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VAR-based Granger-causality test in the presence of instabilities

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Abstract

In this article, we review Granger-causality tests robust to the presence of instabilities in a Vector Autoregressive framework. We also introduce the gcrobustvar command, which illustrates the procedure in Stata. In the presence of instabilities, the Granger-causality robust test is more powerful than the traditional Granger-causality test.

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  • Yiru Wang & Barbara Rossi, 2019. "VAR-based Granger-causality test in the presence of instabilities," Economics Working Papers 1642, Department of Economics and Business, Universitat Pompeu Fabra.
    • Handle: RePEc:upf:upfgen:1642
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    2. Demirer, Riza & Gupta, Rangan & Salisu, Afees A. & van Eyden, Reneé, 2023. "Firm-level business uncertainty and the predictability of the aggregate U.S. stock market volatility during the COVID-19 pandemic," The Quarterly Review of Economics and Finance, Elsevier, vol. 88(C), pages 295-302.
    3. Chevaughn van der Westhuizen & Renee van Eyden & Goodness C. Aye, 2022. "Is Inflation Uncertainty a Self-Fulfilling Prophecy? The Inflation-Inflation Uncertainty Nexus and Inflation Targeting in South Africa," Working Papers 202254, University of Pretoria, Department of Economics.
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    More about this item

    Keywords

    gcrobustvar; Granger-causality; VAR; instability; structural breaks; local projections;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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