Testing for non-causality by using the Autoregressive Metric

A new non-causality test based on the notion of distance between ARMA models is proposed in this paper. The advantage of this test is that it can be used in possible integrated and cointegrated systems, without pre-testing for unit roots and cointegration. The Monte Carlo experiments indicate that the proposed method performs reasonably well in nite samples. The empirical relevance of the test is illustrated via two applications.

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Year of publication:	2011
Authors:	Di Iorio, Francesca ; Triacca, Umberto
Institutions:	Volkswirtschaftliche Fakultät, Ludwig-Maximilians-Universität München
Subject:	AR metric \| Bootstrap test \| Granger non-causality \| VAR

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Extent:	application/pdf
Series:	MPRA Paper.
Type of publication:	Book / Working Paper
Classification:	C12 - Hypothesis Testing ; C15 - Statistical Simulation Methods; Monte Carlo Methods ; C22 - Time-Series Models
Source:	RePEc - Research Papers in Economics

Persistent link: https://ebvufind01.dmz1.zbw.eu/10008869266