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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