Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/62203 
Authors: 
Year of Publication: 
2000
Series/Report no.: 
SFB 373 Discussion Paper No. 2000,5
Publisher: 
Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes, Berlin
Abstract: 
In this paper we consider the stochastic sequence {Pt}E N defined recursively by the linear relation Pt+1 = At Pt + Bt in a random environment which is described by the non-stationary process V = {(At, Bt) t E N.. We formulate sufficient conditions on v which ensure that the finite-dimensional distributions of {Pt} E N converge weakly to the finite-dimensional distribution of a unique stationary process. If the driving sequence v has a nice tail behaviour, then we can establish a global convergence result. This extends results of Brandt (1986) and Borovkov (1998) from the stationary to the non-stationary ease.
Subjects: 
stochastic difference equation
stochastic stability
ergodicity
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

Files in This Item:
File
Size
339.59 kB





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.