Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/25113 
Authors: 
Year of Publication: 
2006
Series/Report no.: 
SFB 649 Discussion Paper No. 2006,030
Publisher: 
Humboldt University of Berlin, Collaborative Research Center 649 - Economic Risk, Berlin
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 available per http://www.wiwi.hu-berlin.de/wpol/html/toolkit.htm .
Subjects: 
numerical methods
linear solution method
loglinearization
dynamic stochastic general equilibrium methods
recursive law of motion
JEL: 
C60
C61
C63
E32
Document Type: 
Working Paper

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