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
This study uses data from the German Mobility Panel (1996–2006) to examine variation of car ownershi...
Abstract: This paper examines the determinants of household car ownership in Ireland, using longitud...
With modern multivariate statistical methods and activity-diary (time-use) data sets, it is possible...
A dynamic (panel data) structural equations model is developed that links four dependent travel beha...
A dynamic (panel data) structural equations model is developed that links four dependent travel beha...
The product of this research is a dynamic simultaneous equations model of car ownership and modal tr...
The product of this research is a dynamic simultaneous equations model of car ownership and modal tr...
A dynamic model of household car ownership and mode use is developed and applied to demand forecasti...
For economic and environmental policy formulation and with the effort of creating less car dependent...
Understanding joint and causal relationships among multiple endogenous variables has been of much in...
The objective of this paper is to present a panel data model of car ownership and mobility. Unobserv...
The question whether fluctuation in fuel price leads to considerable changes in people's activity-tr...
The question whether fluctuation in fuel price leads to considerable changes in people's activity-tr...
This research has two objectives. The first objective is to explore the use of the modeling tool cal...
Levels of demand over time are analyzed for five modes of passenger transportation. The data are for...
This study uses data from the German Mobility Panel (1996–2006) to examine variation of car ownershi...
Abstract: This paper examines the determinants of household car ownership in Ireland, using longitud...
With modern multivariate statistical methods and activity-diary (time-use) data sets, it is possible...
A dynamic (panel data) structural equations model is developed that links four dependent travel beha...
A dynamic (panel data) structural equations model is developed that links four dependent travel beha...
The product of this research is a dynamic simultaneous equations model of car ownership and modal tr...
The product of this research is a dynamic simultaneous equations model of car ownership and modal tr...
A dynamic model of household car ownership and mode use is developed and applied to demand forecasti...
For economic and environmental policy formulation and with the effort of creating less car dependent...
Understanding joint and causal relationships among multiple endogenous variables has been of much in...
The objective of this paper is to present a panel data model of car ownership and mobility. Unobserv...
The question whether fluctuation in fuel price leads to considerable changes in people's activity-tr...
The question whether fluctuation in fuel price leads to considerable changes in people's activity-tr...
This research has two objectives. The first objective is to explore the use of the modeling tool cal...
Levels of demand over time are analyzed for five modes of passenger transportation. The data are for...
This study uses data from the German Mobility Panel (1996–2006) to examine variation of car ownershi...
Abstract: This paper examines the determinants of household car ownership in Ireland, using longitud...
With modern multivariate statistical methods and activity-diary (time-use) data sets, it is possible...