  With the big popularity and success of Judea Pearl's original causality book,
this review covers the main topics updated in the second edition in 2009 and
illustrates an easy-to-follow causal inference strategy in a forecast scenario.
It further discusses some potential benefits and challenges for causal
inference with time series forecasting when modeling the counterfactuals,
estimating the uncertainty and incorporating prior knowledge to estimate causal
effects in different forecasting scenarios.
