published as 'Partner (dis)agreement on moving desires and the subsequent moving behaviour of couples' in: Population, Space and Place, 2012, 18 (1), 16-30
Residential mobility decisions are known to be made at the household level. However, most empirical analyses of residential mobility relate moving behaviour to the housing and neighbourhood satisfaction and pre-move thoughts of individuals. If partners in a couple do not share evaluations of dwelling or neighbourhood quality or do not agree on whether moving is (un)desirable, ignoring these disagreements will lead to an inaccurate assessment of the strength of the links between moving desires and actual moves. This study is one of the first to investigate disagreements in moving desires between partners and the subsequent consequences of such disagreements for moving behaviour. Drawing on British Household Panel Survey (BHPS) data, we find that disagreement about the desirability of moving is most likely where partners also disagree about the quality of their dwelling or neighbourhood. Panel logistic regression models show that the moving desires of both partners interact to affect the moving behaviour of couples. Only 7.6% of couples move if only the man desires to move, whereas 20.1% of shared moving desires lead to a subsequent move.
We use cookies to provide you with an optimal website experience. This includes cookies that are necessary for the operation of the site as well as cookies that are only used for anonymous statistical purposes, for comfort settings or to display personalized content. You can decide for yourself which categories you want to allow. Please note that based on your settings, you may not be able to use all of the site's functions.
Cookie settings
These necessary cookies are required to activate the core functionality of the website. An opt-out from these technologies is not available.
In order to further improve our offer and our website, we collect anonymous data for statistics and analyses. With the help of these cookies we can, for example, determine the number of visitors and the effect of certain pages on our website and optimize our content.