Spurious Granger causality between a broken-trend stationary process and a stochastic trend process

Lingxiang Zhang*, Xiaotong Zhang

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

This paper examines spurious Granger causality between a trend stationary process with structural breaks and a stochastic trend process. Monte Carlo simulations show that whether or not there are deterministic variables in the testing models, the sample size and the parameter values of the data generation process can affect the empirical frequencies of spurious Granger causality relations in different degrees. The analysis also points out that an alternative rank-based causality test method can avoid the risk of spurious causality to some extent by adopting an intercept and deterministic trend term in the testing regressions.

Original languageEnglish
Pages (from-to)1673-1681
Number of pages9
JournalMathematics and Computers in Simulation
Volume81
Issue number8
DOIs
Publication statusPublished - Apr 2011
Externally publishedYes

Keywords

  • Granger causality
  • Spurious rejection
  • Stochastic trend
  • Structural break

Fingerprint

Dive into the research topics of 'Spurious Granger causality between a broken-trend stationary process and a stochastic trend process'. Together they form a unique fingerprint.

Cite this