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.     

Changes in level of household car ownership: the role of life events and spatial context

Recent longitudinal studies of household car ownership have examined factors associated with increases and decreases in car ownership level. The contribution of this panel data analysis is to identify the predictors of different types of car ownership level change (zero to one car, one to two cars and vice versa) and demonstrate that these are quite different in nature. The study develops a large scale data set (n = 19,334), drawing on the first two waves (2009–2011) of the UK Household Longitudinal Study (UKHLS). This has enabled the generation of a comprehensive set of life event and spatial context variables. Changes to composition of households (people arriving and leaving) and to driving licence availability are the strongest predictors of car ownership level changes, followed by employment status and income changes. Households were found to be more likely to relinquish cars in association with an income reduction than they were to acquire cars in association with an income gain. This may be attributed to the economic recession of the time. The effect of having children differs according to car ownership state with it increasing the probability of acquiring a car for non-car owners and increasing the probability of relinquishing a car for two car owners. Sensitivity to spatial context is demonstrated by poorer access to public transport predicting higher probability of a non-car owning household acquiring a car and lower probability of a one-car owning household relinquishing a car. While previous panel studies have had to rely on comparatively small samples, the large scale nature of the UKHLS has provided robust and comprehensive evidence of the factors that determine different car ownership level changes.     

The asymmetric income effect on household vehicle ownership in Taiwan: A threshold cointegration approach

This paper uses the asymmetric threshold cointegration test to examine the asymmetric relationship between household income and vehicle ownership in Taiwan, presenting estimated asymmetric error correction models. The empirical data include information on household income, car ownership and motorcycle ownership in different regions from 1974 to 2009. The results show that, first, motorcycle ownership is asymmetrically cointegrated with household income in each region, and car ownership is asymmetrically cointegrated with household income in all regions except Taipei city. Second, both car and motorcycle ownership levels increase faster than they decrease in the asymmetric adjustment of their long-run relationship. Third, sensitivity tests for the period 1987-2009 show that the cointegration relationship of the car ownership equations vanished. Finally, we find evidence on the effects of household income on motorcycle ownership, and the effects of income variables on car and motorcycle ownership are dissimilar. This study exhibits different results across regions. These findings may be related to the development of public transit system in each region.     

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 model system of household car ownership,trip generation,and modal split: model development and simulation experiment

A dynamic model of household car ownership and mode use is developed and applied to demand forecasting. The model system consists of three interrelated components: car ownership, mechanized trip generation, and modal split. The level of household car ownership is represented as a function of household attributes and mobility measures from the preceding observation time point using an ordered-response probit model. The trip generation model predicts the weekly number of trips made by household members using car or public transit, and the modal split model predicts the fraction of trips that are made by public transit. Household car ownership is a major determinant in the latter two model components. A simulation experiment is conducted using sample households from the Dutch National Mobility Panel data set and applying the model system to predict household car ownership and mode use under different scenarios on future household income, employment, and drivers’ license holding. Policy implications of the simulation results are discussed.     

Changing household car ownership level and life cycle events: an action in anticipation or an action on occurrence

This paper analyzes households’ decision to change their car ownership level in response to actions/decisions regarding mobility issues and other household events. Following recent literature on the importance of critical events for mobility decisions, it focuses on the relationship between specific events (e.g. childbirth and buying an extra car), rather than trying to explain the status of car ownership from a set of stationary explanatory variables. In particular, it is hypothesized that changes in household car ownership level take place in response to stressors, resulting from changed household needs or aspirations. The study includes a broad range of events. Apart from changes in work status, employer and residential location, it analyzes demographic events such as household formation and childbirth. Also, it scrutinizes the temporal sequence in which chains of related events are most likely to occur. To this end, data from a retrospective survey that records respondents’ car ownership status, as well as residential and household situation over the past 20 years are used. A panel analysis has been carried out to disentangle typical relationships. The results suggest that strong and simultaneous relationships exist between car ownership changes and household formation and dissolution processes. Childbirth and residential relocation invoke car ownership changes. Changes are also made in anticipation of future events such as employer change and childbirth. Childbirth is associated with increasing the number of cars, whereas the effect of employer change goes the opposite way. Job change increases the probability of car ownership change in the following year.     

Variation of households<Emphasis Type="Bold">’</Emphasis> car ownership across time: application of a panel data model

For economic and environmental policy formulation and with the effort of creating less car dependent societies, it is important to study the changing characteristics of car ownership in a household through time as well as factors responsible of these variations. There is a vast body of literature on empirical studies of car ownership and use. These studies have investigated the socio-economic background of the decision maker, the built environment and the perception associated with owning a car as determinant factors of car ownership and use. In most cases, these analyses have been carried out using cross-sectional data sets. However, the analysis of factors determining changes in travel behavior of an individual or household requires information on their behavior over time (longitudinal data set). In this study, the German Mobility Panel (1996–2006) is used to examine variation of car ownership through time and across households. The panel data modeling results showed that there are variations of car ownership between households whereas changes in car ownership of a given household over time (within household variations) are insignificant. The influence of other factors such as the households’ socio-economic background, the availability of public transportation and shopping/leisure facilities, perception on parking difficulties and satisfaction with existing public transportation services on the car owning characteristics of households is also presented and discussed in this paper.

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.     

From e-bike to car: A study on factors influencing motorization of e-bike users across China

Household car ownership has risen dramatically in China over the past decade. At the same time a disruptive transportation technology emerged, the electric bike (e-bike). Most studies investigating motorization in China focus on macro-level economic indicators like GDP, with few focusing on household, city-level, environmental, or geographic indicators, and none in the context of high e-bike ownership. This study examines household vehicle purchase decisions across 59 cities in China with broad geographic, environmental, and socio-economic characteristics. We focus on a subset of households who own e-bikes and rely on a telephone survey from an industry customer database. From these responses, we estimate two three-level hierarchical choice models to assess attributes that contribute to (1) recent car purchases and (2) the intention to buy a car in the near future. The results show that the models are dominated by household characteristics including household income, household size, household vehicle ownership, number of licensed drivers and duration of car ownership. Some geographic, environmental and socio-economic factors have significant influences on car purchase decisions. Only two city-level transportation variable have an effect – higher taxi density and higher bus density reducing car purchase. Cold weather, population density gross domestic product per capita positively influence car purchase, while urbanization rate reduces car purchase. Because of supply heterogeneity in the data set, described by publicly available urban transportation data, this is the first study that can include geographic and urban infrastructure differences that influence purchase choice and suggests potential region-specific policy approaches to managing car purchase may be necessary.     

Estimating the long-term effects of different passenger car technologies on energy/fuel consumption and emissions of greenhouse gases in Europe

Abstract

A stated preference (SP) experiment of car ownership was conducted in Mumbai Metropolitan Region (MMR) of Maharashtra in India. A full factorial experiment was designed to considering various attributes such as travel time, travel cost, projected household income, car loan payment and servicing cost. Data on 357 individuals were collected which resulted in 3213 observations for the calibration of the work trip and recreational trip car ownership models. The car ownership alternatives considered 0, 1 and 2 cars. A multinomial logit framework was used to develop the car ownership model taking the household as a decision unit. The specification and results of the SP car ownership model are discussed. The observed and predicted values matched reasonably when the validity of the SP car ownership model was tested against revealed preference (RP) data. The car ownership models developed in this study exhibit a satisfactory goodness of fit. It is concluded that the SP modelling approach can be successfully used for modelling car ownership decisions of households in developing countries.     

Household-level commuting mode choices,car allocation and car ownership level choices of two-worker households: the case of the city of Toronto

The paper presents a comprehensive investigation on household level commuting mode, car allocation and car ownership level choices of two-worker households in the City of Toronto. A joint econometric model and a household travel survey dataset are used for empirical investigations. Empirical models reveal that significant substitution patterns exist between auto driving and all other mode choices in two-worker households. It is revealed that, female commuters do not prefer auto driving, but in case of a one car (and two commuters with driving licenses) household, a female commuter gets more preference for auto driving option than the male commuter. Reverse commuting (commuting in opposite direction of home to central business district) plays a critical role on household level car allocation choices and in defining the stability of commuting behaviour of two-worker households. Two worker households in higher income zones and with longer commuting distances tend to have higher car ownership levels than others. However, higher transit accessibility to jobs reduces household car ownership levels. The study reveals that both increasing two worker households and reverse commuting would increase dependency on private car for commuting.     

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.     

The transaction cost approach to modeling the demand for automobiles

The purchase of an automobile involves significant transaction costs in addition to the purchase price. Therefore, the assumptions implied by static car holding models are invalid. This paper describes a dynamic approach to the modeling of level-of-ownership and auto-type choice, based on a transaction choice model which utilizes information on past car ownership. The cost or disutility of a transaction depends on the attributes of the household and the purchased car, as well as on past car-ownership characteristics. A set of assumptions underlying the incorporation of transaction costs in the model is presented. The paper discusses the econometric implications of omitting the dynamic attributes (i.e., past ownership characteristics). A disaggregate model was estimated, using a choice-based sample consisting of a random sample of households enriched with a sample of households which transacted in the car market during the study period. This sampling method combined with a random choice of a subset of the car alternatives provides for a cost-effective method to estimate a transaction model.     

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.     

The effect of prices and income on car travel in the UK

The objective of this paper is to analyse the factors determining household car travel, and specifically the effects of household income and the prices of cars and motor fuels, and to explore the intertemporal pattern of adjustment. The question of asymmetry in the response to rising and falling income is also addressed. Such asymmetry may be caused by habit or resistance to change or the tendency to acquire habits to consume more easily than to abandon them. The impact of prices, the speed of adjustment and the resistance to change will be important in determining the possibility of influencing travel behaviour and specifically car use. The study utilises repeated cross-section data from the annual UK Family Expenditure Surveys and employs a pseudo-panel methodology. The results are compared with those for car ownership estimated on the basis of similar models.     

Car ownership and access to jobs in Spain

The purpose of this paper is to assess the effect of urban structure on household car ownership in a context of rapid job and population decentralization. We capture the effect of urban structure through a measure of job accessibility to employment by public transport. An ordered probit explaining the number of cars per household is estimated as a function of individual, household and spatial variables. The data used in the analysis come from the Spanish Institute of Statistics’ 2001 Micro-census for the areas of Barcelona and Madrid. The results show that spatial variables play a significant role in explaining the probability of car ownership. We provide the car ownership elasticities with respect the job accessibility measure. Additionally, we carried out simulation exercises in which the expected number of vehicles decreases as accessibility improves.     

Car ownership and public transport use: Revisiting the interaction

At the beginning of the 1980s, it seemed that a consensus was emerging among researchers that public transport service levels, fares or quality had a small but possibly important effect on car ownership, and that this should be taken into account for those purposes where car ownership forecasts are used for developing policy on public transport or roads. Somehow, the findings faded away, and had little effect on policy thinking or on analytical techniques. The results of six surveys carried out in South Yorkshire over the period 1972 to 1991, during which there were extreme changes in public transport policy, tend to support a prima facie case for reopening the question. At the household level, car ownership rates are shown to be more volatile than is often assumed, especially in multiple car households. This volatility provides a context within which the quality of public transport provision appears to influence both the level of car ownership and the relationship between changes in the level of car ownership and changes in public transport use.     

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.