本文選題：鋼鐵行業(yè) + 數(shù)據(jù)包絡(luò)分析��； 參考：《重慶工商大學(xué)》2017年碩士論文

【摘要】：鋼鐵行業(yè)作為國(guó)民經(jīng)濟(jì)的重要產(chǎn)業(yè),在長(zhǎng)期的經(jīng)濟(jì)建設(shè)過(guò)程中,支撐和保障了相關(guān)產(chǎn)業(yè)的發(fā)展,強(qiáng)有力地推動(dòng)我國(guó)工業(yè)化和現(xiàn)代化進(jìn)程。當(dāng)前我國(guó)處于建設(shè)制造強(qiáng)國(guó)的開(kāi)局階段,也是鋼鐵行業(yè)供給側(cè)改革的關(guān)鍵時(shí)期。因此,測(cè)度我國(guó)鋼鐵行業(yè)的全要素生產(chǎn)率的變動(dòng)情況,分析并找出影響其效率和生產(chǎn)率的有關(guān)因素,針對(duì)性地提出相關(guān)的對(duì)策建議,對(duì)于我國(guó)鋼鐵行業(yè)擺脫目前的發(fā)展困境,顯得十分迫切,是值得關(guān)注并深入研究的重要課題。文章首先對(duì)鋼鐵行業(yè)效率與生產(chǎn)率的有關(guān)文獻(xiàn)進(jìn)行梳理,接著分析鋼鐵行業(yè)的現(xiàn)狀及存在的問(wèn)題。然后,基于省級(jí)面板數(shù)據(jù),構(gòu)建相應(yīng)的投入產(chǎn)出指標(biāo)體系,通過(guò)DEA模型對(duì)28個(gè)省市鋼鐵行業(yè)的效率和生產(chǎn)率進(jìn)行測(cè)度研究。最后,選取相關(guān)的指標(biāo)因素,運(yùn)用回歸方法分析這些因素對(duì)鋼鐵行業(yè)的作用力度和影響方向。經(jīng)研究發(fā)現(xiàn):第一,整個(gè)鋼鐵行業(yè)的技術(shù)效率比較低。從不同區(qū)域來(lái)看,東部地區(qū)在技術(shù)效率層面有明顯的優(yōu)勢(shì)。排名前15位的省市中,東部地區(qū)的10個(gè)省市全都包含在內(nèi),中部地區(qū)有4個(gè)省市,而西部地區(qū)只有1個(gè)省市。第二,通過(guò)BCC模型分解技術(shù)效率發(fā)現(xiàn),鋼鐵行業(yè)技術(shù)效率偏低的主要原因在于純技術(shù)效率導(dǎo)致的。規(guī)模效率雖然沒(méi)有達(dá)到生產(chǎn)前沿面上,但是絕大多數(shù)省市表現(xiàn)出了規(guī)模報(bào)酬遞增的趨勢(shì),這表明鋼鐵行業(yè)是存在一定的規(guī)模效應(yīng)的。第三,我國(guó)鋼鐵行業(yè)全要素生產(chǎn)率的均值為1.076,年均增長(zhǎng)7.6%,技術(shù)進(jìn)步指數(shù)年均增長(zhǎng)9.4%。除個(gè)別省份外,所有省市的生產(chǎn)率是增長(zhǎng)的,主要得益于技術(shù)進(jìn)步有效。第四,選取的影響因素指標(biāo)有一個(gè)未通過(guò)檢驗(yàn),其余指標(biāo)在不同程度上都通過(guò)了顯著性檢驗(yàn),說(shuō)明這些因素與全要素生產(chǎn)率存在顯著性關(guān)系。但是有個(gè)別指標(biāo)呈負(fù)相關(guān),意味著在推動(dòng)全要素生產(chǎn)率上并沒(méi)有起到促進(jìn)作用。最后,根據(jù)研究的結(jié)論,提出了相應(yīng)的對(duì)策建議:(1)以創(chuàng)新為驅(qū)動(dòng)突破鋼鐵行業(yè)發(fā)展瓶頸(2)以可控的方式實(shí)現(xiàn)行業(yè)的去產(chǎn)能(3)以兼并重組來(lái)提高產(chǎn)業(yè)集中度。
[Abstract]:As an important industry of national economy, iron and steel industry supports and guarantees the development of related industries in the process of long-term economic construction, and strongly promotes the industrialization and modernization process of our country. At present, our country is at the beginning stage of building a powerful manufacturing country, which is also the key period of supply-side reform of steel industry. Therefore, to measure the change of total factor productivity of China's iron and steel industry, to analyze and find out the relevant factors that affect its efficiency and productivity, and to put forward relevant countermeasures and suggestions, in order to extricate China's iron and steel industry from the current predicament of development. Appear very urgent, is worthy of attention and in-depth study of an important subject. This paper firstly combs the literatures on efficiency and productivity of iron and steel industry, and then analyzes the present situation and existing problems of steel industry. Then, based on provincial panel data, the corresponding input-output index system is constructed, and the efficiency and productivity of steel industry in 28 provinces and cities are measured by DEA model. Finally, the influence of these factors on iron and steel industry is analyzed by regression method. The research found that: first, the technical efficiency of the whole steel industry is relatively low. From different regions, the eastern region has obvious advantages in terms of technical efficiency. Of the top 15 provinces and cities, 10 are in the east, four in the central region and only one in the west. Secondly, the technical efficiency of iron and steel industry is mainly caused by pure technical efficiency, which is found by BCC model decomposition technology efficiency. Although the scale efficiency does not reach the production front, most provinces and cities show the increasing trend of scale returns, which indicates that there is a certain scale effect in the steel industry. Third, the average value of total factor productivity (TFP) of China's iron and steel industry is 1.076, with an average annual growth of 7.6%, and an average annual growth of 9.4% of the technological progress index. Productivity has increased in all provinces except individual provinces, largely thanks to effective technological progress. Fourth one of the selected influencing factors has failed the test and the others have passed the significance test to varying degrees indicating that these factors have a significant relationship with total factor productivity. However, a few indicators are negatively correlated, meaning that TFP has not been promoted. Finally, according to the conclusion of the research, the paper puts forward the corresponding countermeasures and suggestions: 1) to take innovation as the driving force to break through the bottleneck of iron and steel industry development (2) to realize the deproductivity of the steel industry in a controllable way) to increase the degree of industrial concentration by annexation and reorganization.
【學(xué)位授予單位】：重慶工商大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：F224;F426.31

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