아태비즈니스연구 (Asia-Pacific Journal of Business)

  • 제15권3호
  • /
  • Pages.385-397
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  • 2024
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  • 2233-5900(pISSN)
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  • 2384-3934(eISSN)
강원대학교 경영경제연구소 (KNU The Institute of Management & Economy Research)
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국제유가와 거시경제의 동태적 관계에 관한 분석

An Analysis of Dynamic Relationships Between Oil Prices and Macroeconomy

  • 정수관 (창원대학교 글로벌비즈니스)
  • Su-Kwan Jung (Department of GlobalBusiness, Changwon University)
  • 투고 : 2024.08.30
  • 심사 : 2024.09.25
  • 발행 : 2024.09.30
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초록

Purpose - The purpose of this study was to analyze the dynamic relationship between oil prices and macroeconomic variables (gross domestic product, consumer price index, and interest rate). Long-run and short-run effects of oil prices on these macroeconomic variables are examined. Design/methodology/approach - The vector error correction model (VECM) is used to examine the short-run and long-term causality of oil prices, and a hierarchical Bayesian vector autoregressive model (HBVAR) is used to find the impulse of oil shock and the response of other variables. Findings - First, oil prices do not have short-term causality with macroeconomic variables, but they have long-term causality with interest rates and GDP. Second, the long-term stable relationship of oil prices and other macroeconomic variables is important to find out causality. Third, oil shock increases interest rates and decreases GDP and consumer price. Research implications or Originality - The significance of this study is a new attempt to analyze the dynamic relationship between oil prices and macroeconomic variables by linking VECM and HBVAR. Although VECM can analyze the long-term relationship and short-term dynamics between oil prices and macroeconomic variables, it was difficult to identify the transmission path of the oil price shock. HBVAR is confirmed to be flexible because it can bypass the process of selecting VAR or VECM through unit root test and cointegration analysis, and it is expected to reduce uncertainty of selecting hyperparameters.

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참고문헌

  1. 강규호 (2016), 「베이지안 계량경제학」, 서울: 박영사.
  2. 김권식 (2011), "국제유가 충격이 경기불황을 심화시키는가?", 「경제분석」, 17(2), 90-123.
  3. 김동현, 황영식 (2012), "유가충격과 산업생산 간 관계 분석", 「한국경제의 분석」, 18(1), 55-121.
  4. 박춘성, 박성욱 (2022), 「대형 베이지안 VAR 모형을 활용한 경제전망과 시나리오 분석 (2022-04)」, 서울: 한국금융연구원.
  5. 백인걸, 김태환. (2020), "경기변동에 따른 유가충격이 거시경제에 미치는 영향에 관한 연구", 「자원.환경경제연구」, 29(2), 171-194.
  6. 성병희 (2001), "Bayesian VAR 모형을 이용한 경제전망", 「경제분석」, 7(2), 59-90.
  7. 이근영 (2011), "유가충격이 거시경제변수에 미치는 영향", 「금융연구」, 25(4), 59-93.
  8. 이근영, 정한영. (2002), "유가상승이 국민소득, 물가 및 통화정책에 미치는 영향", 「금융연구」, 16(2), 103-129.
  9. 정수관 (2023), "유가 충격이 경제활동에 미치는 비대칭적 영향", 「산업경제연구」, 36(5), 777-794.
  10. 차경수 (2018), "한국경제에 미치는 유가충격의 시간-가변적 성과에 관한 연구", 「자원.환경경제연구」, 27(3), 495-520.
  11. Bessec, M. and S. Meritet (2007), "The Causality Link between Energy Prices, Technology and Energy Intensity". In The Econometrics of Energy Systems (pp. 121-145). London: Palgrave Macmillan UK.
  12. Bernanke, B. S., M. Gertler, M. Watson, C. A. Sims and B. M. Friedman, B. M. (1997), "Systematic Monetary Policy and the Effects of Oil Price Shocks", Brookings Papers on Economic Activity, 1997(1), 91-157.
  13. Cunado, J. and F. P. de Gracia (2003), "Do Oil Price Shocks Matter? Evidence for Some European Countries", Energy economics, 25(2), 137-154.
  14. Dagum, E. B. and P. A. Cholette (2006), "The Cholette-Dagum Regression-Based Benchmarking Method-The Additive Model", Benchmarking Temporal Distribution, and Reconciliation Methods for Time Series, 51-84.
  15. Giannone, D., M. Lenza and G. E. Primiceri (2015), "Prior Selection for Vector Autoregressions", Review of Economics and Statistics, 97(2), 436-451.
  16. Gisser, M. and T. H. Goodwin (1986), "Crude Oil and the Macroeconomy: Tests of Some Popular Notions: Note", Journal of Money, Credit and Banking, 18(1), 95-103.
  17. Hamilton, J. D. (1983), "Oil and the Macroeconomy since World War II", Journal of Political Economy, 91(2), 228-248.
  18. Hamilton, J. D. (1996), "This is What Happened to the Oil Price-Macroeconomy Relationship", Journal of Monetary Economics, 38(2), 215-220.
  19. Johansen, S. (1988), "Statistical Analysis of Cointegration Vectors", Journal of Economic Dynamics and Control, 12(2-3), 231-254.
  20. Kuschnig, N. and L. Vashold (2021), "BVAR: Bayesian Vector Autoregressions with Hierarchical Prior Selection in R", Journal of Statistical Software, 100(14), 1-27.
  21. Litterman, R. B. (1986). "Forecasting with Bayesian Vector Autoregressions: Five years of Experience", Journal of Business & Economic Statistics, 4(1), 25-38.
  22. Jimenez-Rodriguez*, R. and M. Sanchez (2005), "Oil Price Shocks and real GDP growth: Empirical Evidence for Some OECD Countries", Applied economics, 37(2), 201-228.
  23. Mork, K. A. (1989), "Oil and the Macroeconomy when Prices Go Up and Down: an Extension of Hamilton's Results", Journal of Political Economy, 97(3), 740-744.
  24. Sims, C. A. (1980), "Macroeconomics and Reality", Econometrica: Journal of the Econometric Society, 48(1), 1-48.
  25. Sims, C. A. (1992), "Interpreting the Macroeconomic Time Series Facts: The effects of Monetary Policy", European Economic Review, 36(5), 975-1000.
  26. Sims, C. A. and T. Zha (1998), "Bayesian Methods for Dynamic Multivariate Models", International Economic Review, 39(4), 949-968.