Recently, Lasso methods have been applied to economic questions. In a seminal paper, Belloni et al. (Econometrica; 80(6): 2369-2429) make use of (post-)Lasso for instrumental variable selection in a setting where the number of instruments p is large or might even exceed the number of observations n-a situation which is prevalent in many current applications. We replicate their simulation study with the statistical package R (R Development Core Team (2008)) and, moreover, analyze in more detail the importance of the choice of the penalization parameter, a crucial component in applications.