Description   Focus of our statistical and econometric research methodology is the analysis of individual behaviour. We study decisions made by individuals or households, and we analyse how individuals respond to their socio-economic environment, including institutions and policy measures. We estimate behavioural reactions ("feedback effects") to changes in public policy, e.g. changes of health care utilisation and its implications for health status in the wake of a health care reform, or changes of the retirement age and the level of savings in the wake of a pension reform. The data we are using are non-experimental and come from SHARE and its sister surveys ELSA and HRS. We employ a number of well-known and also of advanced statistical techniques, including regression types of analyses, multinomial choice models of various kinds, robust, semi-parametric and non-parametric estimation methods, duration analysis, and bio-statistical methods, paying attention to the nature (particularly selectivity) of the samples and the endogeneity of explanatory variables. In addition to the behavioural analyses, we construct indicators designed to inform policy in the area of ageing. The choice of indicators will be motivated by both policy relevance and the cross-country reliability and validity as inferred from the above behavioural analyses. For example, an indicator of work-related disability will reflect validated measures of incapacity to work that are comparable across countries and not administrative data that would confound individual circumstances with legal eligibility rules. We place particular emphasis on inequality or distributional measures, to an extent not possible with aggregate data.