Rational Learning and Bounded Learning in the Diffusion of Policy Innovations

Abstract

In political science, rational learning and bounded learning are commonly studied as two opposing theories of policy choice. In this article, I use a rational learning approach to reach conclusions about bounded learning, showing that the two theories are not necessarily incompatible. By examining a rational learning model and the decisions of a set of developing countries to open up their trade regimes, I show that countries are particularly influenced by the choices of neighbouring countries and by particularly successful policy experiences. These are two typical contentions of the bounded learning literature. I argue that bounded learning and rational learning yield the same results as soon as one drops the rational learning assumption that there are zero costs to gathering new information. I use the discussion on rational learning versus bounded learning as a basis for exploring more general issues concerning the diffusion of policy innovations.