DOI QR코드

DOI QR Code

Investigation on Granger Causality between Economic Growth and Demand for Electricity in Korea: Using Quarterly Data

한국의 경제성장과 전력수요간의 인과성에 관한 연구: 분기별 자료를 이용하여

  • 백문영 (연세대학교 상경대학 경제학과) ;
  • 김우환 (모나쉬대학교 경영학과)
  • Received : 2011.10.24
  • Accepted : 2011.12.07
  • Published : 2012.02.29

Abstract

This study investigates the Granger-causality between economic growth and demand for electricity in Korea, using two quarterly time-series data (real GDP and electricity consumption) for 1970:Q1 through 2009:Q4. We apply Hsiao's sequential procedure to identify a vector autoregressive model to a decision of the optimal lags in the vector error-correction model because the two time-series data contain unit roots respectively and they are cointegrated. According to the empirical results in this study, we find that Hsiao's approach to the Granger-causality indicates a bidirectional causal relation between economic growth and demand for electricity in Korea. Following the Granger and Engle's approach, we also find the statistical evidence on (1) short-run bidirectional causality between real GDP and electricity consumption, (2) bidirectional strong causality between them, and (3) long-run unidirectional causality running from demand for electricity to economic growth. Our results show an inconsistency with the existing studies on Korea's case; however, the results appear to provide more meaningful policy implications for the Korean economy and its strategy of sustainable growth.

본 연구는 한국의 경제성장과 전력수요 사이의 Granger-인과성을 조사한 것이다. 실증분석을 위해 1970년 1분기부터 2009년 4분기까지의 분기별 실질 GDP와 전력소비 시계열 자료를 활용하였다. 두 시계열에 단위근이 존재하고 공적분 관계가 있음을 확인한 후 오차수정모형을 구성하였으며, Hsiao (1979)의 순차적 모형식별 과정을 적용해서 자기회귀항의 최적시차를 결정하여 모형을 추정하였다. Hsiao 방식의 Granger-인과성 분석결과, 한국의 경제성장과 전력수요는 양방향의 인과관계를 보였다. 추정된 개별 오차수정모형을 기반으로 Engle-Granger 방식의 추가적인 인과성 분석 결과로부터는 (1) 경제성장과 전력수요 사이의 단기적인 양방향성 인과관계, (2) 양방향성 강 인과관계, 그리고 (3) 장기적으로는 전력수요로부터 경제성장으로의 단방향성 인과관계를 확인할 수 있었다. 이러한 결과는 기존의 선행연구의 결과와는 상반되는 것이나, 지속적인 경제성장을 추구하는 한국의 상황에서 더 의미 있는 정책적 시사점을 줄 수 있다.

References

  1. Akaike, H. (1969). Fitting autoregressive for prediction, Annals of the Institute of Statistical Mathematics, 21, 243-247. https://doi.org/10.1007/BF02532251
  2. Chen, S. T., Cuo, H. I. and Chen, C. C. (2007). The relationship between GDP and electricity consumption in 10 Asian countries, Energy Policy, 35, 2611-2621. https://doi.org/10.1016/j.enpol.2006.10.001
  3. Dickey, D. A. and Fuller, W. F. (1979). Distribution of the estimations for AR time series with a unit root, Journal of the American Statistical Association, 74, 427-431.
  4. Engle, R. F. and Granger, C. W. (1983). Cointegration and error correction: Representation, estimation, and testing, Econometrica, 55, 251-276. https://doi.org/10.2307/1913236
  5. Glasure, Y. U. and Lee, A. (1998). Cointegration, error-correction, and the relationship between GDP and energy: The case of South Korea and Singapore, Resource and Energy Economics, 20, 17-25. https://doi.org/10.1016/S0928-7655(96)00016-4
  6. Granger, C. W. (1988). Some recent developments in a concept of casuality, Journal of Econometrics, 39, 383-397.
  7. Hsiao, C. (1979). Autoregressive modeling of Canadian money and income data, Journal of the American Statistical Association, 74, 553-560. https://doi.org/10.1080/01621459.1979.10481651
  8. Johansen, S. and Juselius, K. (1990). Maximum likelihood estimation and inference on cointegration with applications to the demand for money, Oxford Bulletin of Economics and Statistics, 52, 169-210. https://doi.org/10.1111/j.1468-0084.1990.mp52002003.x
  9. Narayan, P. K. and Prasad, A. (2008). Electricity consumption-real GDP causality nexus: Evidence from a bootstrapped causality test for 30 OECD countries, Energy Policy, 33, 1109-1116. https://doi.org/10.1016/j.enpol.2003.11.010
  10. Oh, W. and Lee, K. (2004). Casual relationship between energy consumption and GDP revisited: The case of Korea 1970-1999, Energy Economics, 26, 51-59. https://doi.org/10.1016/S0140-9883(03)00030-6
  11. Phillips, P. C. B. and Perron, P. (1988). Testing for a unit root in time series regression, Biometrica, 75, 335-346. https://doi.org/10.1093/biomet/75.2.335
  12. Yoo, S.-H. (2005). Electrcity consumption and economic growth: Evidence from Korea, Energy Policy, 33, 1627-1632. https://doi.org/10.1016/j.enpol.2004.02.002
  13. Yoo, S.-H. (2006). The causal relationship between electricity consumption and economic growth in the ASEAN countries, Energy Policy, 34, 3573-3582. https://doi.org/10.1016/j.enpol.2005.07.011
  14. Yu, E. S. H. and Choi, J. Y. (1985). The causal relationship between energey and GNP: An international comparison, Journal of Energy and Development, 10, 249-272. https://doi.org/10.1016/0360-5442(85)90045-3

Cited by

  1. Information Variables for the Predictability of Future Changes in Real Growth vol.26, pp.2, 2013, https://doi.org/10.5351/KJAS.2013.26.2.253
  2. An Analysis on the Causality between Production Activity and Electricity Consumption in Manufacturing Sector vol.23, pp.2, 2014, https://doi.org/10.15266/KREEA.2014.23.2.349
  3. Identifying the Chickens-Eggs Statistical Lead-Lag Dilemma vol.26, pp.3, 2013, https://doi.org/10.5351/KJAS.2013.26.3.401
  4. An Analysis on the Causal Relation Between Electricity Consumption and GDP by industries in KOREA vol.30, pp.3, 2016, https://doi.org/10.5207/JIEIE.2016.30.3.039
  5. Predictability of Consumer Expectations for Future Changes in Real Growth vol.28, pp.3, 2015, https://doi.org/10.5351/KJAS.2015.28.3.457