A Longitudinal Mixed Logit Model for Estimation of Push and Pull Effects in Residential Location Choice

Abstract

We develop a random effects discrete choice model for the analysis of households’ choice of neighborhood over time. The model is parameterized in a way that exploits longitudinal data to separate the influence of neighborhood 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 households in 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 efficient 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 British Household Panel Survey linked to neighborhood-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. Supplementary materials for this article are available online.