2026-07-28T03:32:33Zhttps://docta.ucm.es/rest/oai/request
oai:docta.ucm.es:20.500.14352/642092025-05-19T18:22:18Zcom_20.500.14352_14col_20.500.14352_17
Docta Complutense author Novales Cinca, Alfonso Santiago author Domínguez Irastorza, Emilio author Pérez, Javier author Ruiz Andújar, Jesús 2023-06-21T01:37:57Z 2023-06-21T01:37:57Z 1998 https://hdl.handle.net/20.500.14352/64209 http://www.ucm.es/icae 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. eng Atribución-NoComercial-CompartirIgual 3.0 España Solving nonlinear rational expectations models by eigenvalue-eigenvector decompositions technical report URL https://docta.ucm.es/bitstreams/a36e534f-4479-4eb6-9117-6592c5425b70/download File MD5 f00614b76ef4d138ee808b69295e59b6 1052800 application/pdf 9808.pdf URL https://docta.ucm.es/bitstreams/838a7582-33fa-43a9-a7d8-6d486962fe6b/download File MD5 1f3d961be4cc9f35fe1800ba508311db 93279 text/plain 9808.pdf.txt