Kyoto Protocol’s Carbon Dioxide Emission Reduction Effects Analysis-An Application of Rolling Regression
Bibliographic record
Abstract
[[abstract]]本研究以滾動迴歸法分析1950年-2010年,對京都議定書抱持不同態度的四組國家以及不同經濟發展程度和京都議定書參與程度的五個單一國家的碳排狀況。四組國家分別為16個已簽署京都議定書且在其國內通過法律認證的條約綱要控制國家(澳洲、奧地利、比利時、丹麥、芬蘭、法國、德國、希臘、義大利、日本、挪威、荷蘭、紐西蘭、西班牙、瑞典、英國),雖簽署京都議定書但並未在其國內通過立法認證的條約綱要控制國(美國及2012年退出的加拿大),簽署但為非條約綱要控制的大型開發中國家(中國、印度、巴西),和較小型開發中國家(台灣和南韓)。五個抱持不同態度並且有著不同減碳立場的單一經濟體分別為德國、義大利、日本、印度和台灣。我們使用1950年至2010年每人二氧化碳排放量和實質每人國民所得的追蹤資料和單一國家時間序列資料,以滾動迴歸法分析,將1950年-1990年41年期資料為起始滾動期間,逐次加入一期新資料並剔除第一期資料,估計並計算21個年度區間倒U型環境顧志耐曲線的轉折點,透過轉折點變化來呈現對京都議定書抱持不同態度有著不同立場的國家,隨著時間的遞移,碳排轉折點的變化。藉著此一研究,可以了解對京都議定書包括在不同立場和不同參與程度國家的碳排狀況及碳減排的效果。本研究結果發現,京都議定書簽訂後,全力支持且參與京都議定書的條約綱要控制國16個OECD國家的轉折點有著明顯下降趨勢;而美國、加拿大轉折點無顯著下降情況,甚至部分年份呈現上升狀況;非條約綱要控制國的中、印、巴三國和開發中小型經濟體國家台灣、韓國,呈現碳排持續擴張狀況,即使有轉折點也常發生在資料區外。由此可推論京都議定書對於全力支持且須負強制減排責任的國家,在簽訂京都議定書後,二氧化碳的排放具有明顯的抑制效果。又本研究在單一國家時間序列分析發現,在京都議定書簽訂後,德國、日本兩國扣除資料不顯著年份其轉折點呈現持續下降趨勢;義大利轉折點僅在部分年度區間出現短暫的下降趨勢,之後在歐債危機期間,其碳排持續擴張;印度和台灣則與跨國區域的結論相同,碳排持續擴張,雖有轉折點的呈現卻多發生在資料區外。由研究結果可推論,未來碳減排要成功,各個不同經濟發展階段的國家,均需全力支持並承擔起強制減排責任。 This study investigates the relationships of CO2 emissions and income for 23 countries with different involvement the international treaty of the Kyoto Protocol. This study inspects the empirical time-path of the turning points of the inverted U-shaped Environmental Kuznets Curve by Rolling Regression technique for four panel groups of countries and five single countries with time series data. The panel data include 23 countries; we classify them to four groups with different involvement in and attitude to Kyoto Protocol. The first group is 16 countries of OECD. They are Australia, Austria, Belgium, Denmark, Finland, France, Germany, Greece, Italy, Japan, Norway, the Netherlands, New Zealand, Spain, Sweden, and United Kingdom. These 16 countries had signed and ratified the Kyoto Protocol. The second group is the US and Canada. The US had signed but never ratified. Canada had signed and ratified but quits Kyoto Protocol in 2012. The third group includes large developing countries such as China, India and Brazil. In current version of Kyoto Protocol, these countries take no responsibility to reduce emission. The last group is small developing economies such as Taiwan, and South Korea. And this study chooses 5 (Germany, Italy, Japan, India and Taiwan) among the 23 countries to investigate single country emission patterns. The results suggest that there are significant carbon dioxide reduction effects in the chosen 16 countries of OECD with a declining trend of turning point. For the US, Canada and developing countries, the EKC turning points have no significant declining trend. In some periods of time, the turning points do not exist. In the single country analysis, the turning points of Germany and Japan, present downward trends. The turning points of Italy have downward trend in most periods of time, except in recent financial crisis. For India and Taiwan, the carbon emissions continue their expansion trends. The results evidence that those countries take carbon-reduction responsibility through Kyoto Protocol participation, have significant carbon reduction effects. For the carbon reduction to be successful in the future, more countries need to support international carbon reduction treaty and take responsibility for emission reductions.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".