Placebo Tests for Synthetic Controls
Bruno Ferman and
Cristine Pinto ()
MPRA Paper from University Library of Munich, Germany
The synthetic control (SC) method has been recently proposed as an alternative to estimate treatment effects in comparative case studies. An important feature of the SC method is the inferential procedures based on placebo studies, suggested in Abadie et al. (2010). In this paper, we evaluate the statistical properties of these inferential techniques. We first show that the graphical analysis with placebos can be misleading, as placebo runs with lower expected squared prediction errors would still be considered in the analysis. Then we show that a test based on the the post/pre-intervention mean squared prediction error, as suggested in Abadie et al. (2010), ameliorates this problem. However, we show that such test can still have some size distortions, even if we consider a case in which the test statistic has the same marginal distribution for all placebo runs. Finally, we show that the fact that the SC weights are estimated can lead to important additional size distortions.
Keywords: synthetic control, difference-in-differences; linear factor model, inference, permutation test (search for similar items in EconPapers)
JEL-codes: C12 C13 C21 C23 (search for similar items in EconPapers)
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