本文選題：人力資本 + 碳排放強(qiáng)度�。� 參考：《山東師范大學(xué)》2017年碩士論文

【摘要】：氣候變化是全世界共同面臨的重大挑戰(zhàn)之一。為了抑制氣候變化,各國(guó)政府都在為此做出努力。我國(guó)政府在巴黎氣候大會(huì)上承諾2030年左右二氧化碳排放量達(dá)到峰值等具體目標(biāo)。人力資本作為非物質(zhì)資本,是經(jīng)濟(jì)發(fā)展的源動(dòng)力,對(duì)減緩氣候變化具有重要影響。本文以除西藏之外的30個(gè)省區(qū)作為研究區(qū)域,探究各省區(qū)四類人力資本存量以及碳排放強(qiáng)度的時(shí)空變動(dòng)趨勢(shì);在剖析人力資本對(duì)減緩氣候變化作用機(jī)理的基礎(chǔ)上,運(yùn)用空間計(jì)量模型分析人力資本對(duì)減緩氣候變化的影響程度,進(jìn)而為中國(guó)減緩氣候變化提供重要科學(xué)依據(jù)。全文重要分為六個(gè)部分:第一部分是引言部分,主要提出了論文的研究背景、理論及實(shí)踐意義、國(guó)內(nèi)外相關(guān)研究、相關(guān)研究評(píng)述、研究?jī)?nèi)容、研究方法與技術(shù)路線等。第二部分為理論部分,論文主要對(duì)人力資本、氣候變化、碳排放等概念進(jìn)行解析,并系統(tǒng)闡述了人力資本及碳排放的理論基礎(chǔ),主要包含了現(xiàn)代人力資本理論、內(nèi)生增長(zhǎng)理論、碳庫茲涅茨曲線理論、碳足跡理論。最后闡述了人力資本對(duì)減緩氣候變化的作用機(jī)制等。第三部分,基于人力資本的投資對(duì)人力資本進(jìn)行分類、測(cè)算,描述中國(guó)1995年以來各省區(qū)時(shí)空變動(dòng)趨勢(shì)。得到的結(jié)論有:(1)在時(shí)間層面上,各類人力資本均在波動(dòng)中上升;(2)在空間上,各類人力資本基礎(chǔ)出現(xiàn)東高-西低的空間分異特征。第四部分,在分析中國(guó)各省區(qū)近20年來碳排放強(qiáng)度時(shí)空變動(dòng)趨勢(shì)的基礎(chǔ)上,探討四類人力資本與碳排放強(qiáng)度的關(guān)系及其作用機(jī)理。得到如下結(jié)論:(1)在時(shí)間上,我國(guó)各省區(qū)碳排放強(qiáng)度在波動(dòng)中不斷下降;(2)在空間上,我國(guó)碳排放強(qiáng)度呈現(xiàn)了北高-南低、高值-高值、低值-低值分別集聚的空間分異特征。然后,從經(jīng)濟(jì)、農(nóng)業(yè)、社會(huì)、資源等四個(gè)方面分析減緩氣候變化的影響因素。最后,先對(duì)各類型人力資本和碳排放強(qiáng)度做了簡(jiǎn)單的相關(guān)性分析,然后分析各類型人力資本對(duì)減緩氣候變化的作用機(jī)理,發(fā)現(xiàn)各類人力資本通過作用于經(jīng)濟(jì)發(fā)展、居民收入與消費(fèi)水平、技術(shù)創(chuàng)新與進(jìn)步、城市化水平等間接作用于碳排放強(qiáng)度,進(jìn)而影響氣候變化。第五部分,將各類型人力資本作為解釋變量,技術(shù)因素、財(cái)富因素作為控制變量,碳排放強(qiáng)度作為被解釋變量,基于擴(kuò)展的環(huán)境壓力模型,運(yùn)用1995-2014年中國(guó)各省區(qū)面板數(shù)據(jù)從全國(guó)、東、中、西及東北范圍內(nèi)分別建立空間杜賓模型、空間固定效應(yīng)模型和空間隨機(jī)模型。結(jié)論表明,基礎(chǔ)型人力資本和知識(shí)型人力資本對(duì)碳排放強(qiáng)度呈現(xiàn)正向效應(yīng),技能型人力資本與制度性人力資本對(duì)碳排放強(qiáng)度具有負(fù)向效應(yīng);人口因素各指標(biāo)的估計(jì)系數(shù)符號(hào)的正負(fù)性及顯著性均不穩(wěn)定;財(cái)富因素中的lnPGDP的估計(jì)系數(shù)在全國(guó)及東部地區(qū)為正,而在中、西及東北地區(qū)lnPGDP影響系數(shù)為負(fù),碳排放強(qiáng)度隨著經(jīng)濟(jì)的增長(zhǎng)而減小;反映第三產(chǎn)業(yè)水平的變量lnTI估計(jì)系數(shù)只有東、中部地區(qū)顯著,全國(guó)、西部及東北地區(qū)均不顯著;技術(shù)因素中的lnRD的估計(jì)系數(shù)符號(hào)的正負(fù)性與顯著性也不穩(wěn)定,能源強(qiáng)度的系數(shù)均為正且顯著。第六部分,總結(jié)論文的主要結(jié)論,并從加強(qiáng)人力資本、優(yōu)化人力資本配置、培養(yǎng)低碳技術(shù)人才、調(diào)節(jié)產(chǎn)業(yè)機(jī)構(gòu)、加大宏觀調(diào)控等方面提出減緩氣候變化的對(duì)策建議。
[Abstract]:Climate change is one of the major challenges facing the world. In order to curb climate change, governments are making efforts to do so. The government of our government at the Paris climate conference promised specific targets such as the peak value of carbon dioxide emissions around 2030. As a non material capital, human capital is the source of economic development and the reduction of gas. In this paper, 30 provinces and regions other than Tibet are used as research areas to explore the four types of human capital stock and the spatio-temporal change trend of carbon emission intensity in each province and region. Based on the analysis of the mechanism of the effect of human capital on mitigation of climate change, the spatial calculation model is used to analyze the mitigation of climate change by human capital. The impact degree of the paper will provide an important scientific basis for the mitigation of climate change in China. The full text is divided into six parts: the first part is an introduction, which mainly puts forward the research background, theoretical and practical significance, relevant research at home and abroad, related research review, research content, research method and technical route, etc. the second part is the theory. Part of the paper, the paper analyzes the concepts of human capital, climate change, carbon emission and so on, and systematically expounds the theoretical basis of human capital and carbon emissions, including the modern human capital theory, endogenous growth theory, carbon Kuznets curve theory and carbon footprint theory. Finally, the role of human capital on mitigation of climate change is expounded. Mechanism and so on. The third part, based on human capital investment to classify human capital, calculate and describe the temporal and spatial variation trend of China's provinces and regions since 1995. The conclusions are as follows: (1) in the time level, all kinds of human capital are rising in the fluctuation; (2) in space, the spatial differentiation characteristics of all kinds of human capital base in East High West low In the fourth part, based on the analysis of the temporal and spatial variation trend of carbon emission intensity in China's provinces in the last 20 years, the relationship between the four types of human capital and carbon emission intensity and its mechanism are discussed. (1) in time, the carbon emission intensity of China's provinces and regions is decreasing in the fluctuation; (2) in space, the carbon emission intensity in China presents The spatial differentiation characteristics of the North High South low, high value, high value, low value and low value are analyzed respectively. Then, the influence factors of climate change mitigation are analyzed from four aspects, such as economy, agriculture, society and resources. Finally, a simple correlation analysis is made to the various types of human capital and carbon emission intensity, and then the different types of human capital are analyzed to reduce the gas. In the fifth part, human capital is used as the explanatory variable, the technical factor and the wealth factor as the control change. Based on the extended environmental pressure model, the spatial doberen model, the spatial fixed effect model and the spatial random model were established from the national, East, middle, West and northeast of China, based on the extended environmental pressure model, and the basic human capital and the knowledge-based human capital were established. The carbon emission intensity has a positive effect, the skilled human capital and the institutional human capital have a negative effect on the carbon emission intensity; the positive and negative of the estimation coefficient symbols of the population factors are both positive and negative; the estimation coefficient of lnPGDP in the wealth factors is positive in the national and eastern regions, and in the middle, West and northeast region lnPGDP The influence coefficient is negative, and the carbon emission intensity decreases with the economic growth; the variable lnTI estimation coefficient, which reflects the level of the third industry, is only East, the central region is significant, the whole country, the West and the Northeast are not significant; the positive and negative of the lnRD estimation coefficient symbol in the technical factors are also not stable, and the energy intensity coefficient is all positive and the coefficient of energy intensity is positive and the coefficient of energy intensity is positive and the coefficient of energy intensity is positive and the coefficient of energy intensity is positive and the coefficient of energy intensity is positive and The sixth part summarizes the main conclusions of the paper, and puts forward some suggestions on the mitigation of climate change from the aspects of strengthening human capital, optimizing human capital allocation, cultivating low carbon technical personnel, adjusting industrial institutions and increasing macro regulation and control.

【學(xué)位授予單位】：山東師范大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：K901

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 佟金萍;陳國(guó)棟;楊足膺;柏楚;;居民消費(fèi)水平對(duì)生活碳排放的門檻效應(yīng)研究[J];干旱區(qū)資源與環(huán)境;2017年01期

2 周縣華;范慶泉;;碳強(qiáng)度減排目標(biāo)的實(shí)現(xiàn)機(jī)制與行業(yè)減排路徑的優(yōu)化設(shè)計(jì)[J];世界經(jīng)濟(jì);2016年07期

3 黃杰;;人口結(jié)構(gòu)變動(dòng)對(duì)中國(guó)碳排放績(jī)效的影響研究[J];西北人口;2016年02期

4 田成詩;郝艷;李文靜;曲本亮;;中國(guó)人口年齡結(jié)構(gòu)對(duì)碳排放的影響[J];資源科學(xué);2015年12期

5 彭斯震;何霄嘉;張九天;馬欣;孫傅;劉少華;;中國(guó)適應(yīng)氣候變化政策現(xiàn)狀、問題和建議[J];中國(guó)人口·資源與環(huán)境;2015年09期

6 王長(zhǎng)建;汪菲;張虹鷗;;新疆能源消費(fèi)碳排放過程及其影響因素——基于擴(kuò)展的Kaya恒等式[J];生態(tài)學(xué)報(bào);2016年08期

7 劉金濤;;異質(zhì)型人力資本對(duì)經(jīng)濟(jì)增長(zhǎng)作用機(jī)制研究[J];經(jīng)濟(jì)問題;2015年08期

8 洪業(yè)應(yīng);向思潔;陳景信;;重慶市人口規(guī)模、結(jié)構(gòu)對(duì)碳排放影響的實(shí)證研究——基于STIRPAT模型的分析[J];西北人口;2015年03期

9 李斌;張瑤;;異質(zhì)性人力資本與產(chǎn)業(yè)結(jié)構(gòu)變動(dòng)——基于省級(jí)動(dòng)態(tài)面板的系統(tǒng)GMM估計(jì)[J];商業(yè)研究;2015年05期

10 魏婷;董文杰;武炳義;楊世莉;燕青;;近期碳排放趨勢(shì)對(duì)氣候變化歷史責(zé)任歸因的影響[J];科學(xué)通報(bào);2015年07期

相關(guān)碩士學(xué)位論文 前1條

1 邱巨龍;西北—華南地區(qū)家庭碳排放人口影響因素對(duì)比研究[D];蘭州大學(xué);2013年

，

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