Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/62730 
Authors: 
Year of Publication: 
2001
Series/Report no.: 
SFB 373 Discussion Paper No. 2001,29
Publisher: 
Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes, Berlin
Abstract: 
We study the long run behaviour of interactive Markov chains on infinite product spaces. The behaviour at a single site is influenced by the local situation in some neighborhood and by a random signal about the average situation throughout the whole system. The asymptotic behaviour of such Markov chains is analyzed on the microscopic level and on the macroscopic level of empirical fields. We give sufficient conditions for convergence on the macroscopic level. Combining a convergence result from the theory of random systems with complete connections with a perturbation of the Dobrushin-Vasserstein contraction technique we show that macroscopic convergence implies that the underlying Microscopic process has local asymptotic loss of memory.
Subjects: 
Markov chains on infinite product spaces
contraction techniques
Gibbs measures
local asymptotic loss of memory
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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