Second-order approximation of dynamic models without the use of tensors

Paul Gomme and Paul Klein

Working Papers from Concordia University, Department of Economics

Abstract: Several approaches to finding the second-order approximation to a dynamic model have been proposed recently. This paper differs from the existing literature in that it makes use of the Magnus and Neudecker (1999) definition of the Hessian matrix. The key result is a linear system of equations that characterizes the second-order coefficients. No use is made of multi-dimensional arrays or tensors, a practical implication of which is that it is much easier to transcribe the mathematical representation of the solution into usable computer code. Matlab code is available from http://paulklein.se/codes.htm; Fortran 90 code is available from http://paulgomme.github.io/

Keywords: Solving dynamic models; second-order approximation (search for similar items in EconPapers)
JEL-codes: C63 E0 (search for similar items in EconPapers)
Pages: 27 pages
Date: 2009-02-17, Revised 2010-04-28
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (25)

Downloads: (external link)
http://paulgomme.github.io/secondorder.pdf (application/pdf)

Related works:
Journal Article: Second-order approximation of dynamic models without the use of tensors (2011)
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Persistent link: https://EconPapers.repec.org/RePEc:crd:wpaper:09004

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