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  • 标题:On approximating DSGE models by series expansions
  • 本地全文:下载
  • 作者:Giovanni Lombardo
  • 期刊名称:Euro Area Balance of Payments and International Investment Position Statistics
  • 印刷版ISSN:1830-3420
  • 电子版ISSN:1830-3439
  • 出版年度:2010
  • 出版社:European Central Bank
  • 摘要:We show how to use a simple perturbation method to solve non-linear ra- tional expectation models. Drawing from the applied mathematics literature we propose a method consisting of series expansions of the non-linear system around a known solution. The variables are represented in terms of their orders of approximation with respect to a perturbation parameter. The nal solution, therefore, is the sum of the dierent orders. This approach links to formal arguments the idea that each order of approx- imation is solved recursively taking as given the lower order of approximation. Therefore, this method is not subject to the ambiguity concerning the order of the variables in the resulting state-space representation as, for example, has been discussed by Kim et al. (2008). Provided that the model is locally stable, the approximation technique dis- cussed in this paper delivers stable solutions at any order of approximation.
  • 关键词:Solving dynamic stochastic general equilibrium models; Pertur-;bation methods; Series expansions; Non-linear dierence equations.
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