RT Report
T1 Solving nonlinear rational expectations models by eigenvalue-eigenvector decompositions
A1 Novales Cinca, Alfonso Santiago
A1 Domínguez Irastorza, Emilio
A1 Pérez, Javier
A1 Ruiz Andújar, Jesús
AB We provide a summarized presentation of solution methods for rational expectations models, based on eigenvalue/eigenvector decompositions. These methods solve systems of stochastic linear difference equations by relying on the use of stability conditions derived from the eigenvectors associated to unstable eigenvalues of the coefficient matrices in the system. For nonlinear models, a linear approximation must be obtained, and the stability conditions are approximate, This is however, the only source of approximation error, since the nonlinear structure of the original model is used to produce the numerical solution. After applying the method to a baseline stochastic growth model, we explain how it can be used: i) to salve some identification problems that may arise in standard growth models, and ii) to solve endogenous growth models.
PB Facultad de Ciencias Económicas y Empresariales. Instituto Complutense de Análisis Económico (ICAE)
YR 1998
FD 1998
LK https://hdl.handle.net/20.500.14352/64209
UL https://hdl.handle.net/20.500.14352/64209
LA eng
DS Docta Complutense
RD 30 mar 2026