I've done some research in causal inference/maximum-accuracy modeling using (interrupted) time series . It is fascinating, however I am not yet convinced that this is the best analytic engine for producing accurate future forecasts. Perhaps others will suggest methods which exactly match your research objectives.
If legacy methods return less-than-desired performance in your application, I heartily recommend methods which are discussed in the following two articles for information regarding accurate future forecasting in temporal series.