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Connectedness Between Natural Gas Price and BRICS Exchange Rates: Evidence from Time and Frequency Domains

Author

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  • Yijin He

    (Graduate School of Economics, Kobe University, 2-1, Rokkodai, Nada-Ku, Kobe 657-8501, Japan)

  • Tadahiro Nakajima

    (Graduate School of Economics, Kobe University, 2-1, Rokkodai, Nada-Ku, Kobe 657-8501, Japan
    The Kansai Electric Power Company, Incorporated, 6-16, Nakanoshima 3-chome, Kita-Ku, Osaka 530-8270, Japan)

  • Shigeyuki Hamori

    (Graduate School of Economics, Kobe University, 2-1, Rokkodai, Nada-Ku, Kobe 657-8501, Japan)

Abstract

In this paper, we investigate the connectedness between natural gas and BRICS (Brazil, Russia, India, China, and South Africa)’s exchange rate in terms of time and frequency. This empirical work is based on the approach of connectedness proposed by Diebold and Yilmaz, who provided an effective way of valuing how much variation in one variable is responsible for the value of other variables, and the method proposed by Baruník and Křehlík, who decomposed the results from Diebold and Yilmaz into different frequencies. We also use the rolling-window method to conduct time-varying analysis. The data used in this paper are from 23 August 2010 to 20 June 2019. We find that the natural gas price hardly influences BRICS’s exchange rates, which provides an important practical implication for policymakers, especially in oil-dependent countries.

Suggested Citation

  • Yijin He & Tadahiro Nakajima & Shigeyuki Hamori, 2019. "Connectedness Between Natural Gas Price and BRICS Exchange Rates: Evidence from Time and Frequency Domains," Energies, MDPI, vol. 12(20), pages 1-28, October.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:20:p:3970-:d:278100
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    References listed on IDEAS

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    1. Diebold, Francis X. & Yılmaz, Kamil, 2014. "On the network topology of variance decompositions: Measuring the connectedness of financial firms," Journal of Econometrics, Elsevier, vol. 182(1), pages 119-134.
    2. Lovcha, Yuliya & Perez-Laborda, Alejandro, 2020. "Dynamic frequency connectedness between oil and natural gas volatilities," Economic Modelling, Elsevier, vol. 84(C), pages 181-189.
    3. Zivot, Eric & Andrews, Donald W K, 2002. "Further Evidence on the Great Crash, the Oil-Price Shock, and the Unit-Root Hypothesis," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 25-44, January.
    4. Stiassny, Alfred, 1996. "A Spectral Decomposition for Structural VAR Models," Empirical Economics, Springer, vol. 21(4), pages 535-555.
    5. Lundgren, Amanda Ivarsson & Milicevic, Adriana & Uddin, Gazi Salah & Kang, Sang Hoon, 2018. "Connectedness network and dependence structure mechanism in green investments," Energy Economics, Elsevier, vol. 72(C), pages 145-153.
    6. Koop, Gary & Pesaran, M. Hashem & Potter, Simon M., 1996. "Impulse response analysis in nonlinear multivariate models," Journal of Econometrics, Elsevier, vol. 74(1), pages 119-147, September.
    7. Francis X. Diebold & Kamil Yilmaz, 2009. "Measuring Financial Asset Return and Volatility Spillovers, with Application to Global Equity Markets," Economic Journal, Royal Economic Society, vol. 119(534), pages 158-171, January.
    8. Pesaran, H. Hashem & Shin, Yongcheol, 1998. "Generalized impulse response analysis in linear multivariate models," Economics Letters, Elsevier, vol. 58(1), pages 17-29, January.
    9. Awartani, Basel & Aktham, Maghyereh & Cherif, Guermat, 2016. "The connectedness between crude oil and financial markets: Evidence from implied volatility indices," Journal of Commodity Markets, Elsevier, vol. 4(1), pages 56-69.
    10. Jain, Anshul & Biswal, P.C., 2016. "Dynamic linkages among oil price, gold price, exchange rate, and stock market in India," Resources Policy, Elsevier, vol. 49(C), pages 179-185.
    11. Andrieș, Alin Marius & Ihnatov, Iulian & Tiwari, Aviral Kumar, 2014. "Analyzing time–frequency relationship between interest rate, stock price and exchange rate through continuous wavelet," Economic Modelling, Elsevier, vol. 41(C), pages 227-238.
    12. Singh, Vipul Kumar & Nishant, Shreyank & Kumar, Pawan, 2018. "Dynamic and directional network connectedness of crude oil and currencies: Evidence from implied volatility," Energy Economics, Elsevier, vol. 76(C), pages 48-63.
    13. Brahmasrene, Tantatape & Huang, Jui-Chi & Sissoko, Yaya, 2014. "Crude oil prices and exchange rates: Causality, variance decomposition and impulse response," Energy Economics, Elsevier, vol. 44(C), pages 407-412.
    14. Diebold, Francis X. & Yilmaz, Kamil, 2015. "Financial and Macroeconomic Connectedness: A Network Approach to Measurement and Monitoring," OUP Catalogue, Oxford University Press, number 9780199338306.
    15. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
    16. Robin L. Lumsdaine & David H. Papell, 1997. "Multiple Trend Breaks And The Unit-Root Hypothesis," The Review of Economics and Statistics, MIT Press, vol. 79(2), pages 212-218, May.
    17. Perron, Pierre, 1989. "The Great Crash, the Oil Price Shock, and the Unit Root Hypothesis," Econometrica, Econometric Society, vol. 57(6), pages 1361-1401, November.
    18. Geweke, John F, 1986. "The Superneutrality of Money in the United States: An Interpretation of the Evidence," Econometrica, Econometric Society, vol. 54(1), pages 1-21, January.
    19. Diebold, Francis X. & Yilmaz, Kamil, 2012. "Better to give than to receive: Predictive directional measurement of volatility spillovers," International Journal of Forecasting, Elsevier, vol. 28(1), pages 57-66.
    20. Chen, Shiu-Sheng & Chen, Hung-Chyn, 2007. "Oil prices and real exchange rates," Energy Economics, Elsevier, vol. 29(3), pages 390-404, May.
    21. Ji, Qiang & Geng, Jiang-Bo & Tiwari, Aviral Kumar, 2018. "Information spillovers and connectedness networks in the oil and gas markets," Energy Economics, Elsevier, vol. 75(C), pages 71-84.
    22. Maghyereh, Aktham I. & Awartani, Basel & Bouri, Elie, 2016. "The directional volatility connectedness between crude oil and equity markets: New evidence from implied volatility indexes," Energy Economics, Elsevier, vol. 57(C), pages 78-93.
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    Cited by:

    1. Tadahiro Nakajima & Yuki Toyoshima, 2020. "Examination of the Spillover Effects among Natural Gas and Wholesale Electricity Markets Using Their Futures with Different Maturities and Spot Prices," Energies, MDPI, vol. 13(7), pages 1-14, March.
    2. Xie He & Tetsuya Takiguchi & Tadahiro Nakajima & Shigeyuki Hamori, 2020. "Spillover effects between energies, gold, and stock: the United States versus China," Energy & Environment, , vol. 31(8), pages 1416-1447, December.
    3. Ioannis Katsampoxakis & Apostolos Christopoulos & Petros Kalantonis & Vasileios Nastas, 2022. "Crude Oil Price Shocks and European Stock Markets during the COVID-19 Period," Energies, MDPI, vol. 15(11), pages 1-14, June.
    4. Anna A. Gainetdinova, 2023. "Asymmetric Impact of Geopolitical Risk and Economic Policy Uncertainty on Russian Ruble Exchange Rate," Journal of Applied Economic Research, Graduate School of Economics and Management, Ural Federal University, vol. 22(2), pages 270-293.
    5. Thobekile Qabhobho & Anokye M. Adam & Emmanuel Asafo-Adjei, 2023. "Do Local and International Shocks Matter in the Interconnectedness amid Exchange Rates and Energy Commodities? Insights into BRICS Economies," International Journal of Energy Economics and Policy, Econjournals, vol. 13(6), pages 666-678, November.

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