Modeling household decisions using longitudinal data from household panel surveys, with applications to residential mobility

TL;DR: In this article, the authors proposed two types of multilevel random-effects models to address some of these issues: a multiple-membership model in which the outcome depends on a weighted combination of the random effects for each decision maker and a random-coefficients model that allows different random effect for individuals when they are single and partnered.

Abstract: Many events occurring to married or cohabiting individuals are the result of decisions made jointly by both partners. However, studies of life-course events usually take an individual or head-of-household perspective and so do not explicitly reflect the joint nature of these decisions. Household panel studies and population registers are a rich resource for the study of household events, but analyzing such data presents major analytical challenges. Models should ideally allow for the influence of both partners in a couple’s decision making and be flexible enough to handle the facts that individuals can change their partners and have periods when they are not in coresidential unions. In this article, the authors propose two types of multilevel random-effects models to address some of these issues: a “multiple-membership” model in which the outcome depends on a weighted combination of the random effects for each decision maker and a random-coefficients model that allows different random effects for individuals when they are single and partnered. All methods are discussed in terms of a binary household outcome before describing more general discrete-choice models for nominal outcomes. The proposed methods are compared with previously used approaches in a simulation study and illustrated in analyses of residential mobility using data from the British Household Panel Survey.