In Germany, as elsewhere in the industrialized world, the demand for motor vehicle travel is of particular interest because of its strong growth in recent years, with the number of personal vehicles increasing by 15.2% between 1995 and 2001 (Kraftfahrt-Bundesamt, 2002). Understanding the preferences and constraints that determine motorization can be useful to several policy applications, including assessments of the provision of public transport infrastructure, forecasting of trends in air pollution, and the evaluation of zoning and other land use measures. The present paper analyzes the determinants of individual motor vehicle use by estimating an econometric model on a panel of travel-diary data collected in (Germany between the years 1994 and 2001 http://mobilitaetspanel.ifv.unikarlsruhe.de/). The data set is augmented by various measures of urban form (e.g. street density), which were calculated in a GIS on the basis of postal zip code boundaries. A central goal of the research is to explore the interactions between the urban form measures and the attributes of individual household members, including gender, employment status, and activity pattern, as determinants of private car use. Unlike the majority of studies to date, is addressed the issue of vehicle access from two angles pertaining to the discrete choice of car use and the continuous choice of distance traveled, These distinct yet interrelated decisions are analyzed by employing a Heckit model that partitions individuals according to their use of the car while simultaneously controlling for biases emerging from sample selectivity. The model comprises two stages. As roughly 40% of the observations do not use the car at all on a given day, stage 1 estimates a probit model on the determinants of the discrete choice of vehicle use over the period of a day. In stage 2, a weighted least squares (WLS) model is estimated on the determinants of distance traveled only for those individuals who traveled some positive distance. To control for sample selectivity biases, the inverse Mills ratio calculated from stage 1 is included as an explanatory variable in the second stage estimation. Both the probit and WLS models are estimated using a population-averaged panel specification that controls for the within-person correlation of observations. In applying the model, several conceptual and methodological complications that arise in the context of sample selectivity problems are highlighted. Preliminary results suggest strong effects of gender for both the discrete choice of car use and the continuous choice of distance traveled, whereby women have a lower probability of using the car and travel shorter distances with the car' than men. Interestingly, an interaction term reveals that employed women travel shorter distances with the car than unemployed women. The urban form variables are also identified to be statistically significant, but no distinctions in the effects of these variables are found between women and men. For policy purposes, we discuss how future research needs to disentangle potential simultaneity in decisions regarding mode choice and residential location. For the covering abstract please see ITRD E135207.
Samenvatting