EconPapers    
Economics at your fingertips  
 

New Phenomena Identified in a Stochastic Dynamic Macroeconometric Model: A Bifurcation Perspective

William Barnett and Yijun He

No 145, Computing in Economics and Finance 2004 from Society for Computational Economics

Abstract: In this paper, we consider new bifurcation phenomena in a class of stochastic dynamic macroeconometric models as represented by the stochastic model developed by Leeper and Sims (1994). This model serves as a prototype that could be suitable for monetary policy analysis although the complexity of the model makes any attempt of analytical analysis a difficult task. Leeper and Sims model consists of differential equations with a set of algebraic constraints. Our analysis reveals that singularity occurs within a small neighborhood of estimated parameter values. Singularity boundary is determined. When the parameter values are close to the singularity boundary, one eigenvalue of the linearized part of the model rapidly moves to infinity while others remain bounded, implying nearly instantaneous response of some variables to changes of other variables. On the singularity boundary, the number of differential equations will decrease while the number of algebraic constraints will increase. Such change in the order of dynamics is a new phenomenon in macroeconometric models. We shall determine the singularity-induced bifurcation and its effect on model behavior.

Keywords: stability; bifurcation; macroeconometric systems (search for similar items in EconPapers)
JEL-codes: C32 C52 E61 (search for similar items in EconPapers)
Date: 2004-08-11
References: Add references at CitEc
Citations: View citations in EconPapers (4)

Downloads: (external link)
http://repec.org/sce2004/up.13019.1077747552.pdf (application/pdf)

Related works:
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:scecf4:145

Access Statistics for this paper

More papers in Computing in Economics and Finance 2004 from Society for Computational Economics Contact information at EDIRC.
Bibliographic data for series maintained by Christopher F. Baum ().

 
Page updated 2025-03-22
Handle: RePEc:sce:scecf4:145