| 研究生: |
徐芸霜 Hsu, Yun-Shuang |
|---|---|
| 論文名稱: |
美國、中國及日本之經濟成長、二氧化碳排放量、能源消耗量與各產業之因果關係 A multivariate causality test of economic growth, carbon dioxide emissions, energy consumption and related industry in America, China and Japan. |
| 指導教授: |
張瀞之
Chang, Ching-Chih |
| 學位類別: |
碩士 Master |
| 系所名稱: |
管理學院 - 交通管理科學系 Department of Transportation and Communication Management Science |
| 論文出版年: | 2015 |
| 畢業學年度: | 103 |
| 語文別: | 中文 |
| 論文頁數: | 110 |
| 中文關鍵詞: | 經濟成長 、二氧化碳排放量 、能源消耗 、Granger因果關係 |
| 外文關鍵詞: | Economic growth, Energy consumption, CO2 emissions, Granger causality. |
| 相關次數: | 點閱:153 下載:33 |
| 分享至: |
| 查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報 |
本研究以全球前三大經濟體(美國、中國與日本)為研究對象,探討其國內生產總值(Gross Domestic Product, GDP)、二氧化碳排放量(CO2 emissions)、能源消耗量、人均國民所得毛額(Gross National Income, GNI)與出口貿易量之因果關係,並將能源消耗之主產業細分為工業部門、運輸部門、住宅部門、商業與公共服務部門與農林業部門,探討其與二氧化碳排放量、出口貿易間是否具因果關係存在。本研究採用時間序列分析法,依序對變數做單根檢定(Unit Root Test)、共整合檢定(Co-integration)及誤差修正模型(Vector Error Correction Model, VECM),分析變數間之因果關係。
實證分析之結果依研究國家分述如下。美國:1.經濟成長對能源消耗量、出口貿易量有單向因果關係。2.人均國民所得對出口貿易量有單向因果關係。3.二氧化碳排放量及運輸部門能源消耗量對住宅部門能源消耗量有單向因果關係。4.出口貿易量對二氧化碳排放量、工業部門及運輸部門能源消耗量有單向因果關係。5.工業部門能源消耗量對二氧化碳排放量、農林業部門能源消耗量有單向因果關係。中國:1.出口貿易對工業部門、住宅部門能源消耗量有單向因果關係。2.運輸部門能源消耗量對住宅部門、商業與公共服務部門之能源消耗量有單向因果關係。3.商業與公共服務部門能源消耗量對住宅部門能源消耗量有單向因果關係。4.工業部門能源消耗量對與運輸部門能源消耗量有雙向因果關係。日本:1.二氧化碳排放量、能源消耗量對人均國民所得有單向因果關係。2.出口貿易量對國內生產總值及人均國民所得有單向因果關係。3.工業部門能源消耗量對二氧化碳排放量、出口貿易量有單向因果關係4.商業與公共服務部門及農林業部門能源消耗對二氧化碳排放量有單向因果關係。5.工業部門能源消耗量與運輸部門能源消耗量有雙向因果關係。6.國內生產總值與人均國民所得有雙向因果關係。
根據迴歸分析結果,美國之經濟成長與二氧化碳排放量及出口貿易量與二氧化碳排放量之因果關係最為顯著,且二氧化碳排放量有逐年降低之趨勢;中國方面則為運輸部門能源消耗量與二氧化碳排放量之因果關係相關性最高,運輸部門能源消耗量將逐年攀升;日本為人均國民所得毛額與二氧化碳排放量及工業部門能源消耗量與二氧化碳排放量之迴歸分析結果較顯著,並預估未來二氧化碳排放量將逐年降低、工業部門能源消耗量亦逐年減少。
This study examines the causal relationships among economic growth, CO2 emissions, energy consumption, Gross National Income per capita, and exports of goods and services for the United States, China and Japan. It also divides the energy consumption based on the industrial sector, transportation sector, residential sector, commercial and public service sector and agricultural sector to find out their causal relationships with CO2 emissions and exports of goods and services. Annual data for the period of 1980 to 2012 is used, and this is analyzed using the Unit Root Test in the Augmented Dickey–Fuller (ADF) test and Phillips–Perron (PP) test, a co-integration model and a Vector Error Correction Model (VECM).
The empirical results for the United States from the VECM and Granger causality tests show unidirectional causality running from: (1) GDP to energy consumption and exports of goods and services; (2) GNI to exports of goods and services; (4) exports of goods and services to CO2 emissions and energy consumption in the industrial sector and transportation sector; (5) energy consumption in the transportation sector to energy consumption in the residential sector, (6) energy consumption in the industrial sector to CO2 emissions and energy consumption in the agricultural sector. In China, unidirectional causality runs from: (1) exports of goods and services to energy consumption in the industrial sector and residential sector; (2) energy consumption in the transportation sector to energy consumption in the residential sector and commercial and public service sector; (3) energy consumption in the commercial and public service sector to energy consumption in the residential sector. Also, there exists bidirectional causality between energy consumption in the industrial sector and energy consumption in the transportation sector. In Japan, unidirectional causality runs from: (1) CO2 emissions to GNI; (2) energy consumption to GNI; (3) exports of goods and services to GDP and GNI; (4) energy consumption in the industrial sector to CO2 emissions and exports of goods and services; (5) energy consumption in the commercial and public service sector to CO2 emissions; (6) energy consumption in the agricultural sector to CO2 emissions. Furthermore, there is a bidirectional relationship between (1) energy consumption in the industrial sector and transportation sector; (2) GDP to GNI.
This study concludes that economic growth in the United States induces a higher level of CO2 emissions and exports of goods and services than the other countries. Therefore, the United States needs some comprehensive energy policies and strategies of carbon reduction. In China, there is a highly causal relationship between the energy consumption of the transportation sector and CO2 emissions. The government should thus work to construct a public transportation system. In Japan, the CO2 emissions are determined by the value of the GNI index and energy consumption in the industrial sector. In order to reduce CO2 emissions, this study thus recommends enforcing existing regulations, as well as introducing new owns, if needed.
中文文獻
工業技術研究院之能源與資源研究所 (2011)。「能源查核報導」,經濟部能源委員會。線上檢索日期:2015年5月10日。網址:http://emis.erl.itri.org.tw/book/act/listall.asp#_Toc289161863
張泉湧 (2011)。《氣候變遷-危機與轉機》。台北:五南圖書出版股份有限公司, 21-22。
張嘉齡和王友珊 (2011)。「能源消費、經濟成長與二氧化碳排放量之關聯性研究-以工業國家為例」,國立高雄第一科技大學金融研究所,45。
楊奕農 (2009)。《時間序列分析:經濟與財務上之應用》。台北:雙葉書廊有限公司,80-85;364-384。
蕭代基 (2009) 。「日本節能減碳政策與策略研究計畫」,行政院經濟建設委員會,137。
蕭代基、羅時芳與洪志銘 (2010) 。「碳稅與碳交易:政府減碳管理重要政策如何搭配」,永續產業發展,2010年4月,36-42。
英文文獻
Akaike, H. (1974). A new look at the statistical model identification. Automatic Control, IEEE Transactions on, 19(6), 716-723.
Akinlo, A. E. (2008). Energy consumption and economic growth:Evidence from 11 Sub-Sahara African countries. Energy Economics, 30(5), 2391-2400.
Alam, M. J., Begum, I. A., Buysse, J., Rahman, S., & Van Huylenbroeck, G. (2011). Dynamic modeling of causal relationship between energy consumption, CO2 emissions and economic growth in India. Renewable and Sustainable Energy Reviews, 15(6), 3243-3251.
Ang, J. B. (2007). CO2 emissions, energy consumption, and output in France. Energy Policy, 35(10), 4772-4778.
Apergis, N., & Payne, J. E. (2009). Energy consumption and economic growth:Evidence from the Commonwealth of Independent States. Energy Economics, 31(5), 641-647.
Azlina, A. A., Law, S. H., & Nik Mustapha, N. H. (2014). Dynamic linkages among transport energy consumption, income and CO2 emission in Malaysia. Energy Policy, 73, 598-606.
Batchelor, R., Alizadeh, A., & Visvikis, I. (2007). Forecasting spot and forward prices in the international freight market. International Journal of Forecasting, 23(1), 101-114.
Ben Abdallah, K., Belloumi, M., & De Wolf, D. (2013). Indicators for sustainable energy development:A multivariate cointegration and causality analysis from Tunisian road transport sector. Renewable and Sustainable Energy Reviews, 25, 34-43.
Bozoklu, S., & Yilanci, V. (2013). Energy consumption and economic growth for selected OECD countries:Further evidence from the Granger causality test in the frequency domain. Energy Policy, 63, 877-881.
Bruns, S. B., & Gross, C. (2013). What if energy time series are not independent? Implications for energy-GDP causality analysis. Energy Economics, 40, 753-759.
Chandran, V. G. R., & Tang, C. F. (2013). The impacts of transport energy consumption, foreign direct investment and income on CO2 emissions in ASEAN-5 economies. Renewable and Sustainable Energy Reviews, 24, 445-453.
Chang, C.-C. (2010). A multivariate causality test of carbon dioxide emissions, energy consumption and economic growth in China. Applied Energy, 87(11), 3533-3537.
Chang, C.-C. (2012). Marine energy consumption, national economic activity, and greenhouse gas emissions from international shipping. Energy Policy, 41, 843-848.
Chang, C.-C., & Soruco Carballo, C. F. (2011). Energy conservation and sustainable economic growth:The case of Latin America and the Caribbean. Energy Policy, 39(7), 4215-4221.
Chu, H.-P., & Chang, T. (2012). Nuclear energy consumption, oil consumption and economic growth in G-6 countries:Bootstrap panel causality test. Energy Policy, 48, 762-769.
Dickey, D. A., & Fuller, W. A. (1979). Distribution of the Estimators for Autoregressive Time Series With a Unit Root. journal of the American Statistical Association, 74(366), 427-431.
Dinda, S., & Coondoo, D. (2006). Income and emission:A panel data-based cointegration analysis. Ecological Economics, 57(2), 167-181.
Dritsaki, C., & Dritsaki, M. (2014). Causal Relationship between Energy Consumption, Economic Growth and CO2 Emissions:A Dynamic Panel Data Approach. International Journal of Energy Economics and Policy, 4(2), 125-136.
Elliott, G., Rothenberg, T. J., & Stock, J. H. (1996). Efficient Tests for an Autoregressive Unit Root. Econometrica., 64(4), 813-836.
Enders, W. (2003). Applied Econometric Time Series, 2nd Edition.
Engle, R. F., & Granger, C. W. J. (1987). Co-Integration and Error Correction:Representation, Estimation, and Testing. Econometrica., 55(2), 251-276.
Esso, L. J. (2010). Threshold cointegration and causality relationship between energy use and growth in seven African countries. Energy Economics, 32(6), 1383-1391.
Farhani, S., Chaibi, A., & Rault, C. (2014). CO2 emissions, output, energy consumption, and trade in Tunisia. Economic Modelling, 38, 426-434.
Fuller, W. A. (1976). Introduction to Statistical Time Series. New York:John Wiley.
Granger, C.W.J(1969) Investigating Causal Relation by Econometric Model and Cross-Spectral Method. Econometric, 36, 424-438..
Gilbertson, T., & Reyes, O. (2009). Carbon Trading-How it works and why it fails.
Granger, C. W. J. (1969). Investigating Causal Relations by Econometric Models and Cross-spectral Methods. Econometrica, 37(3), 424-438.
Granger, C. W. J. (1986). DEVELOPMENTS IN THE STUDY OF COINTEGRATED ECONOMIC VARIABLES. Oxford Bulletin of Economics and Statistics, 48(3), 213-228.
Granger, C. W. J., & Newbold, P. (1974). Spurious regressions in econometrics. Journal of Econometrics, 2(2), 111-120
Intergovernmental Panel on Climate Change. (2001). Third Assessment Report, TAR.
Intergovernmental Panel on Climate Change. (2013). Fifth Assessment Report , AR5.
International Energy Agency. (2013a). CO2 Emissions from Fuel Combustion. .
International Energy Agency. (2013b). Energy Balances Statistics.
International Energy Agency. (2013c). World Energy Statistics.
Jahangir Alam, M., Ara Begum, I., Buysse, J., & Van Huylenbroeck, G. (2012). Energy consumption, carbon emissions and economic growth nexus in Bangladesh:Cointegration and dynamic causality analysis. Energy Policy, 45(0), 217-225.
Johansen, S. (1988). Statistical analysis of cointegration vectors. Journal of Economic Dynamics and Control, 12(2–3), 231-254.
Johansen, S. (1991). Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models. Econometrica, 59(6), 1551-1580.
Johansen, S., & Juselius, K. (1990). Maximum Likelihood Estimation and Inference on Cointegration--With Applications to the Demand for Money. Oxford Bulletin of Economics and Statistics, 52(2), 169-210.
Kellogg, W. W. (1970). Study of Critical Environmental Problems (SCEP):In Man's Impact on global environment:assessment and recommendations for action.
Kwiatkowski, D., Phillips, P. C. B., Schmidt, P., & Shin, Y. (1992). Testing the null hypothesis of stationarity against the alternative of a unit root:How sure are we that economic time series have a unit root? Journal of Econometrics, 54(1–3), 159-178.
Lean, H. H., & Smyth, R. (2010). CO2 emissions, electricity consumption and output in ASEAN. Applied Energy, 87(6), 1858-1864
Maddala, G. S., & Kim, I.-M. (1998). Unit roots, cointegration and structural change: Cambridge University Press.
Matthews, W. H., Kellogg, W. W., & Press, M. (1971). Inadvertent Climate Modification:Study of Man's impact on Climate (SMIC).
Nelson, C. R., & Plosser, C. R. (1982). Trends and random walks in macroeconmic time series:Some evidence and implications. Journal of Monetary Economics, 10(2), 139-162.
Ockwell, D. G. (2008). Energy and economic growth:Grounding our understanding in physical reality. Energy Policy, 36(12), 4600-4604.
Ozturk, I. (2010). A literature survey on energy–growth nexus. Energy Policy, 38(1), 340-349.
Payne, J. E. (2010). Survey of the international evidence on the causal relationship between energy consumption and growth. Journal of Economic Studies, 37(1), 53-95.
Phillips, P. C. B., & Perron, P. (1988). Testing for a Unit Root in Time Series Regression. Biometrika, 75(2), 336-346.
Rosellini, C. (2005). La répartition de la rente pétrolière en Afrique centrale :enjeux et perspectives. Afrique contemporaine, 125-138.
Saboori, B., Sapri, M., & bin Baba, M. (2014). Economic growth, energy consumption and CO2 emissions in OECD (Organization for Economic Co-operation and Development)'s transport sector:A fully modified bi-directional relationship approach. Energy, 66, 150-161.
Said, S. E., & Dickey, D. A. (1984). Testing for unit roots in autoregressive-moving average models of unknown order. Biometrika, 71(3), 599-607.
Saidi, K., & Hammami, S. (2015). The impact of energy consumption and CO2 emissions on economic growth:Fresh evidence from dynamic simultaneous-equations models. Sustainable Cities and Society, 14, 178-186.
Salahuddin, M., & Gow, J. (2014). Economic growth, energy consumption and CO2 emissions in Gulf Cooperation Council countries. Energy, 73, 44-58.
Schwert, G. W. (1987). Effects of model specification on tests for unit roots in macroeconomic data. Journal of Monetary Economics, 20(1), 73-103.
Shibata, R. (1976). Selection of the Order of an Autoregressive Model by Akaike's Information Criterion. Biometrika, 63(1), 117-126.
Sims, C. A. (1980). Comparison of Interwar and Postwar Business Cycles:Monetarism Reconsidered. The American Economic Review, 70(2), 250-257.
Śmiech, S., & Papież, M. (2013). Economic Growth and Energy Consumption in Post-Communist Countries:a Bootstrap Panel Granger Causality Analysis. dynamic economic models, 13, 51-68.
Śmiech, S., & Papież, M. (2014). Energy consumption and economic growth in the light of meeting the targets of energy policy in the EU:The bootstrap panel Granger causality approach. Energy Policy, 71(0), 118-129.
Soytas, U., & Sari, R. (2009). Energy consumption, economic growth, and carbon emissions: Challenges faced by an EU candidate member. Ecological Economics, 68(6), 1667-1675
Squalli, J. (2007). Electricity consumption and economic growth:Bounds and causality analyses of OPEC members. Energy Economics, 29(6), 1192-1205
Tamba, J. G., Njomo, D., Limanond, T., & Ntsafack, B. (2012). Causality analysis of diesel consumption and economic growth in Cameroon. Energy Policy, 45, 567-575.
Taschini, L., Dietz, S., & Hicks, N. (2013). A Q&A on a carbon tax versus cap-and-trade.
Wang, S. S., Zhou, D. Q., Zhou, P., & Wang, Q. W. (2011). CO2 emissions, energy consumption and economic growth in China: A panel data analysis. Energy Policy, 39(9), 4870-4875
Wang, Y., Wang, Y. C., Zhou, J., Zhu, X. D., & Lu, G. F. (2011). Energy consumption and economic growth in China:A multivariate causality test. Energy Policy, 39(7), 4399-4406.
World Meteorological Organization. (2014). WMO Greenhouse Gas Bulletin (GHG Bulletin) - N°10:The State of Greenhouse Gases in the Atmosphere Based on Global Observations through 2013.
Writers, S. (2006). Changes In Solar Brightness Too Weak To Explain Global Warming.
Zhang, C., & Nian, J. (2013). Panel estimation for transport sector CO2 emissions and its affecting factors:A regional analysis in China. Energy Policy, 63, 918-926.