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Persistence-robust Granger causality testing

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Author Info

  • Dietmar Bauer

    ()
    (Arsenal Research, Vienna, Austria)

  • Alex Maynard

    ()
    (Department of Economics, University of Guelph, Canada.)

Abstract

The observed persistence common in economic time series may arise from a variety of models that are not always distinguished with confidence in practice, yet play an important role in model specification and second stage inference procedures. Previous literature has introduced causality tests with conventional limiting distributions in I(0)/I(1)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. Building on this approach, but using an infinite order VARX framework, we 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 Chi-Squared null limiting distribution. No first stage testing or estimation is required and known lag orders are not assumed.

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Bibliographic Info

Paper provided by University of Guelph, Department of Economics and Finance in its series Working Papers with number 1011.

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Length: 43 pages
Date of creation: 29 Jun 2010
Date of revision:
Handle: RePEc:gue:guelph:2010-11.

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Related research

Keywords: Granger causality; surplus lag; nonstationary; VAR; local-to-unity; long-memory;

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References

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Citations

Blog mentions

As found by EconAcademics.org, the blog aggregator for Economics research:
  1. Surplus-Lag Granger Causality Testing
    by Dave Giles in Econometrics Beat: Dave Giles' Blog on 2012-04-18 16:13:00
  2. Surplus-Lag Granger Causality Testing
    by Dave Giles in Econometrics Beat: Dave Giles' Blog on 2012-04-18 16:13:00
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Cited by:
  1. 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.

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