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研究生: 黃雅清
Huang, Ya-Ching
論文名稱: 京都議定書對二氧化碳排放量的影響:以LASSO合成控制法估計與檢定
The Assessment of the Effect of the Kyoto Protocol on Carbon Dioxide Emission by LASSO Synthetic Control Method
指導教授: 楊睿中
Yang, Jui‐Chung
口試委員: 廖肇寧
Liao, Chao-Ning
朱紀仰
Chu, Chi-Yang
學位類別: 碩士
Master
系所名稱: 科技管理學院 - 經濟學系
Department of Economics
論文出版年: 2020
畢業學年度: 108
語文別: 中文
論文頁數: 53
中文關鍵詞: 京都議定書合成控制法LASSO
外文關鍵詞: Kyoto Protocol, synthetic control method, LASSO
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  • LASSO合成控制法(LASSO synthetic control method)透過放寬合成控制法對權重與截距項的限制,提升預測反事實情境的準確性。本論文應用LASSO合成控制法,針對23個國家和當時的歐盟,評估其二氧化碳排放量受京都議定書影響的程度。由本文實證結果之個別年度觀察,發現多數國家沒有顯著減少二氧化碳排放量。觀察政策執行期間的平均結果,本文發現多數國家平均有減少碳排放量,但減量的程度沒有達統計上顯著,顯示京都議定書對各國在2005年到2012年二氧化碳排放量的影響,極為有限。


    The LASSO synthetic control method relaxes restrictions on the weights and the intercept of the original synthetic control method so as to improve the prediction of counterfactual outcomes. We apply the LASSO synthetic control method to assess the Kyoto Protocol’s effect on CO2 emission reduction of 23 countries and the European Union, which consists of 15 member states at that time, with binding emission targets under the Kyoto Protocol. We cannot find the statistically significant negative treatment effect for most countries in the following years after the Kyoto Protocol entered into force. As for averaging yearly treatment effects for each country, we find that the average treatment effect for most countries is negative, but it is not statistically significant. In summary, we find little evidence for a significant CO2 emission reduction from 2005 to 2012 for most countries with binding emission targets under the Kyoto Protocol.

    摘要 i Abstract ii 誌謝 iii 目錄 iv 圖表目錄 v 1. 緒論 1 2. 文獻回顧 4 3. 研究方法 7 3.1. 模型架構 7 3.2. 假設 8 3.3. 估計與檢定 9 4. 實證分析 15 4.1. 資料集描述 15 4.2. 資料來源 17 4.3. 資料處理 17 4.4. 實證結果 18 4.5. 穩健測試 20 4.6. 實證結論 32 5. 結論與建議 33 參考文獻 34 附錄 37

    Abadie, A., and Gardeazabal, J. (2003). The economic costs of conflict: A case study of the Basque Country. American Economic Review, 93(1), 113-132.
    Abadie, A., Diamond, A., and Hainmueller, J. (2010). Synthetic control methods for comparative case studies: Estimating the effect of California’s tobacco control program. Journal of the American Statistical Association, 105(490), 493-505.
    Abadie, A., Diamond, A., and Hainmueller, J. (2015). Comparative politics and the synthetic control method. American Journal of Political Science, 59(2), 495-510.
    Aichele, R., and Felbermayr, G. (2013). The effect of the Kyoto Protocol on carbon emissions. Journal of Policy Analysis and Management, 32(4), 731-757.
    Almer, C., and Winkler, R. (2017). Analyzing the effectiveness of international environmental policies: The case of the Kyoto Protocol. Journal of Environmental Economics and Management, 82, 125-151.
    Bai, J. (2009). Panel data models with interactive fixed effects. Econometrica, 77(4), 1229-1279.
    Breidenich, C., Magraw, D., Rowley, A., and Rubin, J. (1998). The Kyoto Protocol to the United Nations Framework Convention on Climate Change. The American Journal of International Law, 92(2), 315-331.
    Cavallo, E., Galiani, S., Noy, I., and Pantano, J. (2013). Catastrophic natural disasters and economic growth. Review of Economics and Statistics, 95(5), 1549-1561.
    Doudchenko, N., & Imbens, G. W. (2016). Balancing, regression, difference-in-differences and synthetic control methods: A synthesis. NBER Working Paper.
    Fortems‐Cheiney, A., Saunois, M., Pison, I., Chevallier, F., Bousquet, P., Cressot, C., ... and Young, D. (2015). Increase in HFC‐134a emissions in response to the success of the Montreal Protocol. Journal of Geophysical Research: Atmospheres, 120(22), 11-728.
    Friedman J., Hastie T., and Tibshirani R. (2010). Regularization paths for generalized linear models via coordinate descent. Journal of Statistical Software, 33(1), 1–22.
    Grunewald, N., and Martinez‐Zarzoso, I. (2016). Did the Kyoto Protocol fail? An evaluation of the effect of the Kyoto Protocol on CO2 emissions. Environment and Development Economics, 21(1), 1-22.
    Hsiao, C., Ching, H. S., and Wan, S. K. (2012). A panel data approach for program evaluation: Measuring the benefits of political and economic integration of Hong Kong with mainland China. Journal of Applied Econometrics, 27(5), 705.
    Intergovernmental Panel on Climate Change (IPCC). (2014). Climate Change 2014: Synthesis report. Contribution of working groups I, II and III to the fifth assessment report of the Intergovernmental Panel on Climate Change. Geneva, Switzerland: IPCC.
    Jain, P. C. (1993). Greenhouse effect and climate change: Scientific basis and overview. Renewable Energy, 3(4-5), 403-420.
    Kallbekken, S., and Hovi, J. (2007). The price of non-compliance with the Kyoto Protocol: The remarkable case of Norway. International Environmental Agreements: Politics, Law and Economics, 7(1), 1-15.
    Kaul, A., Klobner, S., Pfeifer, G., and Schieler, M. (2018). Synthetic control methods: Never use all pre‐intervention outcomes together with covariates. Working Paper.
    Kinn, D. (2018). Synthetic control methods and big data. Working Paper.
    Krug, J. H. (2018). Accounting of GHG emissions and removals from forest management: A long road from Kyoto to Paris. Carbon Balance and Management, 1(13), 1-11.
    Maamoun, N. (2019). The Kyoto Protocol: Empirical evidence of a hidden success. Journal of Environmental Economics and Management, 95, 227-256.
    O’Neill, S., Kreif, N., Grieve, R., Sutton, M., and Sekhon, J. S. (2016). Estimating causal effects: Considering three alternatives to difference-in-differences estimation. Health Services and Outcomes Research Methodology, 16(1-2), 1-21.
    Soetaert, K., Van den Meersche, K., and van Oevelen, D. (2009). limSolve: Solving Linear Inverse Models. R package version 1.5
    Xu, Y. (2017). Generalized synthetic control method: Causal inference with interactive fixed effects models. Political Analysis, 25(1), 57-76.

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