Analyzing Associations in Multivariate Binary Time Series

We analyze multivariate binary time series using a mixed parameterization in terms of the conditional expectations given the past and the pairwise canonical interactions among contemporaneous variables. This allows consistent inference on the influence of past variables even if the contemporaneous associations are misspecified. Particularly, we can detect and test Granger non-causalities since they correspond to zero parameter values.

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Year of publication:	2006
Authors:	Fried, Roland ; Kuhls, Silvia ; Molina, Isabel
Publisher:	Dortmund : Universität Dortmund, Sonderforschungsbereich 475 - Komplexitätsreduktion in Multivariaten Datenstrukturen

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Series:	Technical Report ; 2006,18
Type of publication:	Book / Working Paper
Type of publication (narrower categories):	Working Paper
Language:	English
Other identifiers:	515579882 [GVK] hdl:10419/22661 [Handle] RePEc:zbw:sfb475:200618 [RePEc]
Source:	EconStor

Persistent link: https://www.econbiz.de/10010296732