2021-2022 Schedule


Please Note Non-Convential Time:

Friday, March 25, 2022
3:00 p.m. to 4:00 p.m.

Dr. Raghav Singal
Assistant Professor of Business Administration
Tuck School of Business

Title: "Axiomatic Effect Propagation in Causal Networks"

We study effect propagation in a causal directed acyclic graph (DAG), with the goal of providing a flow-based decomposition of the effect (i.e., change in the outcome variable) as a result of changes in the source variables. Our problem setup serves as a unifying framework to compare various ideas on causality to quantify effect propagation, such as direct and indirect effects (Pearl 2001), path-specific effects (Pearl 2001), and degree of responsibility (Chockler & Halpern 2004). We discuss shortcomings of such approaches and propose a flow-based methodology, which we call recursive Shapley value (RSV). By considering a broader set of counterfactuals than existing methods, RSV obeys a unique adherence to four desirable flow-based axioms. Further, we provide a general path-based characterization of RSV for an arbitrary non-parametric structural equations model (SEM) defined on the underlying DAG.  Interestingly, for the special class of linear SEMs, RSV exhibits a simple and tractable characterization, which recovers the classical method of path coefficients (Wright 1934). For non-parametric SEMs, we use our general characterization to develop an unbiased Monte-Carlo estimation scheme with an exponentially decaying sample complexity.  We showcase the application of RSV on two challenging problems on causality (causal overdetermination and causal unfairness).

Raghav Singal is an Assistant Professor in the Operations and Management Science group at the Tuck School of Business (Dartmouth College). Raghav's primary research interest is in the area of analytics. He likes to build models that help businesses understand complex systems and make better decisions.