An Anticipative Feedback Solution for Infinite-Horizon Linear-Quadratic Dynamic Stackelberg Games

Baoline Chen and Peter Zadrozny
Authors registered in the RePEc Author Service: Peter A. Zadrozny and Baoline Chen

No 110, Computing in Economics and Finance 2001 from Society for Computational Economics

Abstract: The purpose of the paper is to derive and illustrate a new suboptimal-consistent feedback solution for infinite-horizon linear-quadratic dynamic Stackelberg games which is in the same solution space as the infinite-horizon dynamic programming feedback solution, but which puts the leader in a preferred equilibrium position. The idea for the solution comes from Kydland's (1977) suggestion to derive a consistent feedback solution (where "feedback" is understood in the general sense of setting a current control vector as a function of a predetermined state vector) for an infinite-horizon linear-quadratic dynamic Stackelberg game by varying coefficients in players' linear constant-coefficient decision rules. The proposed solution is derived for discrete- and continuous-time versions of the game and is called the anticipative feedback (AF) solution. The AF solution is illustrated with a numerical example of a duopoly model.

Keywords: noncooperative dynamic games; solving Riccati-type nonlinear algebraic equations (search for similar items in EconPapers)
JEL-codes: C61 C63 C73 (search for similar items in EconPapers)
Date: 2001-04-01
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
Journal Article: An anticipative feedback solution for the infinite-horizon, linear-quadratic, dynamic, Stackelberg game (2002)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:sce:scecf1:110

Access Statistics for this paper

More papers in Computing in Economics and Finance 2001 from Society for Computational Economics Contact information at EDIRC.
Bibliographic data for series maintained by Christopher F. Baum ().