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Many phenomena that extend along time require a specific approach to determine the effects over time of a given set of events, for instance online advertising campaigns.

Causal effects in observational time series can be identified by estimating a synthetic control.

This can be done using structural time-series models and suitable predictors.

The CausalImpact R package implements one approach to this.