PEA

I show that the Parameterized Expectations Algorithm (PEA) can be naturally generalized via the bias-corrected Monte Carlo (bc-MC) operator, initially proposed to solve economic models using neural networks. When combined with a parameterized …

Introduction This blog post is about my work on a generalization of the Parameterized Expectations Algorithm, available here. The Parameterized Expectations Algorithm (PEA) is a classic computational approach to numerically “solve” economic models with rational expectations, i.e. finding an approximate solution. Usually, to solve economic models of this type, one has to find a policy function (e.g. how much to consume today, given a current level of capital) that satisfies a functional equation that holds in expectation (e.