Reviews: Identifying Causal Effects via Context-specific Independence Relations

This paper proposes an automated search procedure for identifying causal effects when context-specific independence relations are present in an observed distribution. Equipped with sufficient conditions for conditional independence statements (Boutiller et al. 1996) and LDAG representation (Pensar et al. 2015), a simple search algorithm is implemented. Overall, the paper is clearly written, and it was easy to follow theorems (clarity). However, it is hard to measure the novelty of the paper (originality), which I will discuss below. Hence, the proposed algorithm may be useful for some researchers, but its significance (impact) is unclear. It is nice to see the rules (basic probability axioms (CS) independence) written clearly, which lead to the implementation of a search algorithm.