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Persistence-robust surplus-lag Granger causality testing

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Author Info

  • Bauer, Dietmar
  • Maynard, Alex

Abstract

Previous literature has introduced causality tests with conventional limiting distributions in I(0)/I(1) vector autoregressive (VAR) models with unknown integration orders, based on an additional surplus lag in the specification of the estimated equation, which is not included in the tests. By extending this surplus lag approach to an infinite order VARX framework, we show that it can provide a highly persistence-robust Granger causality test that accommodates i.a stationary, nonstationary, local-to-unity, long-memory, and certain (unmodelled) structural break processes in the forcing variables within the context of a single χ2 null limiting distribution.

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Bibliographic Info

Article provided by Elsevier in its journal Journal of Econometrics.

Volume (Year): 169 (2012)
Issue (Month): 2 ()
Pages: 293-300

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Handle: RePEc:eee:econom:v:169:y:2012:i:2:p:293-300

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Web page: http://www.elsevier.com/locate/jeconom

Related research

Keywords: Granger causality; VAR; Long-memory; Structural breaks; Forward rate unbiasedness;

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References

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Cited by:
  1. Stern, David I. & Enflo, Kerstin, 2013. "Causality between energy and output in the long-run," Energy Economics, Elsevier, vol. 39(C), pages 135-146.
  2. Chevallier, Julien & Sévi, Benoît, 2012. "On the volatility–volume relationship in energy futures markets using intraday data," Energy Economics, Elsevier, vol. 34(6), pages 1896-1909.
  3. repec:hal:cesptp:hal-00984827 is not listed on IDEAS

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