【作者】 张莹；

【导师】 王维国；

【作者基本信息】 东北财经大学 ， 管理科学与工程， 2015， 博士

【摘要】 辽宁省信息产业在近十年来取得了较大的进步,但与广东、上海等东部发达地区相比,无论在产业规模、产业结构还是发展水平等许多方面仍存在一定的差距,处于相对落后状态。随着经济全球化步伐的加快,在一带一路的经济圈产业转移阶段,把握好当前信息产业发展模式变化的机遇,使信息技术真正成为创造更多经济价值和社会价值的关键引擎,是辽宁省增强区域优势的有效途径。在产业融合背景下,信息产业已经进入了突破式发展的重要机遇期。信息产业内部融合发展持续深化的同时,信息产业与其他产业间的相互融合也变得更加紧密,对信息技术和信息产业的需求始终保持旺盛的增长势头。研究辽宁省如何在产业融合背景进行信息化建设,带动产业结构优化,更好地适应经济新常态显得至关重要。本文将产业融合的相关理论和方法进行整合,以经济增长理论、生产理论、信息产业经济学相关理论为基础,采用计量经济学、统计学等方法进行实证研究。分别从宏观和中观层面分析了辽宁省信息产业现状以及信息产业融合与经济增长的关系,测算和评价了辽宁省信息产业的全要素生产率变化情况、信息产业与制造业及物流业的融合度、工业化与信息化的融合质量和融合效率。并将信息产业比较发达的东部地区：北京、天津、上海、江苏、浙江、福建、山东和广东与辽宁省信息产业的状况进行比较分析。全文在可得的实际数据基础上建立相应经济模型,尝试综合运用计量分析方法、网络分析等分析方法,系统地、全面地对辽宁省信息产业进行了科学评价,给出了基于融合视角的辽宁省信息产业发展路径。本文主要研究内容和结论如下：1.通过对投入产出模型进行结构分解,计算辽宁省通信设备、计算机及其它电子设备制造业、信息传输、计算机服务和软件业与各行业间的乘数效应、反馈效应和溢出效应,分析得出辽宁省信息产业与其他产业间的关联情况。计算结果显示这两个行业的需求带动其它行业经济增长的能力在提升,外溢能力增强,但受其它行业的影响较小。根据辽宁省八城市在2008年签署的《信息产业区域合作协议》,将大连、葫芦岛、丹东、营口、盘锦、锦州、辽阳、鞍山八城市做为一个产业集群网络来统筹规划。通过经济联系强度模型计算各城市间的网络经济联系强度,研究结果表明基于区域间产业集群网络的协作,将有利于各区域信息产业水平的提高,产业融合的推进。2.以电子及通信设备制造业和电子计算机及办公设备制造业为代表,分别使用Malmquist指数方法和随机前沿参数(SFA)模型,对辽宁省和东部发达地区信息产业的全要素生产率情况进行了测算,并运用增长核算与计量经济模型相结合的方法计算辽宁省信息技术对辽宁省全要素生产率的贡献。主要结论如下：辽宁省电子及通信设备制造业和电子计算机及办公设备制造业技术进步指数小于1,说明技术进步对电子及通信设备制造业和电子计算机及办公设备制造业发展的贡献不明显,技术效率、技术进步和规模效率并没有实现一起增长；辽宁省全要素增长率与IT固定资产增长率之间的因果关系不显著,说明信息技术投资占总投资比例较低,很难估算其对TFP的影响。要改变以上状况,辽宁省在加快技术进步,通过提高自主创新能力来增强信息产业竞争能力的同时,还要扩大信息产业的投入占总投入的比重,加强信息技术在非信息技术产业中的应用,全面推进产业融合。3.用赫芬达尔指数分别测算了辽宁省电子信息制造业和软件业内部行业间的市场融合度,基于投入产出法计算了辽宁省信息产业与制造业各行业、物流业的融合度。主要结论如下：辽宁省信息产业中电子信息制造业和软件业行业间的内部融合水平高于全国平均水平；辽宁省信息产业与制造业的融合度低于全国平均水平,但辽宁省信息产业与化学工业、通用专用设备制造业、仪器仪表及文化办公用机械制造业这三个行业的融合度要高于全国的平均水平,尤其是通用、专用设备制造业作为资本密集型行业,与信息产业的融合度高出全国平均水平较多,这与辽宁省作为传统老工业基地,一直重视发展通用设备制造业信息化建设是分不开的；尽管辽宁省物流业的产值在国内是比较高的,但是与信息产业的融合度却低于东部发达地区大部份省份和全国平均水平,反映出辽宁省物流业的信息化水平还须进一步提高。4.建立了基于工业化和信息化互动关系分析的向量自回归模型-VAR模型,并利用脉冲响应和方差分解对该模型进行了解释。主要结论如下：辽宁省工业化与信息化之间具有格兰杰因果经济关系,它们之间是相互影响的；VAR方差分解结果显示,工业化对信息化水平的影响会逐渐起到主导作用,而信息化水平对工业化水平的影响作用却是有限的。5.采用非参数面板固定效应模型,对近十一年来东部发达地区与辽宁省的信息产业与工业的融合质量进行了测算和评价,指出辽宁省信息产业融合发展的可行路径。实证结果得出产业融合对东部地区转变经济增长方式、三次产业结构调整有不同程度的影响,其中辽宁省以工业化促进信息化的融合路径比较明显。因此辽宁省信息化水平对工业化水平的影响还需要进一步地引导,要加强信息化带动工业化融合路径,充分发挥信息化对工业化水平的影响和作用。6.从协调发展的角度对辽宁省信息化和工业化的融合效率进行了测算与评价。基于协调度模型计算信息化与工业化融合度的基础上,利用仁慈型DEA交叉效率测算了工业化和信息化的交叉效率,并采用熵权法计算了二者的融合效率。实证结果表明,信息化和工业化的有序度和融合效率从2003年以来一直在逐渐增加,但从2010以后出现了下降趋势,因此工业化和信息化融合在辽宁省仍面临着严峻的挑战,传统大规模的经济生产方式已经无法满足经济发展的要求,必须要立足经济新常态,用信息化手段、互联网创新思维对经济发展方式做出根本性转变。辽宁省在加速信息产业内部融合的同时,还要加强信息产业与其他产业之间的融合,使信息产业成为支撑其他产业发展的通用技术产业。7.对信息产业融合度与经济增长的关系进行了计量分析。运用面板模型测度了辽宁省和广东、上海等东部发达地区信息化与经济增长之间的关系,实证结果表明,辽宁省与东部发达地区均存在信息化与经济增长的双向因果关系。在此基础上,以科技资本存量作为技术融合水平的代表指标,建立可变参数模型基础上,通过卡尔曼滤波的方法,考察在经济发展过程中,在经济结构变化及体制转轨等因素的影响下,技术融合水平对经济发展水平的动态影响。主要结论为：技术融合对经济增长的促进作用是比较明显的,且在经济发展的过程中也具有重要地位。但是,我国在技术融合方面还存在着很多的问题亟待解决,特别是随着市场经济体制不断深化的前提下,政府应加强对技术整合之后的引导和激励,在技术融合的基础上,推动市场融合和产品融合,即推动技术创新成果的商业化、产业化进程,从而使产业融合成为我国经济持续增长的主动力。使用Malmquist指数方法计算了辽宁省与东部发达地区制造业的Malmquist生产率指数,并对产业融合程度与制造业Malmquist生产率指数之间的关系进行了实证分析,结果显示辽宁省制造业加速发展的主要动力来自于技术效率而非技术进步的提升,产业融合与制造业TFP增长率两者之间存在着显著的正相关。论文的研究结果表明,尽管辽宁省信息产业对经济发展有一定的促进作用,但与东部发达地区相比,存在对全要素生产率贡献不明显,技术进步率较低,信息产业投入不足,缺乏创新力等问题。辽宁省信息产业与各产业之间还存在融合度较低、产业融合大部分还停留在初级阶段、信息化带动工业化的融合路径不明显、信息化与工业化融合效率呈现下降趋势等问题。针对辽宁省信息产业实际情况论文中提出以下建议：(1)充分发挥大连辐射作用,振兴东北老工业基地的发展,促进信息业与制造业的深度融合,加速新兴产业布局,实现以工业化促进信息化和以信息化带动工业化二条路径协调发展。加快新技术革命,广泛应用如大数据、3D打印等几大技术领域,将网络化、定制化、智能化作为制造业的主要转型方向。(2)构建产业创新网络,完善产业链,巩固信息产业集群,支持创新集群发展。(3)用互联网创新思维,进行信息化建设,更好地适应经济新常态。(4)改变信息基础设施建设模式和使用模式。购买和使用云服务进行部门信息化建设。(5)大力发展现代服务业,促进制造业、软件业、运营业与内容服务业的“四业融合”,丰富信息消费的内容。(6)完善软件贸易和信息服务外包的政策环境,并培育信息产业相关的服务中介、行业协会、产业联盟等创新连接组织。(7)加快实施人才工程,形成优势人才储备。更多还原

【Abstract】 The information industry in Liaoning province has made obvious progress in the past ten years, but its industry scale, industry structure and development level have a big gap in many aspects compared with the developed provinces and cities in our country. With the speeding-up of the economic globalization and industrial transfer phase through One Belt and One Road economic circle, how to grasp the opportunity of the current mode change of the information industry development and make information technology create more economic value and social value, is an effective way to enhance the regional advantages of Liaoning province.Under the background of industrial convergence, information industry is beginning to embrace the important opportunity of breakthrough development. Internal convergence development of information industry continues to deepen. The mutual convergence between information industry and other industries has also become much more closely, and the demand for information technology and information industry keeps maintaining a strong growth momentum. It is crucial to conduct the research on how to carry out the informatization construction in order to better adapt to the economic new normal,In this paper, we integrate various theories and methods of industry convergence. Based on economic growth theory, production theory and the information industry economics, we carry out an empirical research with the methods of econometrics and statistics. From the macro and micro level, we analyze the current situation of information industry and the relationship between the information industry convergence and economic growth, measure and evaluate the total factor productivity of the information industry, the convergence degree between information industry and manufacturing industry, the logistics industry, the convergence quality and efficiency between informatization and industrialization in Liaoning province. The more developed eastern regions of Beijing, Tianjin, Shanghai, Jiangsu, Zhejiang, Fujian, Shandong and Guangdong are researched as one unit in comparison with Liaoning. Based on the actual available data, we establish the appropriate economic model, try to make comprehensive use of quantitative analysis method, network analysis and empirical analysis to evaluate scientifically the current situation of information industry in Liaoning province. In doing so, we are able to give the practical route of the information industry development in Liaoning province under the convergence background. The main contents and conclusions of this paper are as follows:1. Calculate the multiplier effect, the feedback effect and the spillover effect between the electronic and telecommunication equipment manufacturing industry and other industries, information transmission, computer services, software industry and other industries and analyze the situation of information industry. Studies have shown that the spillover effects, feedback effects of the two industries are increasing, while the multiplier effects are decreasing. According a cooperation agreement between Dalian, Huludao, Dandong, Yingkou, Panjin, Jinzhou, Liaoyang, Anshan signed in 2008, the eight cities are designed to develop as a whole part. The intensity of economic link shows that the collaboration based on the regional industry cluster network will be helpful to the development of the industry convergence and the improvement of the regional information industry. Through the calculation of the economy strength of the eight cities, it will be conducive to the improvement of the regional information industry, the propulsion of industry convergence based on the regional industry cluster network collaboration.2. Respectively using the Malmquist index method and the stochastic frontier parameter (SFA) model, TFP of information industry in Liaoning province has been calculated based on the data of the electronic and communication equipment manufacturing industry and electronic computer and office equipment manufacturing industry. We also calculate the information technology’s contribution to the TFP of Liaoning province through the combing of the growth accounting and the econometric model. Main conclusions are as follows:the TFP index and TECH index of industry is less than 1; the contribution of technological progress to the development of electronic and communications equipment manufacturing and electronic computer and office equipment manufacturing industry is not obvious; the technical efficiency, technological progress and scale efficiency does not achieve growth at the same pace; TFP growth in Liaoning province and IT has no significant causal relation with the growth rate of fixed assets. The main reason is that information technology investment to total investment ratio is low and it is difficult to estimate the effects on TFP. To change the above situation, it is the best to accelerate technological progress, enhance industrial competitiveness through improving self-directed innovation capability, increase the proportion of the investment in the information industry, and strengthen the application of information technology in the non-information technology industry, thus promoting industrial convergence.3. This article evaluates Liaoning’s internal market convergence degree of the information manufacturing industry and software industry using the Hector fanta’s index and the convergence degree between the information industry, the manufacturing industry and the logistics industry using the input-output table. On the whole, compared with the national average, the internal convergence degree of the information industry in Liaoning is higher and the convergence degree between the information industry, the manufacturing industry and the logistics industry manufacturing industry is lower. But the convergence degree of the information industry and chemical industry, general special equipment manufacturing industry, instrumentation and cultural office machinery manufacturing industry of alignment is higher than the national average level, especially the convergence degree between information industry and the general and special equipment manufacturing industry, as a capital-intensive industry, is much higher than the national average. The convergence degree of information industry and the logistics industry in Liaoning is lower than most of the provinces, although the output value of the logistics industry in the province in China is relatively high. It means the informationization level of the logistics industry in Liaoning must be further improved.4. In the paper, vector autoregressive models have been established to analyze the interactive relationship of industrialization and informatization. The impulse response and variance decomposition are used to analyze the model. The results show that the informatization and industrialization in Liaoning province are Granger reasons, and the informationization level and industrialization level have mutual influence on each other. The impact of industrialization level on informationization will gradually play a leading role; and the impact of informationization level on industrialization is limited.5. The paper evaluates the convergence quality of information industry and industrial industries in the eastern regions in the past 11 years using the nonparametric fixed effects models, which points feasible paths to the convergence development of industrialization and informatization in Liaoning province.. The results show that convergence has a different degree of influence to the transformation of the economic growth and the industrial structure adjustment of the eastern regions. The path of industrialization improving informationization is more noticeable, and we should strengthen the path of industrialization improving industrialization.6. The convergence efficiency of informatization and industrialization in Liaoning province is analyzed from the angle of the coordinated development. First, calculate convergence degree of the informatization and industrialization based on coordination degree model; then calculate the cross efficiency of industrialization and informatization using DEA kind efficiency; lastly calculate the convergence efficiency of the two. The research results show that the convergence degree and convergence efficiency of informatization and industrialization since 2003 has presented a gradual increase trend, but a downward trend has appeared since 2010; industrialization and information convergence in Liaoning province is still faced with serious challenges, and expanding the size of the electronic information industry and increasing its proportion in the national economy is still the main development direction in the future.7. We establish the econometric model to analyze the relationship between the information industry convergence and economic growth. Firstly, analyze the relationship between informatization and the economic growth by establishing two sector models. Apply panel unit root and panel GRANGER causality to test the relationship between information and economic growth in the eastern regions. The results show that the development of informatization and economic growth are the GRANGER cause and effect. Based on the variable parameter models, through Kalman filter method as well as using the stock of science and technology, the paper inspects the technology integration level dynamic impact on the level of economic development under the effects of the economic structure change and institutional transition and other factors in the growth process of economy. Based on the dynamic analysis, technology convergence has an obvious promoting effect on the economic development. However, there are still a lot of problems to be solved in regards to the technology convergence. Especially under the premise of deepening the market economy system, the government should strengthen the guide and incentive of technology convergence. On the basis of technology convergence, the government should promote market convergence and product convergence, namely, to promote the process of the commercialization, industrialization of the technology innovation achievements.By doing so, industry convergence can become the main power of sustained economic growth in china. Finally, the total factor productivity of the eastern provinces and Liaoning has been calculated by the use of the Malmquist index method. The results show that the main power of accelerating development of manufacturing industry of Liaoning province comes from the technical progress and technical efficiency improvement. On the basis of the introduction of industrialization and related theories of information industry integration, the empirical analysis between the industrial convergence degree and the Malmquis Index has been conducted, and the results of the study show that there is a significant positive correlation between the informatization and industrialization.Research shows that the contribution of most of the information industry to TFP is not obvious in Liaoning province; most of the information industry have vulnerabilities, such as redundant construction, lack of creativity, etc. And the convergence degree is low between the industries. Most of the industry convergence still stays in the primary stage. The path of informationization driving industrialization is not obvious. The convergence efficiency shows a downward trend. Compared with the other developed eastern provinces, there is still a gap in terms of independent innovation ability. The development of core technology and key equipment had no fundamental breakthrough. The transformation and upgrading of information industry still has a long way to go. Based the actual situation of the information industry clusters in Liaoning province, the paper puts forward the following suggestions:(1) Give full play to the Dalian radiation effect, promote the development of the northeast old industrial base, and promote the in-depth convergence between the information technology and manufacturing industry in order to realize coordinated development of the two paths of industrialization promoting informatization and informatization driving industrialization. (2) Construct industrial innovation network, improve the industrial chains, strengthen information industrial clusters, and support cluster innovation development. (3) Use internet creative thinking to construct informatization and better adapt to the economic new normal. (4) Change the mode of information infrastructure construction and use. Through the purchase and use of cloud services, construct the department informatization. (5) Develop the modern service industry, and at the same time promote "four industries convergence" between the manufacturing industry, software industry, operation industry and content service industry. (6) Perfect the policy environment of the information service outsourcing and software trade and cultivate information industry related service agencies, such as industry associations and industry alliances. (7) Speed up the implementation of talent project to create a reserve of advantageous talents.更多还原