A general framework for testing the Granger noncausality hypothesis

In this paper, new noncausality tests relying on a general nonlinear framework are proposed and their performance studied by a Monte Carlo experiment and a variety of nonlinear artificial series. Two of the tests are based on a Taylor expansion of the nonlinear model around a given point in the sample space. Yet another test is based on artificial neural networks. The tests appear to be well-sized and have good power properties.

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Year of publication:	1999-11-09
Authors:	Péguin-Feissolle, Anne ; Teräsvirta, Timo
Institutions:	Economics Institute for Research (SIR), Handelshögskolan i Stockholm
Subject:	Hypothesis testing \| causality \| artificial neural networks \| nonlinearity

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Series:	SSE/EFI Working Paper Series in Economics and Finance.
Type of publication:	Book / Working Paper
Notes:	Published as Péguin-Feissolle, Anne, Timo Teräsvirta and Birgit Strikholm, 'Testing the Granger noncausality hypothesis in stationary nonlinear models of unknown functional form. ' in Communications in Statistics – Simulation and Computation 42, 1063-1087, 2013, pages 1063-1087. The text is part of a series SSE/EFI Working Paper Series in Economics and Finance Number 343 22 pages
Classification:	C12 - Hypothesis Testing ; C22 - Time-Series Models ; C51 - Model Construction and Estimation
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10005207201