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Detecting positive feedback in multivariate time series: The case of metal prices and US inflation

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  • Kyrtsou, Catherine
  • Labys, Walter C.

Abstract

The objective of this paper is to examine causality and feedback relationships between primary commodity prices and US inflation. To this end, the bivariate noisy Mackey–Glass process recently developed by Kyrtsou and Labys [Evidence for chaotic dependence between US inflation and commodity prices, J. Macroecon. 28(1) (2006) 256–266] has been applied to assess this relationship. Results obtained support evidence in favour of causality, which can help to identify the influences of speculative price behaviour on inflation.

Suggested Citation

  • Kyrtsou, Catherine & Labys, Walter C., 2007. "Detecting positive feedback in multivariate time series: The case of metal prices and US inflation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 377(1), pages 227-229.
    • Handle: RePEc:eee:phsmap:v:377:y:2007:i:1:p:227-229
    DOI: 10.1016/j.physa.2006.11.002
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    1. He, Xue-Zhong & Westerhoff, Frank H., 2005. "Commodity markets, price limiters and speculative price dynamics," Journal of Economic Dynamics and Control, Elsevier, vol. 29(9), pages 1577-1596, September.
    2. LeBaron, Blake, 2006. "Agent-based Computational Finance," Handbook of Computational Economics, in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 24, pages 1187-1233, Elsevier.
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    7. Colander,David (ed.), 2006. "Post Walrasian Macroeconomics," Cambridge Books, Cambridge University Press, number 9780521865487, September.
    8. Catherine Kyrtsou & Walter C. Labys & Michel Terraza, 2004. "Noisy chaotic dynamics in commodity markets," Empirical Economics, Springer, vol. 29(3), pages 489-502, September.
    9. Hommes, Cars H., 2006. "Heterogeneous Agent Models in Economics and Finance," Handbook of Computational Economics, in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 23, pages 1109-1186, Elsevier.
    10. Westerhoff, Frank & Reitz, Stefan, 2005. "Commodity price dynamics and the nonlinear market impact of technical traders: empirical evidence for the US corn market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 349(3), pages 641-648.
    11. Colander,David (ed.), 2006. "Post Walrasian Macroeconomics," Cambridge Books, Cambridge University Press, number 9780521684200, September.
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    Cited by:

    1. D. Hristu-Varsakelis & C. Kyrtsou, 2008. "Evidence for Nonlinear Asymmetric Causality in US Inflation, Metal, and Stock Returns," Discrete Dynamics in Nature and Society, Hindawi, vol. 2008, pages 1-7, May.
    2. Hammoudeh, Shawkat M. & Yuan, Yuan & McAleer, Michael & Thompson, Mark A., 2010. "Precious metals-exchange rate volatility transmissions and hedging strategies," International Review of Economics & Finance, Elsevier, vol. 19(4), pages 633-647, October.
    3. Kyrtsou, Catherine & Vorlow, Costas, 2009. "Modelling non-linear comovements between time series," Journal of Macroeconomics, Elsevier, vol. 31(1), pages 200-211, March.
    4. Al-Khazali, Osamah & Bouri, Elie & Roubaud, David & Zoubi, Taisier, 2017. "The impact of religious practice on stock returns and volatility," International Review of Financial Analysis, Elsevier, vol. 52(C), pages 172-189.
    5. Wen, Xiaoqian & Bouri, Elie & Roubaud, David, 2018. "Does oil product pricing reform increase returns and uncertainty in the Chinese stock market?," The Quarterly Review of Economics and Finance, Elsevier, vol. 68(C), pages 23-30.
    6. Elie Bouri & Naji Jalkh & Peter Molnár & David Roubaud, 2017. "Bitcoin for energy commodities before and after the December 2013 crash: diversifier, hedge or safe haven?," Applied Economics, Taylor & Francis Journals, vol. 49(50), pages 5063-5073, October.
    7. Kyrtsou, Catherine & Malliaris, Anastasios G. & Serletis, Apostolos, 2009. "Energy sector pricing: On the role of neglected nonlinearity," Energy Economics, Elsevier, vol. 31(3), pages 492-502, May.
    8. Ajmi, Ahdi Noomen & El Montasser, Ghassen & Nguyen, Duc Khuong, 2013. "Testing the relationships between energy consumption and income in G7 countries with nonlinear causality tests," Economic Modelling, Elsevier, vol. 35(C), pages 126-133.
    9. Wang, Jinghua & Ngene, Geoffrey M., 2020. "Does Bitcoin still own the dominant power? An intraday analysis," International Review of Financial Analysis, Elsevier, vol. 71(C).
    10. Chemkha, Rahma & BenSaïda, Ahmed & Ghorbel, Ahmed & Tayachi, Tahar, 2021. "Hedge and safe haven properties during COVID-19: Evidence from Bitcoin and gold," The Quarterly Review of Economics and Finance, Elsevier, vol. 82(C), pages 71-85.
    11. Abdul Rashid & Fazal Husain, 2013. "Capital Inflows, Inflation, and the Exchange Rate Volatility- An Investigation for Linear and Nonlinear Causal Linkages," The Pakistan Development Review, Pakistan Institute of Development Economics, vol. 52(3), pages 183-206.
    12. Kyrtsou, Catherine & Malliaris, Anastasios G., 2009. "The impact of information signals on market prices when agents have non-linear trading rules," Economic Modelling, Elsevier, vol. 26(1), pages 167-176, January.
    13. Ren, Yi-Shuai & Klein, Tony & Jiang, Yong & Ma, Chao-Qun & Yang, Xiao-Guang, 2024. "Dynamic spillovers among global oil shocks, economic policy uncertainty, and inflation expectation uncertainty under extreme shocks," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 91(C).
    14. Ngene, Geoffrey M. & Lee Kim, Yea & Wang, Jinghua, 2019. "Who poisons the pool? Time-varying asymmetric and nonlinear causal inference between low-risk and high-risk bonds markets," Economic Modelling, Elsevier, vol. 81(C), pages 136-147.
    15. Catherine Kyrtsou & Michel Terraza, 2010. "Seasonal Mackey–Glass–GARCH process and short-term dynamics," Empirical Economics, Springer, vol. 38(2), pages 325-345, April.
    16. Xu Zhang & Xiaoxing Liu & Jianqin Hang & Dengbao Yao, 2018. "The dynamic causality between commodity prices, inflation and output in China: a bootstrap rolling window approach," Applied Economics, Taylor & Francis Journals, vol. 50(4), pages 407-425, January.
    17. Karagianni Stella & Kyrtsou Catherine, 2011. "Analysing the Dynamics between U.S. Inflation and Dow Jones Index Using Non-Linear Methods," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 15(2), pages 1-25, March.
    18. Jinghua Wang & Geoffrey Ngene, 2018. "Symmetric and asymmetric nonlinear causalities between oil prices and the U.S. economic sectors," Review of Quantitative Finance and Accounting, Springer, vol. 51(1), pages 199-218, July.
    19. Kyrtsou, Catherine & Labys, Walter C., 2006. "Evidence for chaotic dependence between US inflation and commodity prices," Journal of Macroeconomics, Elsevier, vol. 28(1), pages 256-266, March.
    20. Rashid, Abdul, 2010. "Testing for nonlinear causation between capital inflows and domestic prices," MPRA Paper 26082, University Library of Munich, Germany.
    21. Kyrtsou, Catherine, 2008. "Re-examining the sources of heteroskedasticity: The paradigm of noisy chaotic models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(27), pages 6785-6789.
    22. Fernandez, Viviana, 2014. "Linear and non-linear causality between price indices and commodity prices," Resources Policy, Elsevier, vol. 41(C), pages 40-51.

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