I want to use to Google's causal impact function to impute the effect of an intervetion. However, my data is structured as: pre-period=1991-1995, intervetion occurs, post-period=1996-2017. To clarify, the intervention is the entrance of a new buyer to the market. I want to test if the demand of the new buyer changed production. So I want impute the counterfactual for 1991-1995 as if the buyer was always in the market.
Because I have so many more years of post intervetnion data, I think it would be safer to train on the post-period data and try to backcast the pre-period data.
Does anyone know if this is possible using the CausalImpact function? Is anyone aware of a better function or resource?