Asymptotics of locally interacting Markov chains with global signals
Ulrich Horst
No 2001,29, SFB 373 Discussion Papers from Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes
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.
Keywords: Markov chains on infinite product spaces; contraction techniques; Gibbs measures; local asymptotic loss of memory (search for similar items in EconPapers)
Date: 2001
References: Add references at CitEc
Citations: View citations in EconPapers (4)
Downloads: (external link)
https://www.econstor.eu/bitstream/10419/62730/1/724884599.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:zbw:sfb373:200129
Access Statistics for this paper
More papers in SFB 373 Discussion Papers from Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes Contact information at EDIRC.
Bibliographic data for series maintained by ZBW - Leibniz Information Centre for Economics ().