Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/168031
Authors: 
Chatelain, Jean-Bernard
Ralf, Kirsten
Year of Publication: 
2017
Abstract: 
This algorithm extends Ljungqvist and Sargent (2012) algorithm of Stackelberg dynamic game to the case of dynamic stochastic general equilibrium models including exogenous forcing variables. It is based Anderson, Hansen, McGrattan, Sargent (1996) discounted augmented linear quadratic regulator. It adds an intermediate step in solving a Sylvester equation. Forward-looking variables are also optimally anchored on forcing variables. This simple algorithm calls for already programmed routines for Ricatti, Sylvester and Inverse matrix in Matlab and Scilab. A final step using a change of basis vector computes a vector auto regressive representation including Ramsey optimal policy rule function of lagged observable variables, when the exogenous forcing variables are not observable.
Subjects: 
Stackelberg dynamic game
Ramsey optimal policy
Augmented linear quadratic regulator
Algorithm
JEL: 
C61
C62
E47
E52
E58
Document Type: 
Preprint

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