Publication Detail
A Review of Dynamic Vehicle Holdings Models and a Proposal for a Vehicle Transactions Model
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UCD-ITS-RP-92-01 Presentation Series |
Suggested Citation:
Kitamura, Ryuichi (1991) A Review of Dynamic Vehicle Holdings Models and a Proposal for a Vehicle Transactions Model. Institute of Transportation Studies, University of California, Davis, Presentation Series UCD-ITS-RP-92-01
Proceedings of the Japanese Society of Civil Engineers, Number 440/IV-16
Household vehicle holdings observed at a time point embody many decisions made by the household over a period of time. The set of vehicles the household holds, or "household vehicle fleet," is not acquired instantaneously; it is the result of a series of transaction decisions to acquire, replace, or dispose of household vehicles. Each of these decisions is conditioned on the current vehicle holdings, and reflects the long-term planning effort of the household.
Most household vehicle holdings models are either "cross-sectional," using data obtained at one point in time, or "pseudo-dynamic," using repeated cross-sectional data or aggregate time-series observations obtained from various sources. Both classes of models are subject to certain limitations. Application of cross-sectional models to forecasting implies "longitudinal extrapolation of cross-sectional variations" which is valid only under very restrictive conditions. For example, questions have been raised whether cross-sectional elasticities estimated from these models are identical to longitudinal elasticities that are associated with changes in behavior. Cross-sectional models' ability to accurately represent household behavior under changing income, fuel prices, traffic congestion, etc., should be critically re-examined. Aggregate time-series-models, on the other hand, are often incapable of capturing causal relationships governing the behavior of individual behavioral units, thus tend to be limited in their accuracy and policy sensitivity.
Household vehicle holdings observed at a time point embody many decisions made by the household over a period of time. The set of vehicles the household holds, or "household vehicle fleet," is not acquired instantaneously; it is the result of a series of transaction decisions to acquire, replace, or dispose of household vehicles. Each of these decisions is conditioned on the current vehicle holdings, and reflects the long-term planning effort of the household.
Most household vehicle holdings models are either "cross-sectional," using data obtained at one point in time, or "pseudo-dynamic," using repeated cross-sectional data or aggregate time-series observations obtained from various sources. Both classes of models are subject to certain limitations. Application of cross-sectional models to forecasting implies "longitudinal extrapolation of cross-sectional variations" which is valid only under very restrictive conditions. For example, questions have been raised whether cross-sectional elasticities estimated from these models are identical to longitudinal elasticities that are associated with changes in behavior. Cross-sectional models' ability to accurately represent household behavior under changing income, fuel prices, traffic congestion, etc., should be critically re-examined. Aggregate time-series-models, on the other hand, are often incapable of capturing causal relationships governing the behavior of individual behavioral units, thus tend to be limited in their accuracy and policy sensitivity.