Partial unit root and surplus-lag Granger causality testing: A Monte Carlo simulation study

Lingxiang Zhang

Communications in Statistics - Theory and Methods, 2017, vol. 46, issue 24, 12317-12323

Abstract: Previous literature has shown that the addition of an untested surplus-lag Granger causality test can provide highly robust to stationary, non stationary, long memory, and structural break processes in the forcing variables. This study extends this approach to the partial unit root framework by simulation. Results show good size and power. Therefore, the surplus-lag approach is also robust to partial unit root processes.

Date: 2017
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DOI: 10.1080/03610926.2017.1295077

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