我国制造业全要素生产率测度及影响因素分析

发布时间：2018-01-03 15:32

本文关键词：我国制造业全要素生产率测度及影响因素分析　出处：《西南财经大学》2014年硕士论文　论文类型：学位论文

【摘要】：制造业是国家竞争力增强的关键和基础,对国民经济的发展起着重要的推动作用。即使进入当今信息化时代,制造业发展的规模和程度仍然是衡量一个国家综合实力的重要标志之一。从世界范围来看,目前的经济强国,仍然是制造业最发达的国家。美国强大的经济就在于其以先进科技为基础建立了强大的制造业。德国和日本在二战后能够迅速崛起为经济强国,也和其建立具有很强竞争力的技术密集型制造业体系,并大量出口高附加值制造业产品,并最终在国际分工中赢得了有利的贸易条件密不可分。因此,坚定发展制造业使我们国家实现现代化和工业化,是跻身世界强国的必由之路。改革开放以来,中国制造业利用相对低廉的土地、人力、能源和环境保护成本等优势,实现了高速增长。但随着劳动力成本和环境保护成本上升、人民币升值及出口退税政策的调整,中国制造业赖以生存的条件正逐渐散失,从而竞争优势也逐渐降低。我们可以看到转型和升级是当前中国制造业无法回避的问题,只有靠转型升级才能从根本上解决各种矛盾、困难和问题。在我国制造业近年来发展的背后,作为转变经济增长方式和提高增长质量的重要组成部分,全要素生产率的变化情况究竟如何?作为全要素生产率的组成部分,技术效率和技术进步的变动情况如何?全要素生产率在我国制造业各行业间的变动情况又有哪些异同?影响我国制造业全要素生产率变动的影响因素有哪些?需要采取哪些举措来进一步提高我国制造业全要素生产率的水平?以上都是本文试图回答的问题,也是本文的写作初衷。本文首先利用基于数据包络分析法的Malmquist指数方法测算我国制造业各细分行业、按用途属性划分的制造业、按技术标准划分的制造业在2001-2011年间的全要素生产率、技术效率和技术进进步的变动情况,揭示其在11年间的变动规律。结果发现,在技术进步方面,制造业各行业的技术进步趋势基本一致,在2000-2011年间都有较大的提高；在技术效率方面,则有少数行业存在下降趋势,即使某些行业存在技术效率增长,其提高的幅度也是比较低的。因此,我国制造业的全要素生产率的提高主要得益于技术进步的拉动,而技术效率的贡献偏低。其次,采用多元回归模型分析影响我国全要素生产率变动的因素,结果发现人力资源素质的提高、科技投入的加强、对外开放的深化、市场开放的深入都对中国制造业全要素生产率的提高起到了显著的作用。针对以上的分析,论文最后一部分提出了提高制造业全要素生产率的政策建议,从提高人力资源素质、促进技术进步、加快所有制结构调整和深化对外开放等四个层面依次展开。提高人力资源素质层面主要有：重视发展教育；加强科技人才队伍建设；形成以市场为导向的人力资源开发机制。着力发展教育；树立正确的知识生产效率观；形成以市场为导向的人力资源开发机制。促进技术进步层面主要有：充分发挥政府在构建技术创新体系中的主导作用；确定企业在技术创新体系中的主体地位；加强产学研相结合；注重改造传统产业。加快所有制结构调整层面有：加快促进国有经济的重组改革；大力发展非公有制经济。深化对外开放层面有：扩大对外贸易；灵活执行“引进来、走出去”的外贸发展战略；加强信息预警机制,建立和完善信息交流平台。与以往对我国制造业全要素生产率的研究相比,本论文的研究有以下几点创新之处： (1)本文采用基于DEA模型的Malmquist指数分析方法不仅对制造业各细分行业的全要素生产率进行研究,还利用行业加权方法,对按用途属性划分的制造业和按技术标准划分的制造业的全要素生产率指数进行了分项指标(技术进步指数和技术效率指数)的实证研究,并据此进行全面系统的比较分析,具有更强的现实意义。 (2)本文在借鉴以往文献基础上,比较系统的对人力资源素质、技术投入、市场开放程度、对外开放程度、政府干预程度等影响全要素生产率水平的内、外因素进行了实证分析。 (3)在研究时间上,本文选择2001-2011年的数据作为样本来研究我国制造业全要素生产率。已有文献的研究数据选取多截止到2009年前,而实际上我国于2008年经历金融危机,2010年开始,我国才从金融危机的影响中走向复苏。因此本文将用于分析我国制造业的全要素生产率增长状况的时间序列延伸至2011年,对于研究我国制造业在新阶段的发展动向,有着重要意义。
[Abstract]:Manufacturing industry is the key and basis of national competitiveness enhancement , and plays an important role in the development of national economy . Since the reform and opening - up , China ' s manufacturing industry has achieved high - speed growth with relatively low cost of land , manpower , energy and environmental protection . However , with the increase of labor cost and environmental protection costs , the RMB appreciation and the adjustment of export tax rebate policy , the conditions of China ' s manufacturing depend on the gradual loss of competitive advantage . In China ' s manufacturing industry in recent years , as an important part of changing the way of economic growth and improving the quality of growth , what is the change of all - factor productivity ? What are the changes of all - factor productivity as part of all - factor productivity ? What are the factors that affect the whole factor productivity change of our manufacturing industry ? What measures are needed to further improve the level of the whole factor productivity in our manufacturing industry ? This is the question that this article tries to answer , and also the original intention of this article . Based on the Malmquist index method based on the data envelope analysis method , this paper calculates the changing rule of manufacturing industry in China from 2001 to 2011 based on Malmquist index method . Secondly , using the multiple regression model to analyze the factors that affect the whole factor productivity change of our country , the result shows that the improvement of human resource quality , the strengthening of the investment of science and technology , the deepening of the opening of the outside world , and the deepening of the opening of the market play a significant role in the improvement of the whole factor productivity in China ' s manufacturing industry . Aiming at the above analysis , the last part of this paper puts forward the policy suggestion to improve the whole factor productivity of manufacturing industry . Compared with previous researches on the whole factor productivity of manufacturing industry in China , the research of this paper has the following innovations : ( 1 ) Using the Malmquist index analysis method based on DEA model , this paper studies not only the whole factor productivity of the manufacturing industry , but also the industry weighting method , and the empirical research on the sub - index ( technical progress index and technical efficiency index ) of the manufacturing industry and the manufacturing manufactured according to the technical standard , which are divided according to the use attribute , and the comparative analysis of the comprehensive system are carried out accordingly , which has more practical significance . ( 2 ) Based on the previous literatures , this paper makes an empirical analysis on the internal and external factors that affect the whole factor productivity level , such as the quality of human resources , the input of technology , the degree of opening of the market , the degree of opening to the outside world , the degree of government intervention and so on . ( 3 ) At the research time , this paper selects the data from 2001 to 2011 as the sample to study the whole factor productivity of our manufacturing industry . The research data of the literatures have been selected for many years to 2009 . In fact , China has experienced the financial crisis in 2008 . Since 2010 , our country has moved towards the recovery from the impact of the financial crisis . Therefore , this paper extends the time series for analyzing the growth of the whole factor productivity in our manufacturing industry to 2011 , which is of great significance to the study of the development trend of the manufacturing industry in our country in the new stage .

【学位授予单位】：西南财经大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：F224;F424

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