Abstract
This study examines volatility and co-movement structures of coal and agricultural commodities index returns in China’s bioful era. After taking into account the periodicity of changes in coal and agriculture prices, we show that the Period-GARCH (P-GARCH), which captures the characteristics of two commodities is more adequate in contrast to the previously proposed models where the residuals were skewed and had kurtosis, here the resulting residuals are almost Gaussian. Finally, our proposed P-GARCH time-varying copula models indicate that the dependence between energy and agricultural commodities index returns is positive and increasingly stable.
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References
Hertel, T.W., Beckman, J.: Commodity price volatility in the biofuel era: An examination of the linkage between energy and agricultural markets(No. w16824). National Bureau of Economic Research (2011)
Qiu, H., Huang, J., Yang, J., Rozelle, S., Zhang, Y., Zhang, Y., Zhang, Y.: Bioethanol development in China and the potential impacts on its agricultural economy. Applied Energy 87(1), 76–83 (2010)
Hang, L., Tu, M.: The impacts of energy prices on energy intensity: evidence from China. Energy Policy 35(5), 2978–2988 (2007)
Gregg, J.S., Andres, R.J., Marland, G.: China: Emissions pattern of the world leader in CO2 emissions from fossil fuel consumption and cement production. Geophysical Research Letters 35(8), L08806 (2008)
Wright, T.: Price reform in the Chinese coal industry. Asia Research Centre (2009)
Fridley, D., Eden, N.: China Energy Databook 7.0 (2008)
Campiche, J.L., Bryant, H.L., Richardson, J.W., Outlaw, J.L.: Examining the evolving correspondence between petroleum prices and agricultural commodity prices. In: AAEA Proc., Portland, OR (July 2007)
Harri, A., Nalley, L., Hudson, D.: The relationship between oil, exchange rates, and commodity prices. Journal of Agricultural and Applied Economics 41(2), 501–510 (2009)
Zhang, Q., Reed, M.R.: Examining the impact of the world crude oil price on China’s agricultural commodity prices: the case of corn, soybean, and pork. In: 2008 Annual Meeting, Dallas, Texas (No. 6797), February 2-6. Southern Agricultural Economics Association (2008)
Wang, X.S., Xie, S.X.: How do Prices of Foreign Agricultural Products Affects Prices of Chinese Agricultural Products? Economic Research Journal 3 (2012)
Du, X., McPhail, L.L.: Inside the Black Box: the Price Linkage and Transmission between Energy and Agricultural Markets. Energy Journal-Cleveland 33(2), 171 (2012)
Baillie, R.T., Myers, R.J.: Bivariate GARCH estimation of the optimal commodity futures hedge. Journal of Applied Econometrics 6(2), 109–124 (1991)
Wu, C.C., Chung, H., Chang, Y.H.: The economic value of co-movement between oil price and exchange rate using copula-based GARCH models. Energy Economics 34(1), 270–282 (2012)
Bester, C.A.: Seasonal patterns in futures market volatility: a P-GARCH approach. Duke Journal of Economics 11, 65–102 (1999)
Engle, R.F.: Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica: Journal of the Econometric Society, 987–1007 (1982)
Bollerslev, T.: Generalized autoregressive conditional heteroskedasticity. Journal of Econometrics 31(3), 307–327 (1986)
Bollerslev, T., Ghysels, E.: Periodic autoregressive conditional heteroskedasticity. Journal of Business and Economic Statistics 14, 139–151 (1996)
Zhai, P., Pan, X.: Change in Extreme Temperature and Precipitation over Northern China During the Second Half of the 20th Century. Acta Geographica Sinica 58 (2003)
Koopman, S.J., Ooms, M., Carnero, M.A.: Periodic seasonal reg-ARFIMAGARCH models for daily electricity spot prices. Journal of the American Statistical Association 102(477), 16–27 (2007)
Winniford, M.: Real estate investment trusts and seasonal volatility: a periodic GARCH model. working paper, Duke University (2003)
Sklar, M.: Fonctions de rpartition n dimensions et leurs marges. Publications de lInstitut Statistique delUniversite de Paris 8, 229–231 (1959)
Jondeau, E., Rockinger, M.: The copula-garch model of conditional dependencies: an international stock market application. Journal of International Money and Finance 25(5), 827–853 (2006)
Lee, T.H., Long, X.: Copula-based multivariate garch model with uncorrelated dependent errors. Journal of Econometrics 150(2), 207–218 (2009)
Patton, A.J.: Modelling asymmetric exchange rate dependence. International Economic Review 47(2), 527–556 (2006)
Joe, H.: Multivariate models and dependence concepts, vol. 73. Chapman and Hall/CRC (1997)
Yan, J.: Enjoy the joy of copulas: with a package copula. Journal of Statistical Software 21(4), 1–21 (2007)
Bartram, M., Taylor, S.J., Wang, Y.H.: The euro and European financial market integration. Journal of Banking and Finance 51(5), 1461–1481 (2005)
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Xue, G., Sriboonchitta, S. (2014). Co-movement of Prices of Energy and Agricultural Commodities in Biofuel Era: A Period-GARCH Copula Approach. In: Huynh, VN., Kreinovich, V., Sriboonchitta, S. (eds) Modeling Dependence in Econometrics. Advances in Intelligent Systems and Computing, vol 251. Springer, Cham. https://doi.org/10.1007/978-3-319-03395-2_33
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DOI: https://doi.org/10.1007/978-3-319-03395-2_33
Publisher Name: Springer, Cham
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