摘要
历经25年的发展,高新技术产业已经在我国国民经济中占有重要地位。高新技术产业中的知识研发和技术进步是我国经济增长的重要推动力,对于引导我国经济由“投资驱动型”向“技术驱动型”转变具有重要作用。高新技术产业具有高附加值和高收益特征,代表了未来的产业发展方向,对传统产业的提升改造也具有积极促进作用。发展高新技术产业,也是我国在“十二五”期间推动经济科学发展和产业转型升级的重要举措之一。
本文在产业经济学的基础上,从企业、产业、省域、区域、国际等多个视角对高新技术产业的发展及其影响因素进行了研究。本文的主要工作和研究结论如下：
一、采用分位数回归方法研究高新技术企业中研发和人力资本等因素的差异化影响,给出高新技术产业绩效变动的微观经验证据
2009-2010年,随着消费者对新产品需求的不断增长,绩效较好的高新技术企业可以将更多的资金转移到研发活动中,研发的效果也更为显著。人力资本对高新技术企业绩效的影响具有不确定性。人力资本对高新技术企业各分位绩效的影响几乎都不显著,但随着高新技术企业绩效的提升,人力资本变量的影响总体上也呈现逐渐增大的趋势。
资产负债率一直都是影响高新技术企业绩效的重要因素。并且,资产负债率对高新技术企业绩效低分位数的影响小于对绩效高分位数的影响。资产负债率下降有利于我国高新技术企业绩效的提升。2007-2009年,规模因素对高新技术企业各分位绩效并没有显著影响,而2010年,规模对高新技术企业低分位绩效的影响显著为正。因此,“大而全”的发展模式并不适合我国高新技术企业。
二、建立我国高新技术产业中外资与内资企业间双向溢出效应的动态面板数据模型,更为准确地测度外资溢出效应对产出影响的方向和程度
就外资企业向内资企业的溢出效应而言,1995-2001年,我国高新技术产业中的内资企业没有跨越外资发挥作用的“门槛”,导致外资企业对内资企业的溢出效应并不显著。2001-2008年间,外资企业的示范效应、竞争效应以及行业间的带动效应使得外资企业对内资企业产生了正的溢出效应。2001年之前,相对于外资企业而言,内资企业基础条件比较差,没有能力对外资企业产生影响,内资企业向外资企业的溢出效应并不显著。随着高新技术产业中内资企业的不断成长,2001-2008年,内资企业对外资企业产生了负的溢出效应。逐渐壮大的内资企业以低廉的价格、不断壮大的科研队伍等相对优势在国内市场上开展了与外资企业的竞争。
就高新技术产业中内资与外资企业间相互作用的调整机制而言,内资企业在2001年前对市场变化反应并不敏感,2001年之后,调整系数显著增大表明内资企业已转变为能够积极顺应市场需求,把握市场机遇,在市场竞争中不断发展壮大。同时,外资企业对市场变化的反应及调整能力在各个阶段都较强。
三、建立各省份高新技术产业发展水平梯度变迁的广义排序选择模型,找出不同省份高新技术产业发展差异的主要原因
相比而言,中部和西部部分省份高新技术产业发展水平梯度变化较大,东部地区高新技术产业梯度的变化并不明显。区域经济发展战略对于高新技术产业发展的影响和各地区对高新技术产业发展的推动是中西部高新技术产业发展水平变动幅度较大的主要原因。东部高新技术产业处于较为成熟的发展阶段,因而发展水平比较稳定。
对高新技术产业不同发展梯度水平下影响因素的分析结果显示,在高新技术产业发展水平较低的省份,经济发展水平对高新技术产业发展产生了一定的抑制作用,而高新技术产业发展到一定程度后,才会受到当地经济发展水平的积极影响。与经济发展水平相比,工业发展水平对高新技术产业发展的影响恰好相反。随着高新技术产业梯度水平的不断提升,工业发展对高新技术产业的影响由带动变为挤出,因此,工业发展与高新技术产业增长之间存在倒“U”型关系。研发支出的有效性在不同高新技术产业发展水平下也有较大差异。一般而言,随着高新技术产业发展水平的提升,研发支出的有效性也逐渐增加。人力资本支出的风险性和人力资本积累的时滞导致人力资本对高新技术产业发展水平的影响具有不确定性。
四、构建了高新技术产业的空间面板计量经济模型,研究高新技术产业各区域中研发的知识溢出效应和产出的经济溢出效应,以及两种效应对产出增长的贡献
由于研发经费支出对创新成果产出的重要影响和政府对高新技术产业成果转化的推动,各地区高新技术产业中研发投入的高回报特征得到了充分体现,研发积累有效推动了我国各区域高新技术产业的产出增长。各地区高新技术产业中心省份向外围的研发溢出效应对产出增长具有差异化影响。中西部地区高新技术产业研发的溢出效应对产出的促进作用要远小于自身研发努力对产出的贡献,长三角地区各省份研发活动与省份间知识溢出效应贡献近似相等,而珠三角地区研发要素由外围向中心的集聚效应较强导致知识溢出的贡献为负。
总体而言,高新技术产业各地区内产出空间上的相互作用具有正向促进效应。环渤海和东北地区、西部地区高新技术产业中心对外围相关配套产业的拉动有利于外围省份的产出增长,珠三角地区的中心广东已经发展到足够大的规模,离心力使得高新技术产业生产活动和生产要素逐渐流向外围省份,带动了该地区外围省份的产出增长。高新技术产业中的实物资本和劳动对产出增长的贡献显著,资本驱动型和劳动密集型特征明显。实物资本与研发资本相结合共同推动高新技术产业的发展,我国高新技术产品的技术含量低,对技能型普通劳动力的需求较高。
五、建立高新技术产业的可计算一般均衡模型,测度高新技术产业发展财税政策的效果,模拟政府促进高新技术产业发展进而推动产业结构调整的传导机制
在高新技术产业产出增长方面,财政激励政策比税收优惠政策能够更加有效地促进高新技术产业的增加值增长。在高新技术产业的内部结构方面,财政激励政策通过增大研发支出促进技术进步,税收优惠政策通过增加值相对价格下降产生的替代效应和鼓励要素流入产生的技术进步,都能够提高高新技术产业的增加值率,改进高新技术产业的内部结构,但税收优惠政策的作用更为显著。
财政激励下高新技术产业对其后向关联的原材料工业和生产者服务业等产生了显著的回顾效应,对其前向关联的消费者服务业和装备制造业等产生了一定的前瞻效应,对农业和消费品工业的产出增加也具有积极的推动作用。税收优惠作用下,虽然高新技术的应用能够发挥农业和消费品工业劳动密集的比较优势,但高新技术产业对工业资本要素生产率的提升小于相对要素价格上升导致的成本增加,因此,高新技术产业对原材料工业、装备制造业和建筑业的增加值增长产生了负的影响。
六、基于中、日、英、美四个国家投入产出数据,采用结构分解模型测算了最终需求和增加值各变量对高技术产业产出变动的贡献,采用非完全假设抽取法测度了四国高技术产业与其他产业的关联效应
中国技术进步对高技术产业产出的贡献程度远小于其他发达国家,但其推动产出增长的效应逐步显现。消费对各国高技术产业产出贡献的差异较大,对于英国和美国而言,消费是两国高技术产业持续发展的主要拉动力量。中、日、英、美四国高技术产业资本形成与产出变动的方向呈现了高度的一致性,大量的资本形成和净出口的比较优势使得中国高技术产业的“投资驱动型”特征明显。并且,在各国中,净出口对中国高技术产业产出增长的贡献呈现出“一枝独秀”局面。1995-2005年各国高技术产业的盈利能力整体上逐渐增强,但各国高技术产业劳动者报酬差距悬殊,英国和美国高技术产业一直维持着高额的劳动者报酬支出,中国高技术产业劳动者报酬远低于各发达国家。
各国高技术产业与自身的后向关联最为密切,并且,与发达国家相比,中国高技术产业与装备制造业、原材料工业和服务业等行业具有更为紧密的后向关联,且关联效应逐步增强。前向关联方面,中国高技术产业对装备制造业、原材料工业和消费品工业行业效率具有显著提升作用,并且与生产者服务业的前向关联大于消费者服务业,这主要是由中国处于工业化阶段中期的事实所决定的。
我国高新技术产业快速发展影响因素的研究以及高新技术产业中财税政策效果的研究,对于国家高新技术产业发展政策的制定、地方政府对高新技术产业化的推动都具有重要作用。并且,正确认识我国高新技术产业在国际上的地位以及与发达国家高新技术产业的差异,不仅有利于准确判断我国高新技术产业的发展态势,而且有利于借鉴国外高新技术产业发展中的经验教训。因此,对我国高新技术产业的发展及其影响因素进行研究具有重要的理论和现实意义。
High-tech industries have played an important role in our national economy after25years of development. Knowledge-orientated R&D and technological progress in high-tech industries are important driving forces of China's economic growth, and they have a significant effect in guiding China's economic transformation from "investment-driven" to "technology-driven" mode. The high-tech industries which have the characteristics of high added value and high-yield, represent the direction of future industrial development, and also have a positive role to boost the promotion of traditional industries. Developing high-tech industries is one of the important methods to promote economic development scientifically and industrial transformation in the "12th Five-Year" period of China.
Based on the industrial economics, this dissertation made empirical researches on high-tech industries' development and its influencing factors from multiple perspectives of enterprise, industry, provincial, regional and international. The main work and conclusions are as follows:
Firstly, by using the quantile regression method to study the various impacts of R&D and human capital factors on the performances of high-tech enterprises, the dissertation produced micro-empirical evidence of the high-tech industrial performance changes.
During the period from2009to2010, with the growing consumer demand for new products, high-tech enterprises with good performance invested more funds in R&D activities, which resulted in more significant R&D effects. The impacts of human capital on the performances of high-tech enterprises are uncertain. The quantile regression results show that the impacts of human capital on high-tech enterprises' performances of all quantiles are not significant, but with the performance improvement of high-tech enterprises, the impacts of human capital, in general, have taken on a gradually growing trend.
The asset-liability ratio has always been an important factor which affects the performances of high-tech enterprises. And the impact of asset-liability ratio on the performance of low quantile is less than the performance of high quantile. The decline in asset-liability ratio is conducive to the performance enhancement of China's high-tech enterprises. From2007to2009, the effects of size factor on all quantile performances are not significant. But size factor exerts a negative effect on the high-tech enterprises' performance of low quantile. Therefore, the mode of "large and whole" is not suitable for high-tech enterprises in China.
Secondly, by specifying dynamic panel data model of two-way spillover effects between foreign-funded enterprises and domestic-funded enterprises in the development of high-tech industries in China, the dissertation measured the direction and extent of foreign-funded enterprises' spillover effects on output growth of high-tech industry.
As for the spillover effects of foreign-funded enterprises on domestic-funded enterprises, from1995to2001, China's domestic enterprises of high-tech industries did not cross the "threshold" after which foreign investment can play a role, and the spillover effects of foreign-funded enterprises on domestic enterprises were not significant. During the period from2001to2008, the demonstration effects and competition effects of foreign-funded enterprises and the driving effects between industries made foreign-funded enterprises generate positive spillover effects on domestic enterprises. Before2001, compared with foreign-funded enterprises, the basic conditions of domestic companies were relatively poor, and they could not afford impacts on foreign-funded enterprises. The spillover effects of domestic enterprises on foreign-funded enterprises were not significant. With the development of domestic enterprises in high-tech industries, from2001to2008, the domestic enterprises generated negative spillover effects on foreign-funded enterprises. The growing domestic enterprises, which have the comparative advantages such as low cost and the growing research team, are in competition with foreign enterprises in home market.
As for interactive adjustment mechanism between domestic enterprises and foreign-funded enterprises in high-tech industries, domestic enterprises were not sensitive to market change before2001, whereas the coefficient of adjustment have been growing larger after2001. This proves that domestic enterprises which have transformed their mode to seize the market demand and market opportunities are growing continuously in the market's competition. At the same time, foreign enterprises'reaction and adjustment ability to market changes are strong at all stages.
Thirdly, by specifying the generalized ordered choice model of development level changes of high-tech industries in all provinces of China, the dissertation studied the main reasons of development differences in high-tech industries in different provinces of China.
In comparison, the gradient change of high-tech industries' development is greater in several provinces in central and western part of China, but the change of gradient in high-tech industries in the eastern region is not obvious. Two main reasons are listed to explain this phenomenon:one is the different impact of regional economic development strategy on high-tech industries' development, and the other is the promotion by government in central and western region. High-tech industries in eastern region are in a more mature stage of development, and therefore show relatively stable level of development.
This dissertation also analyzed the influencing factors of high-tech industries at different levels of development. The results show that in provinces which are at low development level of high-tech industries, the economic development level can restrain the development of high-tech industry in a sense. When high-tech industries grow to a certain extent, they can be influenced by local economic development level. Compared to the level of economic development, the impacts of the level of industries'development on high-tech industries are exactly contrary. With the continuous lifting of the high-tech industries' gradient, the impact of industrial development on high-tech industries changes from positive to negative. Therefore, the relationship between industrial development and growth of high-tech industries takes on inverted "U"-shaped curve. There are large differences in the effectiveness of R&D expenditures at the different level of development in high-tech industries. In general, as the level of high-tech industrial development enhances, the effectiveness of R&D investment increases gradually. The risk of human capital expenditures and the delay of human capital accumulation lead to the uncertainty of the effects of human capital on the high-tech industrial development.
Fourthly, by using spatial panel data model of high-tech industries, the dissertation did researches on the knowledge spillover effects of R&D and the economic spillover effects of output as well as their contribution to output growth in high-tech industries in regions of China.
Because of R&D expenditure's important effect on innovation output and the government's promotion for the transformation of high-tech industrial achievements, the high-return characteristics of R&D investment in regional high-tech industries have been completely reflected. The accumulation of R&D promotes regional high-tech industrial output growth effectively. R&D spillover effects on peripheral output growth coming from central provinces of high-tech industries are various. The promotion role of high-tech industrial R&D spillover effects on output in the central and western regions of China is much less than their own R&D efforts' contribution. R&D activities'contributions in the provinces of the Yangtze River Delta region and knowledge spillover effects in these provinces are approximately equal. The R&D factors'aggregation from the periphery to the center in the Pearl River Delta region lead to negative contribution of knowledge spillover.
In general, the spatial interactions of the high-tech output of provinces in a region have positive promotion effects mutually. The driving effects of high-tech industrial centers on their related industries in periphery provinces in the Bohai region, northeast region and the western region of China conduce to peripheral output growth. As the center of the Pearl River Delta region, Guangdong province has developed to a sufficiently large scale in high-tech industries. The centrifugal force makes the high-tech industrial production activities and factors of production gradually flow to the peripheral provinces and thus promote the output growth in the Pearl River Delta region. The significant contribution of physical capital and labor to output growth in high-tech industries makes they take on the characteristics of capital-driven and labor-intensive mode. The combination of physical capital and R&D capital promotes the development of high-tech industries. Concerning the characters of low technical content in China's high-tech products, the demand of the ordinary skilled labor in high-tech industries is also great.
Fifthly, by employing a computable general equilibrium model of high-tech industries, the dissertation measured the fiscal policies'effects on the high-tech industrial development, and simulated the transmission mechanism that the government boost the development of high-tech industries and thus promote industrial structure adjustment.
In the high-tech industrial output growth, fiscal incentive policies are more effective to promote high-tech industrial added value growth than the tax preference policies. In the internal structure of the high-tech industries, fiscal incentives promote technological progress by increasing R&D spending, while the tax preference policies upgrade the value-added rate of high-tech industries and improve the internal structure of the high-tech industries by substitution effect arising from the decline in comparative price of added value and technological progress resulting from encouragement of factor flows, but the roles of the tax preference policies are more significant.
Under the financial incentives, the high-tech industries lead to significant backward effects on raw material industries and producer services, and forward effects on consumer services and equipment manufacturing, and positive influences on promoting the increase in output of agriculture and consumer goods industry. Under tax incentives, although the application of high technology can inspirit the labor-intensive comparative advantage of agriculture and consumer goods industry, the upgrading of the industrial capital factor productivity by the high-tech industries is less than the increase in costs caused by relative factor prices. Therefore, the high-tech industries have negative impacts on added value growth of the raw materials industry, equipment manufacturing and construction industry.
Sixthly, based on input-output data of the four countries including China, Japan, the United Kingdom and the United States, the dissertation used the structural decomposition analysis model and non-complete hypothetical extraction method to calculate the contribution of each variable of final demand and added value in these four countries to output change in high-tech industries, and measured correlation effects between high-tech industries and other industries in above-mentioned four countries.
The contribution of technological progress to high-tech industrial output in China is far less than other developed countries, but the promoting effect of technological progress is gradually revealed. Contributions of consumption on high-tech industrial output in these four countries are much different. As for the United Kingdom and the United States, consumption is the main driving force of sustainable development of high-tech industries in the two countries. The direction of capital formation change and output change presents a high degree of consistency in high-tech industries in China, Japan, Great Britain and the United States. The comparative advantages of tremendous capital formation and net exports make Chinese high-tech industries retain the obvious characteristic of "investment-driven style". A fact worthy to be pointed out is that the contribution of net exports to high-tech industrial output growth in China is in the situation of outshing others in these four countries. From1995to2005, the profitability of the high-tech industries in general gradually increased in all these countries, but the workers' pay in the high-tech industries was very different. The high-tech industries in the United Kingdom and the United States maintained a high level of workers' reward expenditure, while the Chinese high-tech industrial workers' remuneration was much lower than developed countries.
As for backward linkage, the high-tech industries are most closely associated with themselves in these four countries. Compared with developed countries, the Chinese high-tech industries are connected more tightly with equipment manufacturing industry, raw materials industry, services industries, and are showing closer backward linkages with these industries gradually. As for forward connection, the Chinese high-tech industries have a significant role in improving the efficiency of equipment manufacturing, raw materials and consumer goods industry, and their forward connection with producer services is greater than that with the consumer services sector. This phenomenon is largely decided by the fact that China is in the mid-stage of industrialization.
The researches on the influencing factors of China's high-tech industries development as well as the effects of fiscal policy in the high-tech industries are of great significance to the planning of the national high-tech industrial development policy and the promotion of the high-tech industrialization by local governments. Moreover, a correct understanding of the international position of Chinese high-tech industry as well as differences with the high-tech industries in developed countries is not only helpful to determine the development trend of China's high-tech industry accurately, but also to learn from lessons in the foreign high-tech industrial development. Therefore, that is of important theoretical and practical significance to study on the development and its influencing factors of the high-tech industries in China.
引文
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①本章中研发对绩效影响机理的分析参照了丹尼斯·W·卡尔顿和杰弗里.M-佩洛夫(2009)的观点。丹尼斯·W·卡尔顿,杰弗里·M·佩洛夫,2009,《现代产业组织》(第四版),北京：中国人民大学出版社,第62—65页。
①本章中人力资本对绩效影响机理的分析参照了Juma et al. (2004)和周业安(2002)的观点。Juma Norma, Payne G. Tyge,2004, "Intellectual Capital and Performance of New Venture High-tech Firms", International Journal of Innovation Management, Vol.8, No.3, pp297-318.周业安,2002,《人力资本、不确定性与高新技术企业的治理》,《中国工业经济》2002年第10期,第56-63页。
①资本结构对绩效影响的分析参照了平狄克和鲁宾费尔德(2006)的观点。平狄克、鲁宾费尔德,2006,《微观经济学》(第四版),北京：中国人民大学出版社,第145—150页。
① Gibrat, R.,1931, Les Inegalites Economiques; Applications:Aux Inegalities Des richesses, A la Concentration Des Enterprises, Aux Populations Des Villes Aux Statistiques Des Ffamilies, Etc., D'une Loi Nouvelle, La loi de L'effet Proportional. Paris:Librairie du Recueil Sirey.
①高铁梅,《计量经济分析方法与建模(第二版)》,清华大学出版社,2009,第4章：118-126。
②数据来源：《中国高技术产业统计年鉴》(2002-2010)和作者计算,北京：中国统计出版社。
①数据来源：《中国高技术产业统计年鉴》(2002-2010)和作者计算,北京：中国统计出版社。
①上海财经大学产业经济研究中心,《2009中国产业发展报告》[R],上海：上海财经大学出版社,2009,第368-382页。
①数据来源：《中国高技术产业统计年鉴》(2002-2010)和作者计算,北京：中国统计出版社。
②研发产出比=研发投入/产出,代表一单位产出所需要的研发投入。
③数据来源：《中国高技术产业统计年鉴》(2002～2010)和作者计算,北京：中国统计出版社。
①潘文卿,外商投资对中国工业部门的外溢效应：基于面板数据的分析[J],世界经济,2003(6),第3-5页。
①余甫功、欧阳建国,2007：《高技术产业发展对工业的带动作用和溢出效应研究》,《数量经济技术经济研究》第7期。
②Feder,G. On Exports and Economic Growth [J]. Journal of Development Economics,1983, (12).
①高铁梅,《计量经济分析方法与建模(第二版)》,清华大学出版社,2009,第10章：319-321。
②白仲林,《面板数据的计量经济分析》,南开大学出版社,2008,第63-73页。
①来源：《1996—2002年全国研究生招生统计年鉴》,北京航空航天大学出版社,2003。
②出口导向指数的数据来源：彭建平、张建华,《国有、三资企业高技术产品出口绩效比较》,《改革》,2007年第9期。
①来源：《中国高技术产业统计年鉴》(2002-2009)和作者计算,北京：中国统计出版社。
②作者根据《中国高技术产业统计年鉴》(2010)计算得到。
③来源：《中国高技术产业统计年鉴》(2010),北京：中国统计出版社。
①来源：《中国高技术产业统计年鉴》(2010)附录3中的指标解释,北京：中国统计出版社。
②来源：《中国高技术产业统计年鉴》(2007和2009),北京：中国统计出版社。
④数据来源：《中国高技术产业统计年鉴》(2010)和作者计算,北京：中国统计出版社。
①来源：潘文卿、李子奈、刘强,中国产业间的技术溢出效应：基于35个工业部门的经验研究[J],经济研究,2011(7),第20页。
③朱有为、徐康宁,研发资本积累对生产率增长的影响[J],中国软科学,2007(4),第60页。
①本章采用Stata10.0软件实现上述操作。
②数据来源：《中国高技术产业统计年鉴》(2010),北京：中国统计出版社。
③数据来源：《中国高技术产业统计年鉴》(2008)和作者计算,北京：中国统计出版社。
④数据来源：《中国高技术产业统计年鉴》(2002),北京：中国统计出版社。
⑤数据来源：作者根据《中国高技术产业统计年鉴》(2002～2010)估算得到,北京：中国统计出版社。
⑥数据来源：作者根据《中国高技术产业统计年鉴》(2006～2010)计算得到,北京：中国统计出版社。
①数据来源：《中国高技术产业统计年鉴》(2010),北京：中国统计出版社。
②数据来源：《中国高技术产业统计年鉴》(2002),北京：中国统计出版社。
③数据来源：《中国高技术产业统计年鉴》(2010),北京：中国统计出版社。
④数据来源：《中国高技术产业统计年鉴》(2010)和作者计算,北京：中国统计出版社。
①数据来源：《中国高技术产业发展年鉴》(2010),北京：北京理工大学出版社,第246页。
②数据来源：《中国高技术产业统计年鉴》(2010)和作者计算。
③数据来源：《中国科技统计资料汇编》(2010),http：//www.sts.org.cn/zlhb/2010/hb2.1.htm#_l。
④作者根据《中国高技术产业统计年鉴》(2009)中公布的研发经费内部支出减去技术改造经费支出、技术引进经费支出、消化吸收经费支出和购买国内技术经费支出四项后得到的数值作为自主研发经费支出。
①数据来源：《中国高技术产业统计年鉴》(2009-2010)。
①数据来源：作者根据《中国高技术产业统计年鉴》(2010)计算得到。
②数据来源：《中国高技术产业统计年鉴》(2010)。
①潘省初、冯媛、周凌瑶,基于2002《国民经济行业分类》国家标准的投入产出序列表的研制,中国投入产出理论与实践2004,中国统计出版社,第754-764页。
②来源：《中国火炬统计年鉴》(2009),北京：中国统计出版社。
③来源：中国中央人民政府网站,http://www.gov.cn/ztzl/kj fzgh/content 883715.htm,2008年2月5日。
④本部分内容参照了Scherer(1983)的观点。Scherer F. M.,1983, "R&D and Declining Productivity Growth", The American Economic Review, Vol.73, (2), pp215-218.
①财税政策作用下高新技术产品消费增长的观点参照平狄克和鲁宾费尔德,2006,《微观经济学》(第四版),北京：中国人民大学出版社,第98一102页。
②作者根据《中国高技术产业统计年鉴》(2010)计算得到,北京：中国统计出版社。
①为与其他各国名称统一,本章使用“高技术产业”一词。
②来源：《中国科技统计资料汇编》(2009-2010),中国科技统计网,http://www.sts.org.cn/zlhb/index.htm。
③来源：《中国高技术产业统计年鉴》(2009),北京：中国统计出版社。
①来源：《国际统计年鉴》(2006/2007),北京：中国财政经济出版社。
①来源：作者根据《中国高技术产业统计年鉴》(2002)计算得到。
①家庭消费率指的是家庭消费支出占国内生产总值的比重。数据来源：作者根据《国际统计年鉴》(2008)计算得到。
①来源：作者根据《中国高技术产业统计年鉴》(2006)计算得到。
①来源：作者根据归并后的《中国投入产出表》(2005)计算得到。
②来源：作者根据归并后的中、日、英、美四国的《投入产出表》(2005)计算得到。
①来源：作者根据归并后的中、日、英、美四国的《投入产出表》(2005)计算得到。
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