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Geometric Ergodicity of Binary Autoregressive Models with Exogenous Variables

  • In this paper we introduce a binary autoregressive model. In contrast to the typical autoregression framework, we allow the conditional distribution of the observed process to depend on past values of the time series and some exogenous variables. Such processes have potential applications in econometrics, medicine and environmental sciences. In this paper, we establish stationarity and geometric ergodicity of these processes under suitable conditions on the parameters of the model. Such properties are important for understanding the stability properties of the model as well as for deriving the asymptotic behavior of the parameter estimators.

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Author:Claudia Kirch, Joseph Tadjuidje Kamgaing
URN (permanent link):urn:nbn:de:hbz:386-kluedo-36475
Document Type:Working Paper
Language of publication:English
Publication Date:2013/11/12
Year of Publication:2013
Publishing Institute:Technische Universität Kaiserslautern
Date of the Publication (Server):2013/11/13
Tag:Binary; Ergodic; Exogenous; Time Series
Number of page:5
Faculties / Organisational entities:Fachbereich Mathematik
DDC-Cassification:5 Naturwissenschaften und Mathematik / 510 Mathematik
MSC-Classification (mathematics):00-XX GENERAL
Licence (German):Standard gemäß KLUEDO-Leitlinien vom 10.09.2012