Counterfactuals and Policy Analysis in Structural Models

TL;DR

This paper introduces a method for evaluating counterfactuals within structural causal models, enabling more accurate policy analysis and fault diagnosis in complex systems.

Contribution

It presents a novel approach to revalue counterfactuals in nonlinear structural models, extending traditional econometric methods for better policy evaluation.

Findings

Provides a coherent framework for policy control analysis

Enables counterfactual evaluation in nonlinear models

Improves fault diagnosis and liability determination

Abstract

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.