SFB 303 Discussion Paper No. A - 266

Author: Horvath, Balazs, and Marc Nerlove
Title: Are Policy Variables Exogeneous? The Econometric Implications of Learning while Maximizing
Abstract: This paper explores the econometric implications of learning behavior. In an illustrative model the government maximizes the discounted sum of tax revenues subject to the constraint imposed by a Laffer curve involving a parameter initially not perfectly known but about which Bayesian learning occurs. A distinction between active and passive learning is made. On the basis of an argument on the curvature of the value function arising in a dynamic programming approach to the problem, active learning is shown to be the rule rather than the exception. The problem is nontrivial and dynamic by virtue of the presence of learning about the unknown parameter. The government must strike an optimal balance between current payoff maximization and generation of future information that enhances the efficiency of maximization in subsequent periods. The issue of exogeneity of policy variables is addressed. It is demonstrated that learning affects the exogeneity status of policy variables and may have implications similar to the Lucas critique.
Creation-Date: Revised December 1989
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