Longitudinal microdata permit important gains for empirical analysis of socio-spatial inequalities, which allow producing more reliable estimates of the different factors determining inequality. By following the same individuals over time, longitudinal data allows to measure how much of the differences in individual socio-economic outcomes are due to changes in their residential locations (e.g. cities vs. rural areas), or to differences between individuals (e.g. high vs. low education levels). Furthermore, it allows measuring these effects over the life-course of individuals and hence provides a unique opportunity to evaluate the effect of specific policy interventions, both place-based and people-based interventions.
RELOCAL will develop empirical models to assess the importance of location and contextual factors and people factors on inequality using longitudinal microdata obtained from (either or both) EUROSTAT microdata surveys such as the European Union Statistics on Income and Living Conditions (EU-SILC), and country-specific national microdata surveys.