A Forecaster's Review of Judea Pearl's Causality: Models, Reasoning and Inference, Second Edition, 2009
It provides a review and application guide for forecasters interested in causal inference, but is incremental as it builds on existing work.
This paper reviews the updated topics in Judea Pearl's second edition causality book and presents an easy-to-follow causal inference strategy for forecasting scenarios, discussing benefits and challenges like modeling counterfactuals and estimating uncertainty.
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.