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A longitudinal mixed logit model for estimation of push andpull effects in residential location choice

机译:纵向混合logit模型,用于估计住宅位置选择中的推拉效应

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摘要

We develop a random effects discrete choice model for the analysis of households' choice of neighbourhood over time. The model is parameterised in a way that exploits longitudinaluddata to separate the influence of neighbourhood characteristics on the decision to move out of the current area ("push" effects) and on the choice of one destination over another ("pull" effects). Random effects are included to allow for unobserved heterogeneity between householdsudin their propensity to move, and in the importance placed on area characteristics. The model also includes area-level random effects. The combination of a large choice set, large sample size and repeated observations mean that existing estimation approaches are often infeasible. We therefore propose an effcient MCMC algorithm for the analysis of large-scale datasets. The model is applied in an analysis of residential choice in England using data from the BritishudHousehold Panel Survey linked to neighbourhood-level census data. We consider how effects of area deprivation and distance from the current area depend on household characteristics and life course transitions in the previous year. We find substantial differences between households in the effects of deprivation on out-mobility and selection of destination, with evidence of severely constrained choices among less-advantaged households.
机译:我们建立了一个随机效应离散选择模型,用于分析家庭随着时间推移对邻里的选择。通过以下方式对模型进行参数化:利用纵向 uddata来区分邻域特征对移出当前区域的决策(“推”效应)和选择一个目的地而不是另一目的地(“拉”效应)的影响。 。包括随机效应,以允许家庭之间的观察到的异质性移动倾向,以及对区域特征的重视。该模型还包括区域级随机效应。大选择集,大样本量和重复观察的结合意味着现有的估算方法通常不可行。因此,我们提出了一种用于分析大型数据集的有效MCMC算法。该模型用于分析英国的住宅选择,使用的是来自British udHousehold Panel Survey的数据,该数据与社区一级的普查数据相关联。我们考虑区域剥夺和与当前区域之间距离的影响如何取决于上一年的家庭特征和生活历程的转变。我们发现,在贫困对外出和目的地选择的影响之间,家庭之间存在巨大差异,证据表明,弱势家庭的选择受到严重限制。

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