This paper examines the monetary transmission mechanism in the euro area for the period of single monetary policy using factor-augmented vector autoregressive (FAVAR) techniques. The contributions of the paper are fourfold. First, a novel dataset consisting of 120 disaggregated macroeconomic time series spanning the period 1999:M1 through 2011:M12 is gathered for the euro area as an aggregate. Second, Bayesian joint estimation technique of FAVARs is applied to the European data. Third, time variation in the transmission mechanism and the impact of the global financial crisis is investigated in the FAVAR context using a rolling windows technique. Fourth, we tried to contribute to the question of whether more data are always better for factor analysis as well as the estimation of structural FAVAR models. We find that there are considerable gains from the implementation of the Bayesian technique such as smoother impulse response functions and statistical significance of the estimates. According to our rolling estimations, consumer prices and monetary aggregates display the most time variant responses to the monetary policy shocks. The pre-screening technique considered, elimination of almost half of the dataset seems to do no worse, and in some cases, better in a structural context.