportion of households without access to a car and a steady increase in the proportion of households with two or more cars. If such trends continue, it is likely that there will be increased energy consumption, increased problems with traffic congestion and atmospheric pollution, and reductions to the financial viability of public transport. Given the importance of car ownership to transport and land-use planning and its relationship with energy consumption, the environment and health, it is the objective of this research to develop econometric models of household car ownership and apply the models to generate forecasts across Britain to the year 2031. To achieve this objective, the research develops discrete choice models of the household’s decision to own zero, one, two or three or more vehicles as a function of market saturation, licence holding, household income and structure, household employment, company car provision, and purchase and use costs. The models are validated to data from the 2001 Census and are used to develop a range of forecasts taking into account changes to the socio-demographic characteristics of Britain.     

A repeated cross-sectional evaluation of car ownership

This paper studies changes in the relationship between household car ownership and income by household type. Ordered response probit models of car ownership are estimated for a sample of households repeatedly at six time points to track the evolution of income elasticities of car ownership over time. Elasticities of car ownership are found to change over time, questioning the existence of a unique equilibrium point between demand and supply that is implicitly assumed in traditional cross-sectional discrete choice car ownership models. Moreover, different household types and households that underwent household type transitions showed differing patterns of change in elasticities. Observed trends in car ownership and income clearly show behavioral asymmetry where the elasticity of procuring an additional car is greater than that of disposing a car. This too shows the inadequacy of traditional cross-sectional models of car ownership which tend to predict symmetry in behavior. The study suggests the importance of incorporating dynamic trends into the forecasting process, which can be accomplished through the use of longitudinal data.     

A dynamic analysis of household car ownership

This paper examines the determinants of household car ownership, using Irish longitudinal data for the period 1995–2001. This was a period of rapid economic and social change in Ireland, with the proportion of households with one or more cars growing from 74.6% to 80.8%. Understanding the determinants of household car ownership, a key determinant of household travel behaviour more generally, is particularly important in the context of current policy developments which seek to encourage more sustainable means of travel. In this paper, we use longitudinal data to estimate dynamic models of household car ownership, controlling for unobserved heterogeneity and state dependence. We find income and previous car ownership to be the strongest determinants of differences in household car ownership, with the effect of permanent income having a stronger and more significant effect on the probability of household car ownership than current income. In addition, income elasticities differ by previous car ownership status, with income elasticities higher for those households with no car in the initial period. Other important influences include household composition (in particular, the presence of young children) and lifecycle effects, which create challenges for policymakers in seeking to change travel behaviour.     

A causal analysis of car ownership and transit use

The causal structure underlying household mobility is examined in this study using a sample obtained from the Dutch National Mobility Panel survey. The results indicate that car ownership is strongly associated with mode use, but that it has no influence on weekly person trip generation by household members. Characteristics of mode use are examined through a causal analysis of changes in car ownership, number of drivers, number of car trips, and number of transit trips. It is shown that observed changes in mode use cannot be adequately explained by assuming that a change in transit use influences car use. The finding suggests that the increase in car use, which is a consequence of increasing car ownership, may not be suppressed by improving public transit.     

Disaggregate and aggregate car ownership forecasting in Great Britain

The first part of this paper argues that the variable ‘cars per household’, as well as the proportion of households owning more than a given number of cars, should be modelled by sigmoid functions with finite saturation levels. Next, a summary and critique of the work of the Regional Highway Traffic Model, group is presented. Problems relating to choice of functional form, interaction of effects, and the usefulness of the explanatory variable ‘Car Purchasing Income’ are discussed.This leads to an analysis of the concept of a saturation level, with a caution against using external data to determine it when the true functional form of the car ownership growth path is unknown. Following this, Transport and Road Research Laboratory work is discussed and its limitations highlighted. Data for the period 1953–1974 is reworked yielding the conclusion that there is no evidence that growth in this period has been non-logistic. This implies that previous overpredictions by TRRL were due to incorrect parameter estimates, rather than the choice of the wrong model form.     

Factors of development of car ownership in Poland

The paper aims (1) to confront the spatial distribution and dynamics of car ownership in Poland with the experiences of the development of private car ownership in other Central and Western European countries; (2) to analyse the phenomenon considered at the regional level, also with respect to its causes and consequences; and (3) to attempt to answer the question whether in the circumstances of the post-socialist countries the development of private car ownership is conditioned by the same factors as those defined in earlier analyses, mainly on the basis of the experiences from developed countries.     

Changes in private car ownership associated with car sharing: gauging differences by residential location and car share typology

Transportation - While a large body of literature shows that car share encourages low car ownership, the evidence is rather limited in the context of different types of car share (fleet-based...     

A panel data switching regression model of mobility and car ownership

The objective of this paper is to present a panel data model of car ownership and mobility. Unobserved heterogeneity is controlled for by including correlated random effects in the equations describing car ownership and mobility. A mass-points approach is adopted to control for unobserved heterogeneity. The results show that decisions concerning the first car in the household are difficult to affect; a large number of households are inclined to keep one car. Second car ownership may be more sensitive to changes in the observed contributing factors. This suggests that in The Netherlands policies aimed at changing second car ownership will be more successful than those aimed at influencing decisions concerning the first car in households. A major part of the correlation between the unobservables in the car ownership and the mobility equations is attributable to random effects. The time-variant errors of the mobility equations are not significantly correlated to car ownership decisions. This implies that mobility can only be influenced to a small extent by policy makers without measures aimed at reducing (second) car ownership.     

Maximum car ownership under constraints of road capacity and parking space

This paper presents a model for determining the maximum number of cars by zones in view of the capacity of the road network and the number of parking spaces available. In other words, the proposed model is to examine whether existing road network and parking supply is capable of accommodating future zonal car ownership growth (or the reserve capacity in each zone); i.e. the potential maximum zonal car ownership growth that generates the road traffic within the network capacity and parking space constraints. In the proposed model, the vehicular trip production and attraction are dependent on the car ownership, available parking spaces and the accessibility measures by traffic zones. The model is formulated as a bi-level programming problem. The lower-level problem is an equilibrium trip distribution/assignment problem, while the upper-level problem is to maximize the sum of zonal car ownership by considering travellers’ route and destination choice behaviour and satisfying the network capacity and parking space constraints. A sensitivity analysis based heuristic algorithm is developed to solve the proposed bi-level car ownership problem and is illustrated with a numerical example.     

The dynamics of household travel time expenditures and car ownership decisions

A dynamic (panel data) structural equations model is developed that links four dependent travel behavior variables at two points in time, one year apart. The four dependent variables are: car ownership, travel time per week by car, travel time by public transit, and travel time by nonmotorized modes. Exogenous variables include 13 household characteristics and variables accounting for period effects over the 1985 to 1987 time frame in the Netherlands. The model treats car ownership as ordered-response probit variables and all travel times as censored (tobit) continuous variables. The model accounts for serially-correlated errors and panel conditioning biases. Results are interpreted in terms of recommendations for forecasting procedures.     

Characterising group-cycling journeys using interactive graphics

The group-cycling behaviours of over 16,000 members of the London Cycle Hire Scheme (LCHS), a large public bikeshare system, are identified and analysed. Group journeys are defined as trips made by two or more cyclists together in space and time. Detailed insights into group-cycling behaviour are generated using specifically designed visualization software. We find that in many respects group-cycle journeys fit an expected pattern of discretionary activity: group journeys are more likely at weekends, late evenings and lunchtimes; they generally take place within more pleasant parts of the city; and between individuals apparently known to each other. A separate set of group activity is found, however, that coincides with commuting peaks and that appears to be imposed onto LCHS users by the scheme’s design. Studying the characteristics of individuals making group journeys, we identify a group of less experienced LCHS cyclists that appear to make more spatially extensive journeys than they would do normally while cycling with others; and that female cyclists are more likely to make late evening journeys when cycling in groups. For 20% of group cyclists, the first journey ever made through the LCHS was a group journey; this is particularly surprising since just 9% of all group cyclists’ journeys are group journeys. Moreover, we find that women are very significantly (p < 0.001) overrepresented amongst these ‘first time group cyclists’. Studying the bikeshare cyclists, or bike share ‘friends’, that individuals make ‘first time group journeys’ with, we find a significantly high incidence (p < 0.001) of group journeys being made with friends of the opposite gender, and for a very large proportion (55%) of members these first ever journeys are made with a friend that shares the same postcode. A substantial insight, then, is that group cycling appears to be a means through which early LCHS usage is initiated.     

Volatility of car ownership, commuting mode and time in the UK

This paper has two objectives: to examine the volatility of travel behaviour over time and consider the factors explaining this volatility; and to estimate the factors determining car ownership and commuting by car. The analysis is based on observations of individuals and households over a period of up to 11 years obtained from the British Household Panel Survey (BHPS). Changes in car ownership, commuting mode and commuting time over a period of years for the same individuals/households are examined to determine the extent to which these change from year-to-year. This volatility of individual behaviour is a measure of the ease of change or adaptation. If behaviour changes easily, policy measures are likely to have a stronger and more rapid effect than if there is more resistance to change. The changes are “explained” in terms of factors such as moving house, changing job and employment status. The factors determining car ownership and commuting by car are analysed using a dynamic panel-data models.     

Carsharing: the impact of system characteristics on its potential to replace private car trips and reduce car ownership

Transportation - This paper aims to explore the potential of carsharing in replacing private car trips and reducing car ownership and how this is affected by its attributes. To that affect, a...     

The residential parking rent price elasticity of car ownership in Japan

By using household-level micro data captured through the National Survey of Family Income and Expenditure for 2004, this study evaluates the residential parking rent price elasticity of car ownership in Japan. It analyzes the number of cars owned by a household, using various attributes including expenditure for renting a parking space on a monthly basis. The estimation results derived from the IV-ordered probit model show that the absolute value of parking rent price elasticity of car ownership is, at most, 0.48, which is fairly small (i.e., inelastic). The elasticity value varies depending on city size; for megacities, elasticity is always negative for car ownership, whereas for middle-sized or small cities, towns, and villages, elasticity is positive for one-car ownership and negative for the ownership of more than one car. Hence, when the price of parking increases, some people may switch from more than one car to one car and some people in megacities may switch from one to zero cars. Indeed, the net effect of a price increase may be that non-car ownership increases in megacities and one-car ownership increases in other cities.     

The effect of income on car ownership: evidence of asymmetry

This paper examines the effect of income on car ownership, and specifically the question of hysteresis or asymmetry. Although there is little doubt that rising income leads to higher car ownership, less is understood about the effect of falling income. Traditional demand modelling is based on the implicit assumption that demand responds symmetrically to rising and falling income. The object of this study is to test this assumption statistically. Using a dynamic econometric model relating household car ownership to income, the number of adults and children in the household, car prices and lagged car ownership, income decomposition techniques are employed to separately estimate elasticities with respect to rising and falling income. The equality of these elasticities – no hysteresis – is tested statistically against the inequality – hysteresis – hypothesis. Various functional specifications are tested in order to assure the robustness of the results to assumptions concerning functional form. The estimation is based on cohort data constructed from 1970 to 1995 UK Family Expenditure Surveys, and a pseudo-panel methodology is employed. The results indicate that car ownership responds more strongly to rising than to falling income – there is a ‘stickiness’ in the downward direction. In addition, there is evidence that the income elasticity is not constant, but instead declines with increasing car ownership.     

The role of individual characteristics in car ownership shortly after relationship dissolution

The dissolution of a relationship is a life event that often coincides with many other changes in life, such as a decline in income level or household size or a change in place of residence. This study aims to provide more insight into the ways in which circumstances shortly following the disruption of a relationship affect travel behaviour. Register data that combines information on the Dutch population, income and vehicle registration are used to understand how personal situations that are closely related to relationship disruption affect car ownership. The study shows that several characteristics of singles and single partners shortly after a breakup negatively affect car ownership. For instance, a relatively low income level, unemployment, living in a city or a residential move all affect car ownership negatively. This study focuses on the role of circumstances shortly after relationship disruption, demonstrating the importance of such an event.     

Modeling car ownership and use in a developing country context with informal public transportation

Transportation - Car ownership and use is a main contributor to the deterioration of air quality in cities and to global warming. There is thus a pressing need to understand their determinants in...     

The determinants of car ownership in England and Wales from anonymous 2001 census data

Within the transportation research literature, the attempt to understand and predict the level of car ownership is probably one of the most popular areas of study. The primary reason for this is understandable, having access to a vehicle increases an individual’s (or their household’s) travel options, leading to greater mobility. Secondary reasons for this scrutiny include the need to predict future transport investment in road infrastructure and the commercial demand for new vehicles. This paper attempts to predict the level of household car ownership as a function of the characteristics of the household and the individuals that make up the household. The primary data source for this study comes from the 2001 United Kingdom Census and the analysis methods used are from the discipline of data mining. The results of this study are in line with those from previous research but show a potential to predict the higher levels of household car ownership with greater accuracy than other similar studies.