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Granger Causality 검정과 공적분 검정을 통한 OECD 국가 재생에너지정책 효과 분석

Analysis of Renewable Energy Policy Effects in OECD Countries Using Granger Causality and Cointegration Test

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주제분류행정학

초록

최근 세계 각국은 기후변화 대응을 위한 온실가스 감축과 더불어 미래 신성장 동력 확보의 일환 으로 재생에너지 개발과 보급 확대를 위한 정책적 노력을 집중하고 있으며, 이에 따라 동 정책들의 효과성을 분석하기 위한 많은 학문적 연구가 진행되었다. 다만, 기존의 많은 연구들은 패널자료를 활용한 계량적 분석에서 정책들 간 상호작용효과와 정책의 의존성 문제에 대한 논의 그리고 정책들 의 장・단기적 효과에 대한 분석이 다소 부족하였다. 이에 본 연구는 OECD 25개국에서 시행 중인 정책수단을 핵심변수로 활용하되 유사한 정책들의 통합변수 구성 등을 통해 보다 효과적인 정책 분석을 시도하였고 동시에 각 국가에서 도입되고 있는 정책의 성과 등을 파악하였다. 분석 결과 첫째, 조세정책은 단기적으로는 재생에너지 발전과 확대에 강력하게 기여하고 있으나 장기적으로 는 효과가 없는 것으로 나타났다. 둘째, 발전차액지원제도 등 가격기반 정책과 투자・보조금정책은 단기적으로는 그 효과가 미미하나 장기적으로는 매우 긍정적인 영향을 미치는 것으로 분석되었다. 셋째, 공급의무할당제도 등 수량기반 정책은 재생에너지 발전과 보급 확대에 유의미한 영향을 미치 지 못하는 것으로 분석되었다. 이러한 연구 결과는 실증적 분석과 더불어 각국에서 운영하고 있는 정책의 경험적 분석을 토대로 정책의 효과성을 제시한 것으로 이론적 가치를 지니며, 보다 실효적 인 정책 방향을 제시하는 데 기여할 수 있다.

Abstract

In recent times, countries around the world have been concentrating their policy resources on the development and wider deployment of renewable energy as part of efforts to reduce greenhouse gas emissions to address climate change and to secure new growth engines for the future. Accordingly, a number of studies have been conducted thus far to analyze the effectiveness of related policies. However, existing studies leave much room for improvement as they, in many cases, lack analysis on the effects of interactions among different policies, interdependence of those policies and short- and long-term effects of those policies while examining panel data analysis. For this reason, this study aimed at more effective policy analysis by using policy measures being taken by 25 OECD member countries as key variables and by making similar policies as composit policy variables, respectively. At the same time, it also tried to assess the implementation of policies introduced by countries in question. The findings of this study include: First, Tax related policies was found to be a strong contributor to the development and wider use of renewable energy in the short term, but not effective in the long term; Second, price-based policies including Feed in Tariff (FIT) programs as well as investment and subsidy schemes were proved to be not so much effective in the short term, but to have very positive impact in the long term; and Third, it was found that quantity-based policies including Renewable Portfolio Standards (RPS) did not have meaningful impact on the development and dissemination of renewable energy. The results of this study have demonstrated the effectiveness of policies undertaken by countries around the world through practical and empirical analysis, and it is also expected to provide adequate directions for policy-makers in formulating more effective renewable energy policy.

참고문헌 (105)

  1. 구민교, "우리나라의 발전차액지원제도 사례 분석: 신산업정책론 시각에서", 한국행정연구, 22(1), pp.1~27 (2013), 한국행정연구원[DOI]
  2. 권태형, "신재생에너지 지원 정책과 지대추구: 국내 발전차액지원제도와 공급의무화제도 사례", 행정논총, 53(2), pp.295~314 (2015), 한국행정연구소
  3. 권태형, "한국의 신재생에너지 정책에서 시장과 규제의 적절한 활용방안 연구", 경제발전연구, 24(2), pp.1~26 (2018), 한국경제발전학회[DOI]
  4. 김다은, "정책수단이 재생에너지 활성화에 미치는 영향에 관한 실증연구: 정책수단과 정부효과성의 상호작용을 중심으로", 한국행정학보, 51(2), pp.33~59 (2017), 한국행정학회[DOI]
  5. 김보례, "패널 VAR를 이용한 부가가치 기준 무역과 경제성장과의 인과관계 분석", 국제통상연구, 20(1), pp.123~154 (2015), 한국국제통상학회
  6. 김승래, "우리나라의 친환경 에너지세제 정책과제와 개선방향 분석", 에너지경제연구, 10(2), pp.143~167 (2011), 재단법인 에너지경제연구원[DOI]
  7. 김은성, "동적 패널 모형을 이용한 재생에너지 정책의 OECD 국가 재생에너지 보급 효과 분석", 자원환경경제연구, 25(2), pp.229~253 (2016), 한국환경경제학회[DOI]
  8. 김정배, "신재생에너지 산업 기술 정책의 투자효과 분석에 대한 기초 연구", 한국태양에너지학회 논문집, 32(5), pp.18~24 (2012), 한국태양에너지학회
  9. 김태은, "신재생에너지 성장의 영향요인 연구: FIT와 RPS의 효과성 검증을 중심으로", 한국행정학보, 45(3), pp.305~333 (2011), 한국행정학회
  10. 민인식, "고급패널데이터 분석" (2012), ㈜지필미디어
  11. 민인식, "고급통계 분석" (2019), ㈜지필미디어
  12. 민인식, "STATA 시계열데이터 분석" (2016), ㈜지필미디어
  13. 백철우, "신재생에너지 분야 정부 R&D 투자 효율성 분석", 에너지공학, 23(3), pp.42~50 (2014), 한국에너지학회
  14. 신정희, "에너지공급에 있어서 국가의 과제와 지속가능한 재생에너지 보급촉진제도 - 현행 발전차액지원제도와 2012년 도입되는 발전비율할당제 -", 법학연구, 52(4), pp.27~51 (2011), 법학연구소
  15. 심진경, "해양에너지분야 정부연구개발사업의 민간참여활성화 방안 연구 - 해양수산부 해양청정에너지개발사업을 중심으로 -", 신재생에너지, 12(4), pp.48~52 (2016), 한국신·재생에너지학회
  16. 임형우, "RPS 및 FIT 제도가 신재생에너지 보급에미치는 효과 분석 : 104개국 패널토빗분석", 에너지경제연구, 16(2), pp.1~31 (2017), 재단법인 에너지경제연구원[DOI]
  17. 이상호, "주요국의 신재생에너지 지원정책 동향", 전기저널 (2019)
  18. 이완수, "의제설정이론에서 그랜저 인과관계 모형의 방법론적 타당성 연구", 커뮤니케이션 이론, 5(2), pp.54~100 (2009), 한국언론학회
  19. 일본 FIT 제도 운영 문제점과 제도개선, "임지영", 19~28, pp.세계 에너지시장 인사이트. 17(12) (2017)
  20. 조하현, "신재생에너지 보급과 경제성장의 비선형 동태패널분석", 국제경제연구, 23(2), pp.31~66 (2017), 한국국제경제학회[DOI]
  21. 채종오, "한국의 탄소배출권 거래제 시행 1년 후 현황과 개선방안 - EU 배출권 거래제와 비교를 통하여 -", 한국기후변화학회지, 7(1), pp.41~48 (2016), 한국기후변화학회[DOI]
  22. Abolhosseini, S., "The main support mechanisms to finance renewable energy development", Renewable and Sustainable Energy Reviews, 40, pp.876~885 (2014)
  23. Akar, B. G, "The Determinants of Renewable Energy Consumption: An Empirical Analysis for the Balkans", European Scientific Journal, 12(11), pp.1857~1881 (2016)
  24. Akin, C. S., "Determinants of Using Renewable Energy Resource : Panel Data Analysis", Global Journal of Advanced Research, 4(9), pp.261~268 (2017)
  25. Apergis, N., "Renewable and non-renewable electricity consumption–growth nexus : evidence from emerging market economies", Applied Energy, 88(12), pp.5226~5230 (2011)
  26. Apergis, N., "On the causal dynamics between emissions, nuclear energy, renewable energy, and economic growth", Ecological Economics, 69(11), pp.2255~2260 (2010)
  27. Arias, A. D., "Energy subsidies, structure of electricity prices and technological change of energy use", Energy Economics, 40(2), pp.495~502 (2013)
  28. Design and Performance of Policy Instruments to Promote the Development of Renewable Energy, A WORLD BANK STUDY, "Azuela, G. E.", The World Bank, ~ (2012)
  29. Design and performance of policy instruments to promote the development of renewable energy: emerging experience in selected developing countries, "Azuela, G. E.", World Bank Publications, ~ (2012)
  30. Design and Performance of Policy Instruments to Promote the Development of Renewable Energy; Emerging Experience in Selected Developing Countries, "Azuela, G. E.", WorldBank, ~, pp.WorldBank Working Paper, No. 22 (2011)
  31. Barradale, M. J., "Impact of public policy uncertainty on renewable energy investment:wind power and the production tax credit", Energy Policy, 38, pp.7698~7709 (2010)
  32. Bertoldi, P., "Do energy efficiency policies save energy? A new approach based on energy policy indicators(in the EU Member States)", Energy Policy, 139, pp.111320~ (2020)
  33. Bickel, P., "Assessment of environment and social impacts of the “KFW Renewable Energies Programme – Standard” for the year 2014", ~ (2016)
  34. Blazquez, J., "The renewable energy policy Paradox", Renewable and Sustainable Energy Reviews, 82, pp.1~5 (2018)
  35. Breusch, T. S., "The Lagrange multiplier test and its application to model specification in econometrics", Review of Economic Studies, 47, pp.239~253 (1980)
  36. Cai, W., "Green economy and green jobs: Myth or reality The case of China’s power generation sector", Energy, 36, pp.5594~6003 (2011)
  37. Cansino, J. M., "Tax incentives to promote green electricity: an overview of EU-27 countries", Energy policy, 38, pp.6000~6008 (2010)
  38. Carley S., "State Renewable Energy Electricity Policies : An Empirical Evaluation of Effectiveness", Energy Policy, 37, pp.3071~3081 (2009)
  39. Carley, S., "State renewable energy electricity policies : An empirical evaluation of effectiveness", Energy policy, 37(8), pp.3071~3081 (2009)
  40. Chien T., "Renewable energy : An efficient mechanism to improve GDP", Energy Policy, 36(8), pp.304~352 (2008)
  41. Couture, T., "An analysis of feed-in-tariff remuneration models:implications for renewable energy investment", Energy policy, 38, pp.955~965 (2010)
  42. Cox, N. J., "Generating composite categorical variables", The Stata Journal, 7(4), pp.582~583 (2007)
  43. Cox, N. J., "Generating composite categorical variables", The Stata Journal, 7(4), pp.582~583 (2007)
  44. Davis, G. A., "Optimizing the level of renewable electric R&D expenditures using real options analysis", Energy Policy, 31(15), pp.1589~1608 (2003)
  45. De Hoyos, R. E., "Testing for cross-sectional dependence in panel-data models", The stata journal, 6(4), pp.482~496 (2006)
  46. Policy instrument design to reduce financing costs in renewable energy technology projects, "De Jager, D.", International Energy Agency Implementing Agreement on Renewable Energy Technology Deployment, ~, pp.PECSNL062979 (2008)
  47. De Jonghe, C., "Interactions between measures for the support of electricity from renewable energy sources and CO2 mitigation", Energy Policy, 37(11), pp.4743~4752 (2009)
  48. Del Rio, P., "Comparing the innovation effects of support schemes for renewable electricity technologies: A function of innovation approach", Energy Policy, 50, pp.272~282 (2012)
  49. Dong, C. G., "Feed-in tariff vs, renewable portfolio standard: an empirical test of their relative effectiveness in promoting wind capacity development", Energy Policy, 42, pp.476~485 (2012)
  50. Fang, Y., "Economic welfare impacts from renewable energy consumption: The China experience", Renew. Sustain. Energy Rev, 15, pp.5120~5128 (2011)
  51. Combining policies for renewable energy: Is the whole less than the sum of its parts?, "Fischer, C.", 10~19 (2010)
  52. Frees, E. W., "Assessing cross-sectional correlation in panel data", Journal of Econometrics, 69, pp.393~414 (1995)
  53. Freidman, M., "The use of ranks to avoid the assumption of normality implict in the analysis of variance", Journal of the American Statistical Association, 32, pp.675~701 (1937)
  54. Frondel, M., "Economic impacts from the promotion of renewable energy technologies : The German experience", Energy Policy, 38(8), pp.4048~4056 (2010)
  55. Hassine, M. B., "The Casual Links between Economic Growth, Renewable Energy, Financial Development and Foreign Trade in Gulf Cooperation Council Countries", International Journal of Energy Economics and Policy, 7(2), pp.76~85 (2017)
  56. Im, K. S., "Testing for unit roots in heterogeneous panels", Journal of econometrics, 115(1), pp.53~74 (2003)
  57. Inglesi-Lotz, R., "The impact of renewable energy consumption to economic growth:A panel data application", Energy economics, 53, pp.58~63 (2016)
  58. Renewable Energy Benefits: Measuring the Economics, "International Renewable Energy Agency", ~ (2016)
  59. Izadian, A., "Renewable energy policies : A brief review of the latest US and EU policies", IEEE Industrial Electronics Magazine, 7(3), pp.21~34 (2013)
  60. Jensen, S. G., "Interactions between the power and green certificate markets", Energy Policy, 30, pp.425~435 (2002)
  61. Jin, T., "What is better for mitigating carbon emissions–Renewable energy or nuclear energy? A panel data analysis", Renewable and Sustainable Energy Reviews, 91, pp.464~471 (2018)
  62. Johnstone, N., "Renewable energy policies and technological innovation: evidence based on patent counts", Environ. Resour. 「Econ」, 45, pp.133~155 (2008)
  63. Kao C., "Nonstationary panels, panel cointegration, and dynamic pnnels, 15. Advanced in Econometrics", pp.170~222 (2000)
  64. Kao, C., "Spurious regression and residual-based tests for cointegrationin panel data", Journal of Econometrics, 90, pp.1~44 (1999)
  65. Kilinc-Ata, N., "The evaluation of renewable energy policies across EU countries and US states: An econometric approach", Energy for Sustainable Development, 31, pp.83~90 (2016)
  66. Kimiagari, A. M., "Analysis of the simultaneous effects of renewable energy consumption and GDP, using Dynamic Panel Data", Journal of Industrial Engineering and Management Studies, 3(1), pp.1~14 (2016)
  67. Lach, S., "Do R&D subsidies stimulate or displace private R&D? Evidence from Israel", The Journal of Industrial Economics, 50(4), pp.369~390 (2002)
  68. Levin, A., "Unit root tests in panel data : asymptotic and finite-sample properties", Journal of econometrics, 108(1), pp.1~24 (2002)
  69. Lise, W., "Energy consumption and GDP in Turkey : Is there a co‐integration relationship?", Energy economics, 29(6), pp.1166~1178 (2007)
  70. Liu, P., "Renewables finance and investment : how to improve industry with private capital in China", Journal of Modern Power Systems and Clean Energy, 7(6), pp.1385~1398 (2019)
  71. Liu, W., "Does renewable energy policy work? Evidence from a panel data analysis", Renewable Energy, 135, pp.635~642 (2019)
  72. Impacts of federal tax credit extensions on renewable deployment and power sector emissions, "Mai, T.", National Renewable Energy Lab.(NREL), ~, pp.No. NREL (2016), TP-6A20-65571
  73. Mannino, M., "Foundational perspectives on causality in large-scale brain networks", Physics of life reviews, 15, pp.107~123 (2015)
  74. Marques, A. C., "Drivers promoting renewable energy : A dynamic panel approach", Renewable and sustainable energy reviews, 15(3), pp.1601~1608 (2011)
  75. Marques, A. C., "Motivations driving renewable energy in European countries : A panel data approach", Energy policy, 38(11), pp.6877~6885 (2010)
  76. "Carbon taxes: What can we learn from international experience" (2019)[URL]
  77. Mitchel. C., "Effectiveness through risk reduction:a comparison of the renewable obligation in England and Wales and the feed-in system in Germany", Energy policy, renewable energy policies in the European Union, 34, pp.297~305 (2006)
  78. Mitić, P., "A cointegration analysis of real GDP and CO2 emissions in transitional countries", Sustainability, 9(4), pp.568~ (2017)
  79. The Impact of Environmental Policies on Renewable Energy Innovations: Addressing the Issue of Endogeneity Using A New Indicator, "Nicolli, F.", OFCE, ~ (2012)
  80. The government’s role in mobilising investment and innovation in renewable energy, Green Finance and Investment Insights, "OECD", ~ (2017)
  81. Ogunlana, A. O., "Tax incentives for renewable Energy: The Eurepean Experience", The European Proceedings of Social & Behavioural Sciences, pp.2357~1330 (2017)
  82. Ouyang, X., "Impacts of increasing renewable energy subsidies and phasing out fossil fuel subsidies in China", Renewable and sustainable energy reviews, 37, pp.933~942 (2014)
  83. Payne, J. E., "The causal dynamics between US renewable energy consumption, output, emissions, and oil prices", Energy Sources, Part B: Economics, Planning, and Policy, 7(4), pp.323~330 (2012)
  84. Pedroni, P., "Critical Values for cointegration tests in heterogenous panels with multiple regressors", Oxford Bulletin of Economics and Statistics Special Issue, 61, pp.653~670 (1999)
  85. Pedroni, P., "Panel cointegration: Asymptotic and finite sample properties of pooled time series tests with an application to the PPP hypothesis", Econometric Theory, 20, pp.597~625 (2004)
  86. General diagnostic tests for cross section dependence in panels, "Pesaran, M. N.", University of Cambridge, Faculty of Economics, ~, pp.Cambridge Working Papers in Economics No. 0435 (2004)
  87. Polzin, F., "Public policy influence on renewable energy investments—A panel data study across OECD countries", Energy Policy, 80, pp.98~111 (2015)
  88. Popp, D., "Technology and the diffusion of renewable energy", Energy Economics, 33(4), pp.648~662 (2011)
  89. The impact of renewable energy policy on economic growth and employment in the European Union, "Ragwitz, M.", European Commission, DG Energy and Transport, ~ (2009)
  90. State and trends of carbon pricing 2019, "Ramstein, C.", The World Bank, ~ (2019)
  91. State and trends of carbon pricing 2019, "Ramstein, C.", The World Bank, ~ (2019)
  92. Rickerson, W., "The debate over fixed price incentives for renewable electricity in Europoe and the United States: Fall out and Future directions. A White parer Prepared for The Heinrich Bill Foundation" (2007)
  93. Romano, A. A., "Investments in Renewable Energy Sources in OPEC Members: a Dynamic Panel Approach", Metodoloski zvezke, 11, pp.93~106 (2014)
  94. Sadorsky, P., "Renewable energy consumption, CO2 emissions and oil prices in the G7countries", Energy Economics, 31(3), pp.456~462 (2009)
  95. Sarafidis, V., "Cross-sectional Dependence in panel Data Analysis" (2010), The University of Sydney
  96. Shafiei, S., "Non-renewable and Renewable Energy Consumption and CO2 Emissions in OECD Countries : A Comparative Analysis", Energy Policy, 66, pp.547~556 (2014)
  97. Singh, N., "Renewable energy development as a driver of economic growth : Evidence from multivariate panel data analysis", Sustainability, 11(8), pp.2418~ (2019)
  98. Sisodia, G. S., "Panel data analysis for renewable energy investment determinants in Europe", Applied Economics Letters, 22(5), pp.397~401 (2015)
  99. Stefan, D. A., "Does Renewable Energy Drive Sustainable Economic Growth?, Multivariate Panel Data Evidence for EU-28 Countries", Energies, 10, pp.1~21 (2017)
  100. Limitations of granger causality analysis to assess the price effects from the financialization of agricultural commodity markets under bounded rationality, "Stephanie, G.", Agricultural and Resource Economics, ~, pp.Discussion Paper, 1 (2012)
  101. Wallsten, S. J., "The effects of government-industry R&D programs on private R&D:the case of the Small Business Innovation Research program", pp.82~100 (2000), The RAND Journal of Economics
  102. Westerlund, J., "Testing for error correction in panel data", Oxford Bulletin of Economics and statistics, 69(6), pp.709~748 (2007)
  103. Yu, F., "The impact of government subsidies and enterprises’ R&D investment: A panel data study from renewable energy in China", Energy Policy, 89, pp.106~113 (2016)
  104. Zhao, Y., "Do renewable electricity policies promote renewable electricity generation? Evidence from panel data", Energy policy, 62, pp.887~897 (2013)
  105. Zoundi, Z., "CO2 emissions, renewable energy and the Environmental Kuznets Curve, a panel cointegration approach", Renewable and Sustainable Energy Reviews, 72, pp.1067~1075 (2017)

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