Testing the Granger Noncausality Hypothesis in Stationary Nonlinear Models of Unknown Functional Form

DOI10.1080/03610918.2012.661500zbMath1433.62063OpenAlexW1560195474MaRDI QIDQ4921616

Timo Teräsvirta, Anne Peguin-Feissolle, Birgit Strikholm

Publication date: 13 May 2013

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: http://hdl.handle.net/10419/56089

zbMATH Keywords

hypothesis testingnonlinearityGranger causality

Mathematics Subject Classification ID

Parametric hypothesis testing (62F03)

Related Items (2)

Testing for misspecification in the short-run component of GARCH-type models ⋮ Nonlinear Correlation Analysis of Time Series Based on Complex Network Similarity

Cites Work

• Unnamed Item
• Unnamed Item
• Goodness-of-fit for allocation models
• A low-dimension portmanteau test for non-linearity
• A non-parametric approach to non-linear causality testing
• Analyzing multiple nonlinear time series with extended Granger causality
• MULTIPLE BILINEAR TIME SERIES MODELS
• Testing linearity against smooth transition autoregressive models
• Advertising and Aggregate Consumption: An Analysis of Causality
• Testing for Higher Order Serial Correlation in Regression Equations when the Regressors Include Lagged Dependent Variables
• A test for independence based on the correlation dimension
• A SIMPLE VARIABLE SELECTION TECHNIQUE FOR NONLINEAR MODELS
• Miscellanea. A note on tests for nonlinearity in a vector time series
• Investigating Causal Relations by Econometric Models and Cross-spectral Methods

This page was built for publication: Testing the Granger Noncausality Hypothesis in Stationary Nonlinear Models of Unknown Functional Form