Environmental and Resource Economics Review (자원ㆍ환경경제연구)

Korean Resource Economics Association (한국자원경제학회)
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Analysis on the Dependence Structure between Energy Price and Economic Uncertainty Using Copula Model

Copula 모형을 이용한 에너지 가격과 경제적 불확실성 사이의 의존관계 분석

  • Kim, Bu-Kwon (Department of Economics, Pusan National University) ;
  • Choi, Ki-Hong (Institute of Economics and International Trade, Pusan National University) ;
  • Yoon, Seong-Min (Department of Economics, Pusan National University)
  • 김부권 (부산대학교 대학원 경제학과) ;
  • 최기홍 (부산대학교 경제통상연구원) ;
  • 윤성민 (부산대학교 경제학부)
  • Received : 2020.02.18
  • Accepted : 2020.05.06
  • Published : 2020.06.30
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Abstract

This study analyzes the dependence structure between energy (crude oil, natural gas, coal) prices and economic (real and financial) uncertainty. Summary of the results of the dependence structure between energy prices and economic uncertainty analysis is as follows. First, the results of model selection show that the BB7 copula model for the pair of crude oil price and economic uncertainty, the Joe copula model for the pair of natural gas price and economic uncertainty, and the Clayton copula model for the pair of coal price and economic uncertainty were chosen. Second, looking at the dependency structure, it showed that the pair of energy (crude oil, natural gas, coal) prices and real market uncertainty show positive dependence. Whereas, the only pair of financial market uncertainty-crude oil price shows positive dependency. In particular, crude oil price was found to have the greatest dependence on economic uncertainty. Third, looking at the results of tail dependency, the pair of real market uncertainty-crude oil price and pair of real market uncertainty-natural gas price have an asymmetric relationship with the upper tail dependency. It can be seen that the only pair of financial market uncertainty-crude oil represents asymmetric relationships with the upper tail dependencies. In other words, combinations with asymmetric relationships have shown strong dependence when negative extreme events occur. On the other hand, tail dependence between economic uncertainty and coal price be not found.

본 연구는 에너지(석유, 천연가스, 석탄) 가격과 경제적(실물 및 금융) 불확실성 사이의 의존성 구조를 분석하였다. Copula 모형을 이용해 얻은 의존구조 분석 결과를 요약하면 다음과 같다. 첫째, 에너지 가격과 실물·금융 불확실성 조합의 적합한 모형을 살펴보면, 원유가격과 실물·금융 불확실성 조합은 BB7 copula 모형, 천연가스 가격과 실물·금융 불확실성 조합은 Joe copula 모형, 석탄 가격과 실물·금융 불확실성 조합은 Clayton copula 모형이 각각 가장 적합한 모형으로 선정되었다. 둘째, 전체적인 의존성 구조를 살펴보면, 원유가격, 천연가스 가격, 석탄 가격과 실물 불확실성은 양(+)의 의존성을 보였다. 그렇지만 금융 불확실성과 원유가격은 양(+)의 의존성을 갖지만, 천연가스 가격과 석탄 가격은 금융 불확성과 음(-)의 의존성을 가지는 것으로 나타났다. 전체적으로 보면, 에너지원 중 원유가격이 실물·금융 불확실성과 가장 높은 의존성을 가지는 것으로 나타났다. 셋째, 극단적인 사건을 나타내는 꼬리 의존성을 분석한 결과, 실물 불확실성과 원유, 천연가스 가격은 위 꼬리 의존성만 보이는 비대칭 관계를 가지는 것으로 나타났으며, 금융 불확실성과 원유가격은 위 꼬리 의존성만 보이는 비대칭 관계를 가지는 것으로 나타났다. 즉, 비대칭 관계를 갖는 에너지 가격은 부정적인 극단사건이 발생하는 경우 불확실성 변수와 강한 의존관계가 있는 것으로 나타났다. 반면, 경제적 불확실성과 석탄 가격은 꼬리 의존성이 없는 것으로 나타났다.

Keywords

References

  1. 김부권, "Copula 모형을 이용한 에너지 가격과 경제적 불확실성 의존관계 분석", 부산대학교 대학원 경제학과 석사학위논문, 2020.
  2. 김상배, "유가 불확실성과 주가지수 수익률: 비선형모형을 이용한 분석", 에너지경제연구, 제17권 제2호, 2018, pp. 31-51.
  3. 노산하․ 김남현, "유가 불확실성이 국내 경제변수에 미치는 영향", 국제경제연구, 제25권 제1호, 2019, pp. 1-38.
  4. 모수원, "뉴스충격과 유가변동성의 비대칭성", 자원․ 환경경제연구, 제13권 제2호, 2004, pp. 175-196.
  5. 배성종․ 박상우, "유가 변동요인이 산업생산에 미치는 영향", 한국은행 조사통계월보, 2012년 7월호, pp. 16-65.
  6. 차경수, "한국경제에 미치는 유가충격의 시간-가변적 효과에 관한 연구", 자원․ 환경경제연구, 제27권 제3호, 2018, pp. 495-520.
  7. Aloui, R., R. Gupta, and S. M. Miller, "Uncertainty and crude oil returns," Energy Economics, Vol. 55, 2016, pp. 92-100. https://doi.org/10.1016/j.eneco.2016.01.012
  8. Antonakakis, N., I. Chatziantoniou, and G. Filis, "Dynamic spillovers of oil price shocks and economic policy uncertainty," Energy Economics, Vol. 44, 2014, pp. 433-447. https://doi.org/10.1016/j.eneco.2014.05.007
  9. Baker, S. R., N. Bloom, and S. J. Davis, "Measuring economic policy uncertainty," Quarterly Journal of Economics, Vol. 131, 2016, pp. 1593-1636. https://doi.org/10.1093/qje/qjw024
  10. Basher, S. A. and P. Sadorsky, "Hedging emerging market stock prices with oil, gold, VIX, and bonds: a comparison between DCC, ADCC and GO-GARCH," Energy Economics, Vol. 54, 2016, pp. 235-247. https://doi.org/10.1016/j.eneco.2015.11.022
  11. Bernanke, B. S., "Irreversibility, uncertainty, and cyclical investuncertainty, and cyclical investment," Quarterly Journal of Economics, Vol. 98, 1983, pp. 85-106. https://doi.org/10.2307/1885568
  12. Brechmann E. and U. Schepsmeier. "Cdvine: Modeling dependence with c-and d-vine copulas in R.," Journal of statistical software, Vol. 52, 2013, pp. 1-27.
  13. Brown, S. P. A. and M. K. Yucel, "What drives natural gas prices?," Energy Journal, Vol. 29, 2008, pp. 45-60.
  14. Cech, C., "Copula-based top-down approaches in financial risk aggregation," 2006, Available at SSRN 953888.
  15. Chang, C. L., M. McAleer, and R. Tansuchat, "Crude oil hedging strategies using dynamic multivariate GARCH," Energy Economics, Vol. 33, 2011, pp. 912-923. https://doi.org/10.1016/j.eneco.2011.01.009
  16. Colombo, V., "Economic policy uncertainty in the US: does it matter for the Euro area?" Economics Letters, Vol. 121, 2013, pp. 39-42. https://doi.org/10.1016/j.econlet.2013.06.024
  17. Degiannakis, S., G. Filis, and V. Arora, "Oil prices and stock markets: a review of the theory and empirical evidence," Energy Journal, Vol. 39, 2018, pp. 85-130.
  18. Elder, J. and A. Serletis, "Oil price uncertainty," Journal of Money, Credit and Banking, Vol. 42, 2010, pp. 1137-1159. https://doi.org/10.1111/j.1538-4616.2010.00323.x
  19. Ferderer, J. P., "Oil price volatility and the macroeconomy," Journal of Macroeconomics, Vol. 18, 1996, pp. 1-26. https://doi.org/10.1016/S0164-0704(96)80001-2
  20. Filis, G., S. Degiannakis, and C. Floros, "Dynamic correlation between stock market and oil prices: the case of oil-importing and oil-exporting countries," International Review of Financial Analysis, Vol. 20, 2011, pp. 152-164. https://doi.org/10.1016/j.irfa.2011.02.014
  21. Genest, C., B. Rémillard, and D. Beaudoin, "Goodness-of-fit tests for copulas: A review and a power study." Insurance: Mathematics and economics, Vol. 44, 2009, pp. 199-213. https://doi.org/10.1016/j.insmatheco.2007.10.005
  22. Halvorsen, R., "Energy substitution in US manufacturing," Review of Economics and Statistics, Vol. 59, 1977, pp. 381-388. https://doi.org/10.2307/1928702
  23. Hamilton, J. D., "Oil and the macroeconomy since World War II," Journal of Political Economy, Vol. 91, 1983, pp. 228-248. https://doi.org/10.1086/261140
  24. Herrera, A. M., L. G. Lagalo, and T. Wada, "Asymmetries in the response of economic activity to oil price increases and decreases?" Journal of International Money and Finance, Vol. 50, 2015, pp. 108-133. https://doi.org/10.1016/j.jimonfin.2014.09.004
  25. Hofert M., I. Kojadinovic, M. Machler, and J. Yan, Elements of copula modeling with R., 2019, Springer.
  26. Jo, S., "The effects of oil price uncertainty on global real economic activity," Journal of Money, Credit and Banking, Vol. 46, 2014, pp. 1113-1135. https://doi.org/10.1111/jmcb.12135
  27. Joe, H., Multivariate Models and Multivariate Dependence Concepts, 1997, London: Chapman & Hall/CRC.
  28. Joo, Y. C. and S. Y. Park, "Oil prices and stock markets: does the effect of uncertainty change over time?" Energy Economics, Vol. 61, 2017, pp. 42-51. https://doi.org/10.1016/j.eneco.2016.10.017
  29. Knight, F. H., "Cost of production and price over long and short periods," Journal of Political Economy, Vol. 29, 1921, pp. 304-335. https://doi.org/10.1086/253349
  30. Oberndorfer, U., "Energy prices, volatility, and the stock market: evidence from the Eurozone," Energy Policy, Vol. 37, 2009, pp. 5787-5795. https://doi.org/10.1016/j.enpol.2009.08.043
  31. Pindyck, R. S., "Volatility and commodity price dynamics," Journal of Futures Markets, Vol. 24, 2004, pp. 1029-1047. https://doi.org/10.1002/fut.20120
  32. Scholtens, B. and C. Yurtsever, "Oil price shocks and European industries," Energy Economics, Vol. 34, 2012, pp. 1187-1195. https://doi.org/10.1016/j.eneco.2011.10.012
  33. Silvennoinen, A. and S. Thorp, "Financialization, crisis and commodity correlation dynamics," Journal of International Financial Markets, Institutions and Money, Vol. 24, 2013, pp. 42-65. https://doi.org/10.1016/j.intfin.2012.11.007
  34. Sklar, A., "Fonctions de Repartition a n Dimensions et Leurs Marges," Publications de l'Institut Statistique de l'Universite de Paris, Vol. 8, 1959, pp. 229-231.
  35. Trivedi, P. K. and D. M. Zimmer, Copula Modeling: An Introduction for Practitioners, 2007, Now Publishers Inc.
  36. Xiao, J., M. Zhou, F. Wen, and F. Wen, "Asymmetric impacts of oil price uncertainty on Chinese stock returns under different market conditions: evidence from oil volatility index," Energy Economics, Vol. 74, 2018, pp. 777-786. https://doi.org/10.1016/j.eneco.2018.07.026