A Log-Linear Homotopy Approach to Initialize the Parameterized Expectations Algorithm

In this paper I present a proposal to obtain appropriate initial conditions while solving general equilibrium rational expectations models with the Parameterized Expectations Algorithm. The proposal is based on a log-linear approximation for the model under study, so that it can be a particular variant of the homotopy approach. The main advantages of the proposal are: (i) it guarantees the ergodicity of the initial time series used as an input to the Parameterized Expectations Algorithm; (ii) it performs well in regard to the speed of convergence when compared to some homotopy alternatives; (iii) it is easy to implement. The claimed advantages are successfully illustrated in the framework of the Cooley and Hansen (1989) model with indivisible labor and money demand motivated via a cash-in-advance constraint, as compared to a procedure based on the standard implementation of homotopy principles.