Abstract
Abstract Some practical issues are discussed that relate to the use of the parameterized expectations approach (PEA) for solving nonlinear stochastic dynamic models with rational expectations. This approach has been applied widely as it turns out to be a convenient algorithm, especially when there are large numbers of state variables and stochastic shocks in key conditional expectations terms. The first main section of the chapter provides a detailed discussion of some practical issues associated with the algorithm, and of its application. This is done using a set of examples—the Lucas asset pricing model, the simple stochastic growth model, and four variations of the latter, each selected to demonstrate a different issue. The next section describes a FORTRAN program used for implementing the algorithm, and the following one shows how it is applied to and adapted for each example previously presented.
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