本文選題：碳強(qiáng)度 + 面板數(shù)據(jù)�。� 參考：《中國礦業(yè)大學(xué)》2017年碩士論文

【摘要】：本文通過通徑分析明確了能源消費(fèi)結(jié)構(gòu)、產(chǎn)業(yè)結(jié)構(gòu)、城市化率、技術(shù)進(jìn)步水平、經(jīng)濟(jì)水平五個影響因素相互間的關(guān)系及它們與碳強(qiáng)度之間的直間接關(guān)系,并進(jìn)行了影響機(jī)理分析。接著綜合采用STIRPAT擴(kuò)展模型和面板數(shù)據(jù)模型從國家層面和八大綜合經(jīng)濟(jì)區(qū)域?qū)用鎸ξ覈紡?qiáng)度的影響因素進(jìn)行了分析研究。在此基礎(chǔ)上,以嶺回歸和替代彈性等相關(guān)方法得到了各變量變動對碳強(qiáng)度影響的靈敏度矩陣,并進(jìn)行了靈敏度分析,同時也計算了相關(guān)條件下對實(shí)現(xiàn)“十三五”規(guī)劃碳強(qiáng)度目標(biāo)的貢獻(xiàn)潛力。本文的主要結(jié)論如下:(1)通過通徑分析研究發(fā)現(xiàn):從整體來看,能源消費(fèi)結(jié)構(gòu)和產(chǎn)業(yè)結(jié)構(gòu)對碳強(qiáng)度的總影響為正,對碳強(qiáng)度的增加是促進(jìn)的,城市化率,技術(shù)進(jìn)步水平和經(jīng)濟(jì)水平比對碳強(qiáng)度的總影響為負(fù),對碳強(qiáng)度的增加是抑制的。(2)通過影響機(jī)理分析,每個因素都通過其他因素對碳強(qiáng)度有間接的影響,只是各自的間接影響程度強(qiáng)弱不同。其中產(chǎn)業(yè)結(jié)構(gòu)和經(jīng)濟(jì)水平通過其他因素對碳強(qiáng)度的總間接影響都是正向增強(qiáng),直接影響卻是負(fù)向減弱;而能源消費(fèi)結(jié)構(gòu)、城市化率和技術(shù)進(jìn)步水平通過其他因素對碳強(qiáng)度的總間接影響確都是負(fù)向減弱,直接影響卻是正向增強(qiáng)。能源消費(fèi)結(jié)構(gòu)對碳強(qiáng)度的增加主要是通過直接影響來促進(jìn)的,總間接影響有一定的抑制作用;產(chǎn)業(yè)結(jié)構(gòu)對碳強(qiáng)度的增加主要是通過總間接影響來促進(jìn)的,而直接影響是抑制的;城市化率對碳強(qiáng)度的增加更多的是通過總間接影響來產(chǎn)生抑制作用;技術(shù)進(jìn)步水平對碳強(qiáng)度的增加更多的是通過總間接影響來產(chǎn)生抑制作用;經(jīng)濟(jì)水平對碳強(qiáng)度的增加主要是通過直接影響來抑制的,而總間接影響是促進(jìn)的。(3)在全國和八大區(qū)域模型中產(chǎn)業(yè)結(jié)構(gòu)對碳強(qiáng)度均產(chǎn)生顯著正影響,能源消費(fèi)結(jié)構(gòu)對碳強(qiáng)度也普遍表現(xiàn)為顯著正影響(除了南部沿海模型表現(xiàn)為負(fù)相關(guān)以外);技術(shù)進(jìn)步對碳強(qiáng)度普遍產(chǎn)生顯著負(fù)影響;經(jīng)濟(jì)水平對碳強(qiáng)度也普遍體現(xiàn)顯著負(fù)影響;而城市化率則表現(xiàn)為除了大西南區(qū)域顯著負(fù)相關(guān)以外,其他模型區(qū)域均不顯著。經(jīng)濟(jì)增長和技術(shù)進(jìn)步對碳強(qiáng)度的降低有促進(jìn)作用,產(chǎn)業(yè)結(jié)構(gòu)和能源消費(fèi)結(jié)構(gòu)對碳強(qiáng)度的降低有抑制作用。在全國總體模型中,產(chǎn)業(yè)結(jié)構(gòu)對我國碳強(qiáng)度的影響程度是最強(qiáng)的,技術(shù)進(jìn)步和經(jīng)濟(jì)水平對我國碳強(qiáng)度的影響程度次之,能源消費(fèi)結(jié)構(gòu)對我國碳強(qiáng)度的影響程度最弱。在區(qū)域模型的研究中,各因素對碳強(qiáng)度的影響程度在區(qū)域之間是存在顯著差異的。降低煤炭消費(fèi)占比,降低第二產(chǎn)業(yè)占比,增加科技研發(fā)投入和提高人均GDP水平都是符合低碳發(fā)展需要的,他們都是實(shí)現(xiàn)我國碳強(qiáng)度目標(biāo)的重要路徑。(4)煤炭消費(fèi)占比降低1個百分點(diǎn),若分別完全由第二次產(chǎn)業(yè)占比、RD機(jī)構(gòu)投入比重比重、人均GDP水平來替代,則碳強(qiáng)度相應(yīng)降低0.1766、0.1962、0.2063個百分點(diǎn)。根據(jù)“十三五”規(guī)劃相關(guān)目標(biāo)及政策預(yù)測,通過靈敏度矩陣可知,當(dāng)降低煤炭消費(fèi)比例5%,降低第二產(chǎn)業(yè)占比5.5%,提高RD機(jī)構(gòu)投入比重0.4%,提高人均GDP水平10.1%時,到2020年可以使碳強(qiáng)度降低4.46個百分點(diǎn),對實(shí)現(xiàn)“十三五”規(guī)劃碳強(qiáng)度目標(biāo)(碳強(qiáng)度降低18%)的貢獻(xiàn)潛力為24.78%。
[Abstract]:Through path analysis the energy consumption structure, industrial structure, city rate, the level of technological progress, direct and indirect relationship between the economic level of the five factors and their interactions with carbon intensity, and the influence mechanism analysis. Then used STIRPAT model and panel data model are studied in the face of the influence factors of China's carbon intensity from the national level and the eight integrated economic region. On this basis, Yiling regression and elasticity of substitution and other related method to get the sensitivity matrix of the variable effects on carbon intensity, and the sensitivity analysis, also calculated the potential contribution to the realization of "13th Five-Year plan" carbon intensity the target related conditions. The main conclusions of this paper are as follows: (1) through path analysis found: on the whole, the energy consumption structure and industrial structure of carbon intensity The total effect is positive, the carbon intensity is to promote the city rate, total effect of technological progress and economic level on carbon intensity is negative, the carbon intensity is inhibited. (2) the influence mechanism analysis, each factor through other factors on carbon intensity have indirect effect only indirectly, their influence degree is different. The industrial structure and the level of the economy through other factors total indirect effect on carbon intensity is positive enhancement, direct effect is negative and decreased; the energy consumption structure, city rate and the level of technological progress through other factors the total indirect effect on carbon intensity that is negative to weaken, direct influence is positive. Enhance the increase in energy consumption structure on carbon intensity is mainly promoted through direct effects, the total indirect effect has certain inhibitory effect; industrial structure on carbon intensity increase If the total indirect effect to promote, and the direct effect is suppressed; increase the rate of City carbon intensity is more through the total indirect effect to produce inhibition; increase the level of technological progress on carbon intensity is more through the total indirect effect to produce inhibition; increase the economic level of the main carbon intensity is inhibited by the direct effects and indirect effects is to promote the total. (3) in the country and eight regions in the model of industrial structure on carbon intensity has a significant positive impact on the carbon intensity of energy consumption structure also generally showed significant positive effects (in addition to the performance of the southern coastal model is negatively related to outside technology); progress generally have a significant negative impact on the economic level of carbon intensity; carbon intensity is generally reflected a significant negative impact; while the city rate showed a significant negative correlation in the southwest region, other regional model Were not significant. The economic growth and technological progress have stimulative effect to reduce carbon intensity, industrial structure and energy consumption structure to reduce the carbon intensity of inhibition in the whole country. In the model, the influence degree of the industrial structure of China's carbon intensity is the strongest, technological progress and economic level of China's carbon intensity the influence of the degree of influence of the weakest energy consumption structure of China's carbon intensity in the study area. In the model, the impact of various factors on carbon intensity have a significant difference in area between. To reduce coal consumption accounted for second, reducing industrial proportion, increase R & D investment and improve the level of GDP per capita it meets the needs of low-carbon development, they are an important path to achieve the target of carbon intensity in China. (4) coal consumption accounted for 1 percentage points lower, respectively, if entirely by the second industries accounted for the proportion of investment institutions, RD The proportion of alternative to the level of GDP per capita, the carbon intensity decreased by 0.1766,0.1962,0.2063 percentage points. According to the "13th Five-Year" planning objectives and policies predicted by the sensitivity matrix shows when reduce the proportion of coal consumption reduced 5%, second industries accounted for 5.5%, the proportion of investment increased 0.4% RD, increased by 10.1% per capita GDP, 2020 the carbon intensity decreased by 4.46 percentage points, to achieve the "13th Five-Year plan" carbon intensity targets (18% reduction in carbon intensity) potential contribution to 24.78%.

【學(xué)位授予單位】：中國礦業(yè)大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：X321

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