Counterfactuals and Policy Analysis in Structural Models
This work addresses policy analysis and fault diagnosis in econometrics and social sciences, representing an incremental advancement in structural modeling.
The paper tackles the problem of evaluating counterfactual queries in causal models, presenting a method for nonlinear structural models that generalizes simultaneous equations, with results enabling coherent policy analysis for controlled variables influenced by other variables.
Evaluation of counterfactual queries (e.g., "If A were true, would C have been true?") is important to fault diagnosis, planning, determination of liability, and policy analysis. We present a method of revaluating counterfactuals when the underlying causal model is represented by structural models - a nonlinear generalization of the simultaneous equations models commonly used in econometrics and social sciences. This new method provides a coherent means for evaluating policies involving the control of variables which, prior to enacting the policy were influenced by other variables in the system.