中国R&D资本存量测算：1952~2014年

2008年SNA修订了R&D支出的核算方法,R&D支出不再视为中间消耗,而是作为固定资本形成处理。本文依据2008年SNA和我国R&D统计调查数据等,科学测算了1952年以来每年R&D活动所形成的资产价值,同时对R&D资产进口和出口进行了适当调整。然后,在合理选取和估计R&D资产折旧率、R&D价格指数和基年R&D资本存量的基础上,根据永续盘存法对我国1952~2014年R&D资本存量进行了测算。结果显示,我国R&D投资与R&D内部经费支出的年平均比例为95.5%,我国R&D资本存量总体上呈快速增长趋势,2014年达到42244亿元,且R&D资本存量与GDP之比呈“N”形趋势,经历了先上升后下降再上升的过程。     

多视角下R&D资本化测算方法比较与应用

R&D资本化基本测度方法主要有三种：Goldsmith方法、Griliches方法和BEA方法,在不同的经济理念下,三种测度方法既各有特色,又有共同特征。在Goldsmith方法设定理念中,当期R&D资本存量由当期不变价R&D投资额与扣除折旧后的上一期R&D资本存量两部分构成,且当期不变价R&D投资额全部转化为当期资本存量;在Griliches方法设定理念中,当期R&D资本存量由上一期不变价R&D投资额与扣除折旧后的上一期R&D资本存量两部分构成,且上一期不变价R&D投资额全部转化为当期资本存量;而在BEA方法设定理念中,当期R&D资本存量由当期不变价R&D投资额与扣除折旧后的上一期R&D资本存量两部分构成,且当期不变价R&D投资额的一半发生折旧。在具体测算过程中,三种测度方法均要考虑R&D资本存量增长率、R&D资本折旧率、R&D支出价格指数等关键参数的设定。同时,基于三种测度方法比较研究,将其应用于中国R&D资本化估算实践。     

中国财富性与生产性R&D资本存量估算——基于非传统永续盘存法

研究目标:测度1978～2018年中国不同性质的财富性与生产性R&D资本存量,并探讨可比口径下参数设定组合的稳健性检验。研究方法:基于OECD资本测算手册,运用兼备财富和生产属性的非传统永续盘存法估算R&D资本存量。研究发现:1978年以来中国R&D资本存量呈快速上升趋势,财富性R&D资本存量总额、生产性R&D资本存量和财富性R&D资本存量净额三者符合资本测算理论中依次递减规律,反映出财富性和生产性R&D资本存量存在差异;稳健性检验中,单一役龄效率剖面和平均役龄效率剖面汇总公式的参数设定会影响估算结果稳健性,而钟型正态退役分布较稳健。研究创新:选取更适合R&D资产的测算模式,运用具有流量与存量一致性的非传统永续盘存法。研究价值:提高了R&D资本存量测算的科学性,为后续研究奠定了可靠性基础。     

中国工业行业R&D投入的产出效率与影响因素

运用知识生产函数模型,以中国工业行业（1993~2008）为研究对象,在将R&D资本存量分为本国本行业R&D、本国其它行业R&D、外国本行业R&D、外国其它行业R&D资本存量的基础上,首先运用随机前沿生产函数方法对中国R&D投入的产出效率进行了实证研究,随后综合考虑了人力资本、贸易开放度、技术距离、行业竞争程度、物质资本存量、行业技术水平、产权结构等因素对R&D产出效率的影响。结论显示,除外国其它行业R&D资本对R&D投入的产出效率影响不显著外,其它三种R&D资本存量均有显著的正的影响,且人力资本、贸易开放度、物质资本存量等因素均显著的促进了R&D产出效率的提升,技术距离则对R&D产出效率的提升有抑制作用,行业竞争程度对R&D产出效率影响不显著,高技术行业R&D产出效率要比非高技术行业低,国有产权比重较高行业R&D产出效率与国有产权比重较低行业相比并无显著差异。     

中国研发资本测算及其经济增长贡献

本文在国民账户体系（SNA,2008）框架下对中国1952—2014年研发（R&D）资本进行科学测算,在此基础上测度了研发对经济增长的贡献,并利用扩展的索洛模型及隐性变量法进一步分析了考虑研发资本投入的真实全要素生产率水平。研究表明：（1）1952年以来,中国当期新增R&D资产绝对额及相对额均呈快速增长趋势,但与美国相比,水平仍较低;（2）R&D资本投入有效促进了经济增长,其对经济增长贡献达21.95%;（3）过去中国的R&D资本中硬技术比重较高,规则、标准方面的软技术含量相对较低,即技术进步更多地为体现型技术进步;（4）考虑R&D资本投入后的真实全要素生产率水平总体呈先上升后下降的趋势,其经济增长贡献也呈相同趋势,且在近年来对经济增长产生了负向影响。     

中国固定资本存量与研发资本增长效应重估

本文在新的国民经济核算规范SNA2008和CSNA2016下,重新估算了中国固定资本存量与研发资本的增长效应。本文严格参照SNA2008的测算框架和国内研究进展对中国研发资本和总固定资本存量进行了估算,并依照国际核算规范对研发资本的再认识扩展了索洛增长模型。研究发现,中国固定资本存量在1990～2019年快速增长,年均增长率达13.27%,到2019年中国固定资本存量增长至81.889万亿元;进一步将研发资本扩展进索洛增长模型,发现中国研发资本年均经济增长效应为5.85%,年均经济增长贡献率为53.98%,其中直接效应为22.51%,间接效应为31.48%,是推动中国经济增长的重要因素。分地区来看,东中部地区研发资本存在显著的增长效应,因此促进市场良性竞争环境、提高科技转化率和产研结合效率是扩大研发资本经济增长效应和提升经济增长贡献率的重要路径。     

中国经济增长中的公共资本外溢

本文估算了中国1952-2010年的水利基础设施的物质资本存量,并在基于政府生产性支出的内生增长框架中估计水利资本的产出效率,证实公共资本具有显著的外溢效应。在此基础上,本文着重揭示,在基于历史数据的中国经济增长研究中,不仅水利等基础设施公共资本存量存在明显的测量误差,而且总的资本存量、劳动投入等生产要素的基础数据,也可能存在严重的准确性问题,影响了对经济增长的准确判断,急需系统深入的研究讨论加以完善以形成理论共识。     

国际技术外溢渠道的实证研究

本文在对相关文献进行梳理的基础上,测算了中国1985-2005年间通过外国直接投资、对外直接投资、出口贸易和进口贸易四种渠道溢出的外国研发资本存量,并采用国际R＆D溢出回归框架实证分析了各种渠道的技术外溢对于中国全要素生产率的影响。研究结果表明,国内的研发支出是促进全要素生产率增长的最重要因素,通过外国直接投资和出口贸易渠道的技术外溢是全要素生产率增长的重要源泉,但是以对外直接投资和进口贸易为传导机制的国际研发溢出并没有对我国的技术进步起到促进作用。     

家族企业代际传承模式与长期投资决策研究——基于家族化方式的调节效应

以2008—2018年沪深上市家族企业为研究对象,实证检验了家族企业代际传承模式和家族化方式对长期投资决策的影响。研究发现：与职业经理人传承模式相比,子承父业传承模式家族企业的投资规模下降幅度较大,但主要降低的是资本支出,R&D支出在长期投资中的占比下降幅度较小;并且与间接创办型家族企业相比,直接创办型家族企业有利于促进子承父业家族企业长期投资规模的下降,但是却抑制了该类家族企业R&D投入占比的下降。     

中国研发（R&D）资本存量估计：1978—2012

目前鲜有文献涉及R&D资本存量的估计,且存在明显缺陷,以致影响了后续研究的准确性和可靠性,因而有必要延长年限重新估计。本文合理选取R&D投入指标、增长率g、折旧率δ和价格指数权重,利用永续盘存法对中国1978—2012年R&D资本存量进行了测算。研究发现:(1)2000年是中国R&D资本存量增长的突破点,实现了从缓慢低位增长到迅速攀升的转变;(2)R&D资本存量占GDP份额呈现为"U"型走势,经历了先下降后提升的过程;(3)无论是R&D资本存量的绝对值还是R&D资本存量占GDP份额,中国均明显落后于美国。中国R&D活动取得了重要进展,但仍需通过加大R&D投入以提升国家创新能力。     

中国装备制造业全要素生产率增长的波动与异质性

研究目标：中国装备制造业及其细分行业TFP增长率的测定与分解。研究方法：构建超越对数形式的随机前沿生产函数模型,测算中国装备制造业及其细分行业TFP增长率,并对其进行分解。研究发现：中国装备制造业TFP增长率不但在区域和省份之间存在差异,而且存在明显的内部行业异质性;技术进步和配置效率变化分别是提高和阻碍装备制造业TFP增长率的主要原因和障碍;除技术进步均为正值外,技术效率变化、规模效率变化和配置效率变化在装备制造业各行业中异质性相当明显;装备制造业及其细分行业仍未从真正意义上实现由粗放型向集约型增长方式的转变。研究创新：中国装备制造业细分行业TFP增长率及其异质性。研究价值：为装备制造业转型与升级提供经验证据。     

Interindustry R&D Spillovers for Electrical and Electronic Products: The Canadian Case

This paper estimates the effects of interindustry R&D spillovers on the cost and production structure for 10 Canadian manufacturing industries. Because of their high-tech nature and productivity performance, spillovers from electrical and electronic products are distinguished from other spillover sources. Generally, spillovers from electrical and electronic products generate cost reductions and render production processes for Canadian manufacturing industries more capital intensive (i.e. either more physical or R&D capital intensive). Social rates of return for R&D capital are calculated for all 10 industries. The social rates are 5–11 times greater than are the private rates. Indeed, the social rates are high for all the industries. This implies that the electrical and electronic products industry is an important interindustry spillover source but, like other industries, a major spillover-using industry.     

Efficiency evaluation of China's high-tech industry with a multi-activity network data envelopment analysis approach

This paper employs a Russell multi-activity network DEA model and divides the overall innovation process into the upstream Research and Development (R&D) process and the downstream commercialization process to appraise the innovation performance of China's high-tech industries from 2009 to 2013. This model can deal with the problems of intermediates, shared inputs and slack-based measure in a unified framework, and the result can provide policy makers with process-specific information on how to improve the innovation performance of China's high-tech industries. The main findings are presented as follows. First, the overall efficiency of China's high-tech industries still remains at a low level, which has its roots mainly in commercialization inefficiencies other than R&D inefficiencies. Second, for most provinces, their R&D efficiencies do not match up with their commercialization efficiencies. Finally, the innovative activities of China's high-tech industries should be driven by the market demand -oriented for the improvement of innovation efficiency.     

Reprint of "Performance evaluation of China's high-tech innovation process :Analysis based on the innovation value chain"

The Chinese high-tech industry has developed greatly since the beginning of China's “National High-tech R&D (863) Program” and “China Torch Program”. This paper introduces a conceptual model extended from the innovation value chain model to simultaneously estimate the R&D and commercialization efficiencies for the high-tech industries of 29 provincial-level regions in China. To match reality, a network DEA incorporating both shared inputs and additional intermediate inputs is constructed to open the “black box” view of decision making units used in single-stage DEA. This study is the first attempt to link the R&D and commercialization with a solid theoretical foundation and feasible mathematical methods. The empirical findings show that most of the 29 regions have low efficiency in the commercialization sub-process compared to the R&D sub-process, although there are regional differences in China's high-tech industry. Pearson correlation shows that the R&D sub-process is not closely correlated to the commercialization sub-process in terms of efficiency. Our analysis can provide information for the formulation of policies to achieve high innovation efficiency.     

Performance evaluation of China's high-tech innovation process: Analysis based on the innovation value chain

The Chinese high-tech industry has developed greatly since the beginning of China's “National High-tech R&D (863) Program” and “China Torch Program”. This paper introduces a conceptual model extended from the innovation value chain model to simultaneously estimate the R&D and commercialization efficiencies for the high-tech industries of 29 provincial-level regions in China. To match reality, a network DEA incorporating both shared inputs and additional intermediate inputs is constructed to open the “black box” view of decision making units used in single-stage DEA. This study is the first attempt to link the R&D and commercialization with a solid theoretical foundation and feasible mathematical methods. The empirical findings show that most of the 29 regions have low efficiency in the commercialization sub-process compared to the R&D sub-process, although there are regional differences in China's high-tech industry. Pearson correlation shows that the R&D sub-process is not closely correlated to the commercialization sub-process in terms of efficiency. Our analysis can provide information for the formulation of policies to achieve high innovation efficiency.     

改革开放以来中国出口增长推动力的阶段性演进及地区分布差异

研究目标：研究中国出口增长推动力的阶段性演进及地区分布差异。研究方法：基于中国1978~2014年的省级面板数据,采用超越对数形式的随机前沿模型进行分析。研究发现：在经济转型期,市场化改革与对外开放的发展是中国出口增长的首要推动力;在“入世”准备期,中国出口增长由制度因素、物质要素投入协同推动;在“入世”增长期,物质要素投入成为中国出口增长的首要来源;在全球引擎期,物质要素投入协同贸易潜力主导中国出口贸易的发展;地区间出口贸易差距主要源于贸易潜力、资本与制度因素的三重差异。研究创新：对改革开放以来至2008年金融危机以后中国出口增长推动力的阶段性演进进行系统研究。研究价值：针对中国贸易可持续发展面临的主要挑战,提供政策建议。     

Interactive strategies in supply chains–a double-edged portfolio approach to small-and medium-sized subcontractors’ position analyses

China is concerned to improve the technical capability of its industry. It has chosen Science and Technology Industry Parks (STIPs) as the model for incubating its R&D capability and driving its hi-tech policy. Against this background, the authors examine two main issues. First, we review assessments of university science parks in the UK and a wider context extracted from the literature before examining specifically China's R&D intensity and hi-tech policy. Second, we examine the performance of hi-tech companies situated on STIPs and those located outside STIPs, comparing their success in commercializing technology. We pay particular attention to the role of entrepreneurship in this activity by those engaged in it. Our findings are based on secondary quantitative data and qualitative data collected by means of interviews and focus groups in the Beijing and Shanghai areas in March 2004. From our research it is clear that China lags behind OECD countries in its R&D capability and the technology transfer rate is low, hampering China's hi-tech potential, although China is achieving some success in hi-tech exports, notably of ICT goods. Furthermore, innovation capability, locational factors such as being located in a regional industry cluster (in or outside STIPs), guanxi and networking opportunities, entrepreneurial skills, including international business experience and access to more financial sources and capital for developing the business, are essential for commercializing technology effectively in China. The role of entrepreneurship is evident. However, it remains still underdeveloped in China's STIPs.     

Intangible capital in the pharmaceutical and chemical industry

We investigate whether measures of intangible capital based on advertising and R&D can explain variation in Tobin's Q ratio for the pharmaceutical and chemical industry. The study is motivated by prior literature studying this relation in other industries, recent literature investigating intangible capital in this industry, and the larger controversy about whether stock valuations have been high due to irrational investors or large investment in intangible capital. We find that our measures of intangible capital are statistically significant determinants of Q and explain 20% of the variation in our sample. When age and industry are incorporated into the model our explanatory power reaches 25%.     

How to optimize the allocation of research resources? An empirical study based on output and substitution elasticities of universities in Chinese provincial level

Although significant progress has been made in China's basic research in recent years, there remains a wide gap between research in China and that from developed countries. How to optimize the allocative efficiency of research resources is of great importance for increasing research output. In this paper, using the fixed effect stochastic frontier model based on the translog production function, we estimate output and substitution elasticities of research and development (R&D) inputs at universities in China's provincial level during 2009–2016. We find that the R&D technical efficiency of China's universities, after a rapid growth, has tended to become relatively stable. Improvements of internationalization degree and exogenous R&D capabilities are conducive to promoting R&D technical efficiency, whereas expenditures from government grants inhibit the promotion of R&D technical efficiency; the effects of R&D capital deepening and internet penetration are not evident. The output elasticity of R&D capital is much higher than that of R&D personnel, suggesting that R&D capital is the main driving force of research output. The substitution elasticity between R&D capital and personnel has experienced a change from substitution to complementary since 2014. To realize sustained growth of research output, we should increase R&D input with positive output elasticity or reduce R&D input with negative output elasticity, making the necessary trade-offs according to the substitution relationship between the two R&D inputs.     

中国企业参与垂直分工会促进其技术创新吗？

研究目标：研究中国企业参与垂直分工会对其技术创新产生何种影响。研究方法：利用2000~2013年中国工业企业数据库与海关贸易统计库匹配数据测算中国企业的垂直专业化指数（VSS）,继而实证分析垂直分工对不同所有制、贸易类型及组织模式的企业技术创新的影响。研究发现：中国企业的VSS从2000年的0.48下降至2013年的0.27;整体来说,中国企业参与垂直分工对其技术创新产生了显著的抑制效应;区分所有制、贸易方式和组织模式后发现,垂直分工对外资企业、加工企业及外资加工企业的创新抑制效应最大。研究创新：在Upward等（2013）和张杰等（2013）关于VSS测算方法的基础上进行了改进。研究价值：支撑了中国目前实施的“做强一般贸易、扩大一般贸易规模”的政策。该政策虽然使得企业的垂直分工程度不断下降,但不会削弱其技术创新能力。