This paper investigates car ownership dynamics based on irregularly spaced panel data of Denmark. The data originates from a national travel survey, where a fraction of the respondents are recurrent due to the random sampling scheme of the survey. While this creates a rich sample collected over a long time period and with desired variation between the panel observations, it introduces an estimation challenge due to the irregular spacing of the panel observations. This challenge is addressed by estimating changes in car ownership based on a generalised ordered logit model in which the irregular nature of the spacing between panel observations is controlled by including panel-specific weights in the log-likelihood function. The estimated model, which is formulated as a first-difference approach, includes several variables explaining the change of car ownership. Specifically, it is found that accessibility improvements, measured as the number of people that can be reached by public transport within a certain time interval, significantly reduce the likelihood of acquiring additional cars in the observation period. In line with the literature, it is also confirmed that changes in income, number of adults and driver’s licenses within the household have a significant impact on household car ownership changes.

本文基于丹麦的不规则间隔面板数据研究汽车拥有动态。数据来自全国旅行调查，由于调查的随机抽样方案，其中一小部分受访者是经常性的。虽然这会产生一个在很长一段时间内收集的丰富样本，并且在小组观察之间具有所需的变化，但由于小组观察的不规则间隔，它引入了估计挑战。这一挑战是通过基于广义有序 logit 模型估计汽车拥有量的变化来解决的，在该模型中，通过在对数似然函数中包含特定于面板的权重来控制面板观察之间间隔的不规则性质。估计模型，它被公式化为一阶差分方法，包括几个解释汽车所有权变化的变量。具体而言，研究发现，以公共交通在一定时间间隔内可到达的人数来衡量的可达性改善，显着降低了观察期内获得更多汽车的可能性。与文献一致，也证实了家庭内收入、成年人数量和驾照的变化对家庭汽车拥有量的变化有显着影响。