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.g. the Euler equation). The PEA flips this idea on its head: if we know the expectation term, we can recover the unknown policy function. For several reasons, this works better this way.