**By Gabriel Vasconcelos**

In a recent paper, which can be downloaded here, Carvalho, Masini and Medeiros show that estimating counterfactuals in a non-stationary framework (when I say non-stationary it means integrated) is a tricky task. It is intuitive that the models will not work properly in the absence of cointegration (spurious case), but what the authors show is that even with cointegration, the average treatment effect (ATE) converges to a non-standard distribution. As a result, standard tests on the ATE will identify treatment effects in several cases when there is no effect at all.

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