Structural models for policy-making: Coping with parametric uncertainty

TL;DR

This paper introduces a framework for policy evaluation with structural econometric models that explicitly accounts for parametric uncertainty, highlighting its impact on policy recommendations.

Contribution

It develops a generic approach using uncertainty sets to incorporate parametric uncertainty into policy-making, framing it as a decision problem under uncertainty.

Findings

Significant uncertainty in policy predictions from the human capital investment model.

Different decision rules under uncertainty lead to varying policy recommendations.

The approach emphasizes the importance of accounting for parametric uncertainty in policy analysis.

Abstract

The ex-ante evaluation of policies using structural econometric models is based on estimated parameters as a stand-in for the true parameters. This practice ignores uncertainty in the counterfactual policy predictions of the model. We develop a generic approach that deals with parametric uncertainty using uncertainty sets and frames model-informed policy-making as a decision problem under uncertainty. The seminal human capital investment model by Keane and Wolpin (1997) provides a well-known, influential, and empirically-grounded test case. We document considerable uncertainty in the models's policy predictions and highlight the resulting policy recommendations obtained from using different formal rules of decision-making under uncertainty.