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Non-causality due to irrelevant lag polynomials

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  • Kul Luintel

Abstract

This letter illustrates that Granger causality tests tend to be sensitive to irrelevant lag polynomials and could lead to wrong inference of non-causality. In view of the little insight one gets from economic theory about short-run dynamics, it suggests exclusion restrictions prior to causality testing.

Suggested Citation

  • Kul Luintel, 1999. "Non-causality due to irrelevant lag polynomials," Applied Economics Letters, Taylor & Francis Journals, vol. 6(1), pages 17-20.
  • Handle: RePEc:taf:apeclt:v:6:y:1999:i:1:p:17-20
    DOI: 10.1080/135048599353807
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    Cited by:

    1. Andrew McKay & Sarmistha Pal, 2004. "Relationships between Household Consumption and Inequality in the Indian States," Journal of Development Studies, Taylor & Francis Journals, vol. 40(5), pages 65-90.
    2. R. Scott Hacker & Abdulnasser Hatemi-J, 2006. "Tests for causality between integrated variables using asymptotic and bootstrap distributions: theory and application," Applied Economics, Taylor & Francis Journals, vol. 38(13), pages 1489-1500.
    3. Andrew McKay & Sarmistha Pal, 2003. "Relationships between consumption and inequality in the Indian states," Development and Comp Systems 0309005, University Library of Munich, Germany.
    4. Laing, Andrew R. & Nolan, James F., 2009. "Price Dynamics and Market Structure in Transportation: For-Hire Grain Trucking Along the Alberta- Saskatchewan Border," 50th Annual Transportation Research Forum, Portland, Oregon, March 16-18, 2009 207599, Transportation Research Forum.
    5. Cook, Steven, 2007. "On the relationship between mergers and economic activity: Evidence from an optimised hybrid method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 379(2), pages 628-634.
    6. Nezir Kose & Nuri Ucar, 2006. "Effect of cross correlations in error terms on the model selection criteria for the stationary VAR process," Applied Economics Letters, Taylor & Francis Journals, vol. 13(4), pages 223-228.

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