Using unique administrative register data, we investigate old-age retirement under the statutory pension scheme in Finland. The analysis is based on multi-outcome modelling of pensions and working lives together with a range of explanatory variables. An adaptive multi-outcome LAD-lasso regression method is applied to obtain estimates of earnings and socioeconomic factors affecting old-age retirement and to decide which of these variables should be included in our model. The proposed statistical technique produces robust and less biased regression coefficient estimates in the context of skewed outcome distributions and an excess number of zeros in some of the explanatory variables. The results underline the importance of late life course earnings and employment to the final amount of pension and reveal differences in pension outcomes across socioeconomic groups. We conclude that adaptive LAD-lasso regression is a promising statistical technique that could be usefully employed in studying various topics in the pension industry.Peer reviewe
