摘要：While the literature on synthetic control methods mostly abstracts from out-of-sample measures, Abadie et al. (2015)
have recently introduced a cross-validation approach. This technique, however, is not well-defined since it hinges on
predictor weights which are not uniquely defined. We fix this issue, proposing a new, well-defined cross-validation
technique, which we apply to the original Abadie et al. (2015) data. Additionally, we discuss how this new technique
can be used for comparing different specifications based on out-of-sample measures, avoiding the danger of cherrypicking.
