本文選題：能源效率 + 空間相關(guān)性�。� 參考：《浙江工商大學(xué)》2017年碩士論文

【摘要】：自改革開放以來,隨著經(jīng)濟(jì)總量與實(shí)力的不斷增長,經(jīng)濟(jì)增長對能源的需求不斷增加,石油與煤炭資源過渡使用。雖然國家近些年來出臺許多政策控制能源生產(chǎn)總量,同時(shí)加大國外進(jìn)口,但是仍舊難以彌補(bǔ)能源的缺口。在新能源未被發(fā)現(xiàn)利用之前,提高能源利用效率迫在眉睫。在回顧及分析已有學(xué)者對能源效率的關(guān)聯(lián)及分異性研究后,在此基礎(chǔ)上,對能源效率的理論及其模型進(jìn)行闡釋。本文選擇30個(gè)省份地區(qū)(除西藏)的數(shù)據(jù)進(jìn)行分析。首先采用全局自相關(guān)檢驗(yàn)統(tǒng)計(jì)量Moran'I值進(jìn)行全局關(guān)聯(lián)探索,發(fā)現(xiàn)能源效率在空間上有十分顯著的空間正相關(guān)性。然后再利用局部空間相關(guān)統(tǒng)計(jì)量LISA值及其顯著性檢驗(yàn),發(fā)現(xiàn)局部空間聚集現(xiàn)象明顯。通過Moran散點(diǎn)圖的結(jié)果,可以發(fā)現(xiàn)大部分省份位于第三象限與第一象限,即低值省份與低值省份為臨,高值省份與高值省份相近,說明地區(qū)數(shù)值存在正空間自相關(guān)性。在發(fā)現(xiàn)存在明顯的全局及局部空間關(guān)聯(lián)性后,利用空間截面回歸模型及空間杜賓誤差模型對研究地域進(jìn)行空間計(jì)量回歸分析。結(jié)果顯示空間影響系數(shù)通過顯著性檢驗(yàn),說明空間關(guān)聯(lián)性較強(qiáng)。與普通OLS回歸模型比較后發(fā)現(xiàn),空間滯后模型與空間誤差模型的模擬效果更佳。接著利用空間杜賓誤差模型從時(shí)空角度分析其空間關(guān)聯(lián)性,發(fā)現(xiàn)不但能源效率的地區(qū)關(guān)聯(lián)性明顯,同時(shí)發(fā)現(xiàn)解釋變量及誤差項(xiàng)之間也有較強(qiáng)的地區(qū)關(guān)聯(lián)性。由于地區(qū)之間的要素不勻質(zhì)性,導(dǎo)致地區(qū)差異性存在。本文采用GWR模型對四年的截面進(jìn)行分析對比。利用DIFF of Criterion對局部回歸系數(shù)的顯著性進(jìn)行檢驗(yàn)判斷,發(fā)現(xiàn)大部分影響因素都很明顯,說明局部回歸效果優(yōu)于全局回歸,同時(shí)殘差檢驗(yàn)也證明GWR模型效果優(yōu)于普通OLS回歸分析。結(jié)合以上實(shí)證結(jié)果發(fā)現(xiàn),人均GDP,人均專利數(shù)及工業(yè)生產(chǎn)者購進(jìn)價(jià)格指數(shù)的增加對能源使用效率的提高主要具有正向促進(jìn)作用,但空間杜賓誤差模型中工業(yè)生產(chǎn)者購進(jìn)價(jià)格指數(shù)的溢出效應(yīng)系數(shù)為正值,說明周圍地區(qū)價(jià)格的上升對本地的能源效率有抑制作用。第二、三產(chǎn)業(yè)比重的增加對本地的能源使用效率的提高具有抑制作用,但在空間杜賓誤差模型中其溢出效應(yīng)系數(shù)為負(fù)值,即周圍地區(qū)該要素的增加促進(jìn)本地能源使用效率的提高。在GWR模型中,在2008年受全球金融危機(jī)影響,所有地區(qū)工業(yè)生產(chǎn)者購進(jìn)價(jià)格指數(shù)的系數(shù)均為正值,即對能源使用效率的提高具有抑制作用。本文同時(shí)發(fā)現(xiàn)各地區(qū)其他影響能源效率因素的稟賦不同,在空間上也具有明顯溢出作用。基于上述結(jié)論提出了相關(guān)政策建議。本文主要?jiǎng)?chuàng)新點(diǎn):利用空間杜賓誤差模型同時(shí)將選取的四個(gè)指標(biāo)的空間滯后影響考慮在內(nèi),同時(shí)探討能源要素的直接與溢出效應(yīng)。然而這些要素并不能完全反應(yīng)影響能源使用效率的具體情況,各地區(qū)由于其他影響能源效率因素的稟賦不同,也會對周圍地區(qū)有溢出影響,空間杜賓誤差模型可以將這些因素放在誤差項(xiàng)里進(jìn)行整體分析。
[Abstract]:Since the reform and opening up, with the continuous growth of the total economy and the strength of the economic growth and the increasing demand for energy, petroleum and coal resources in transition countries in recent years. Although the introduction of many policies to control the total energy production, while increasing foreign imports, but still difficult to compensate for the energy gap. Before the new energy has not been found by and improve the efficiency of energy use is imminent. In the review and analysis of scholars related to energy efficiency and specific research, based on the interpretation of the theory and model of energy efficiency. This paper chooses 30 provinces (except Tibet) data were analyzed. Firstly, using global autocorrelation test statistic Moran'I value the global association of exploration, found that energy efficiency has a very significant positive correlation between space and space. And then using local spatial correlation statistics and LISA value The test of significance, find local spatial aggregation phenomenon is obvious. The Moran plot results can be found in most of the provinces in the first quadrant and third quadrant, namely low value and low value for the provinces of provinces, provinces of high value and high value provinces are similar, there is a numerical description of regional spatial autocorrelation. In found obvious the global and local spatial correlation, regression model and spatial Durbin error model for the study of regional spatial econometric regression analysis using the space section. The results showed that the coefficient of spatial effects through the significant test, the spatial relevance of the discovery and the ordinary OLS regression model. After comparison, better simulation results and the spatial error model of spatial lag model the use of space. Then the Durbin error model to analyze the spatial relationship from the angle of time and space, we found that not only the area association of energy efficiency was also found to explain There are also regional strong correlation between variables and the error term. Because of elements between regions is not uniform, leading to the existence of regional differences. This paper uses a comparative analysis on the cross section of four years of the GWR model. Of Criterion was on the local regression coefficients were tested by judge DIFF, found that most influence factors are obviously, that is better than the global local regression regression, and residual test also proved that GWR model is better than the effect of general OLS regression analysis. According to the above empirical results, the per capita GDP, per capita number of patents and industrial producer price index increased mainly has positive effect on energy use efficiency, but the spillover coefficient spatial Durbin error the model of industrial producer price index is positive, indicating the area around the price rise has inhibitory effect on local energy efficiency second, third. Industry's increasing use efficiency of local energy increase with inhibition, but in space Durbin error model and its spillover effect coefficient is negative, increasing the elements of the surrounding area to promote local energy use efficiency. In GWR model, in 2008 by the global financial crisis, the purchase price index area of industrial producers coefficients were positive, which has inhibitory effect on energy use efficiency. This paper also found that the influence of other area energy efficiency factor endowment different, also has obvious spillover effects in space. Based on the above conclusions relevant policy recommendations were put forward. The main innovation of this paper: four indicators using spatial Durbin at the same time the error model of the spatial lag effect into account, and to explore the direct and spillover effects of energy factors. However these factors can not completely reverse Effect of specific energy efficiency, the energy efficiency effect due to other factors endowment different, will also have a spillover effect on the surrounding area, spatial Durbin error model of these factors can be put in error in the overall analysis.

【學(xué)位授予單位】：浙江工商大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：F224;F426.2

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