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Assessment of resampling methods for causality testing: A note on the US inflation behavior

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  • Angeliki Papana
  • Catherine Kyrtsou
  • Dimitris Kugiumtzis
  • Cees Diks

Abstract

Different resampling methods for the null hypothesis of no Granger causality are assessed in the setting of multivariate time series, taking into account that the driving-response coupling is conditioned on the other observed variables. As appropriate test statistic for this setting, the partial transfer entropy (PTE), an information and model-free measure, is used. Two resampling techniques, time-shifted surrogates and the stationary bootstrap, are combined with three independence settings (giving a total of six resampling methods), all approximating the null hypothesis of no Granger causality. In these three settings, the level of dependence is changed, while the conditioning variables remain intact. The empirical null distribution of the PTE, as the surrogate and bootstrapped time series become more independent, is examined along with the size and power of the respective tests. Additionally, we consider a seventh resampling method by contemporaneously resampling the driving and the response time series using the stationary bootstrap. Although this case does not comply with the no causality hypothesis, one can obtain an accurate sampling distribution for the mean of the test statistic since its value is zero under H0. Results indicate that as the resampling setting gets more independent, the test becomes more conservative. Finally, we conclude with a real application. More specifically, we investigate the causal links among the growth rates for the US CPI, money supply and crude oil. Based on the PTE and the seven resampling methods, we consistently find that changes in crude oil cause inflation conditioning on money supply in the post-1986 period. However this relationship cannot be explained on the basis of traditional cost-push mechanisms.

Suggested Citation

  • Angeliki Papana & Catherine Kyrtsou & Dimitris Kugiumtzis & Cees Diks, 2017. "Assessment of resampling methods for causality testing: A note on the US inflation behavior," PLOS ONE, Public Library of Science, vol. 12(7), pages 1-20, July.
  • Handle: RePEc:plo:pone00:0180852
    DOI: 10.1371/journal.pone.0180852
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    References listed on IDEAS

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    1. Christoph Schmidt & Britta Pester & Nicole Schmid-Hertel & Herbert Witte & Axel Wismüller & Lutz Leistritz, 2016. "A Multivariate Granger Causality Concept towards Full Brain Functional Connectivity," PLOS ONE, Public Library of Science, vol. 11(4), pages 1-25, April.
    2. Olivier J. Blanchard & Jordi Galí, 2007. "The Macroeconomic Effects of Oil Price Shocks: Why Are the 2000s so Different from the 1970s?," NBER Chapters, in: International Dimensions of Monetary Policy, pages 373-421, National Bureau of Economic Research, Inc.
    3. Diks Cees & Manzan Sebastiano, 2002. "Tests for Serial Independence and Linearity Based on Correlation Integrals," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 6(2), pages 1-22, July.
    4. Okyu Kwon & Jae-Suk Yang, 2008. "Information flow between stock indices," Papers 0802.1747, arXiv.org.
    5. Alberto Porta & Luca Faes & Giandomenico Nollo & Vlasta Bari & Andrea Marchi & Beatrice De Maria & Anielle C M Takahashi & Aparecida M Catai, 2015. "Conditional Self-Entropy and Conditional Joint Transfer Entropy in Heart Period Variability during Graded Postural Challenge," PLOS ONE, Public Library of Science, vol. 10(7), pages 1-21, July.
    6. Daniel Yasumasa Takahashi & Luiz Antonio Baccal & Koichi Sameshima, 2007. "Connectivity Inference between Neural Structures via Partial Directed Coherence," Journal of Applied Statistics, Taylor & Francis Journals, vol. 34(10), pages 1259-1273.
    7. Papana, A. & Kyrtsou, K. & Kugiumtzis, D. & Diks, C.G.H., 2014. "Assessment of Resampling Methods for Causality Testing," CeNDEF Working Papers 14-08, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
    8. Fatimah Abdul Razak & Henrik Jeldtoft Jensen, 2014. "Quantifying ‘Causality’ in Complex Systems: Understanding Transfer Entropy," PLOS ONE, Public Library of Science, vol. 9(6), pages 1-14, June.
    9. Kilian, Lutz, 2010. "Oil price volatility: Origins and effects," WTO Staff Working Papers ERSD-2010-02, World Trade Organization (WTO), Economic Research and Statistics Division.
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