Working Paper: NBER ID: w10025
Authors: William A. Brock; Steven N. Durlauf; Kenneth D. West
Abstract: This paper develops a decision-theoretic approach to policy analysis. We argue that policy evaluation should be conducted on the basis of two factors: the policymaker's preferences, and the conditional distribution of the outcomes of interest given a policy and available information. From this perspective, the common practice of conditioning on a particular model is often inappropriate, since model uncertainty is an important element of policy evaluation. We advocate the use of model averaging to account for model uncertainty and show how it may be applied to policy evaluation exercises. We illustrate our approach with applications to monetary policy and to growth policy.
Keywords: No keywords provided
JEL Codes: C10; C50; E52; O40
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| Model Uncertainty (D81) | Evaluation of Policies (D78) |
| Model Uncertainty (D81) | True Effects of a Policy (D78) |
| Model Averaging (C51) | Assessment of Policy Impacts (F68) |
| Model Averaging (C51) | Robustness of Policy Effects (D78) |
| Conditional Probabilities of Outcomes (C29) | Policy Recommendations (D78) |
| Policymakers' Preferences (D72) | Evaluation of Policies (D78) |