Approximate Solutions to Dynamic Models - Linear Methods

SFB 649 Discussion Paper No. 2006-030

12 Pages Posted: 3 Aug 2006  

Harald Uhlig

University of Chicago - Department of Economics

Date Written: August 2006

Abstract

Linear Methods are often used to compute approximate solutions to dynamic models, as these models often cannot be solved analytically. Linear methods are very popular, as they can easily be implemented. Also, they provide a useful starting point for understanding more elaborate numerical methods. It shall be described here first for the example of a simple real business cycle model, including how to easily generate the log-linearized equations needed before solving the linear system. For a general framework, formulas are provided for calculating the recursive law of motion. The algorithm described here is implemented with the toolkit programs.

Keywords: numerical methods, linear solution method, loglinearization, dynamic stochastic general equilibrium methods, recursive law of motion

JEL Classification: C60, C61, C63, E32

Suggested Citation

Uhlig, Harald, Approximate Solutions to Dynamic Models - Linear Methods (August 2006). SFB 649 Discussion Paper No. 2006-030. Available at SSRN: https://ssrn.com/abstract=921357 or http://dx.doi.org/10.2139/ssrn.921357

Harald Uhlig (Contact Author)

University of Chicago - Department of Economics ( email )

1101 East 58th Street
Chicago, IL 60637
United States

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