融资约束、政府财政资助与企业研发投入

本文在不同融资约束背景下对政府财政资助与企业研发投入的关系进行了实证检验。实证结果表明,无论融资约束强的企业还是融资约束弱的企业,政府财政资助对企业研发投入都具有诱导效应。与融资约束强的企业相比,政府财政资助对企业研发投入的诱导效果在融资约束弱的企业中表现得更好,且与企业的股权性质无关;此外,与非国有控股企业相比,国有控股企业的诱导效应对融资约束的强弱更加敏感。     

政府 R&D资助与研发效率要要基于高技术产业的实证研究

文章在基于随机前沿分析方法测度出中国高技术产业研发效率的基础上,运用 Tobit 面板估计方法实证分析了政府 R&D 资助对研发效率的影响及其决定因素.研究发现,中国政府 R&D 资助显著促进了高技术产业研发效率的提升,同时,产权结构、企业规模会对政府 R&D 资助效果产生显著影响,行业中国有产权比重不利于政府 R&D 资助效果的发挥,企业规模则会对政府 R&D 资助效果产生显著的正向效应.     

政府资助产业共性技术研发的原理及模式研究

以往研究政府对共性技术资助的绝大部分研究都从宏观的角度进行实证分析,缺乏从政府资助对研发企业研发收益和风险影响的微观研究,并且到目前为止关于政府资助企业进行技术研发是具有互补还是替代效应到目前为止还没有比较一致的结论。文章利用企业进行共性技术开发和商业化的一个三阶段模型,从政府资助共性技术研发对研发企业收益和风险影响的微观角度研究了政府资助对共性技术研发企业研发投入的影响,并识别了共性研发失灵的主要影响因素以及政府对共性技术研发企业资助效果的作用原理及主要影响因素;最后,文章就政府资助共性技术研发的模式给出了政策建议。     

企业研发会计核算与政府统计的衔接问题研究

企业研发会计核算与政府研发支出统计原本是各自封闭的两个截然不同的系统,然而随着国民经济核算模式的改良调整,以及政府统计手段的不断优化改进,理论和实务界人士越来越意识到企业研发会计核算与政府统计衔接融合的重要性和迫切性.文章从上述两套系统的衔接融合探讨入手,在比较两者研发核算异同的基础上,揭示出两者衔接融合的主要难点障碍,继而提出了破除鸿沟隔阂推进企业研发会计核算与政府统计对接嵌入的框架思路,并以江苏省为例,总结介绍了该省企业会计与政府统计在研发支出核算上实现顺畅衔接的成功经验,最后有针对性地提出了强化组织领导、建立研发台账数据库和卫星账户以及加强专业人员培训的政策建议.     

政府R&D资助、对外开放与中国光伏企业创新能力提升

以战略性新兴产业之一的光伏产业为例以战略性新兴产业之一的光伏产业为例,从政府R&D资助和对外开放两个层面选取指标资助和对外开放两个层面选取指标,分析这些变量对我国光伏企业自主创新能力的影响。研究表明研究表明,政府R&D补助对企业盈利能力的正效应较为显著补助对企业盈利能力的正效应较为显著,对外开放和资产负债率对企业创新活动有较为显著的正效应。具有较强自主创新能力的企业通常具有较好的盈利能力具有较强自主创新能力的企业通常具有较好的盈利能力,所以企业盈利能力在一定程度上反映了企业的创新能力。因此因此,加大政府研发补助、扩大企业出口和保持适当的资产负债率等措施扩大企业出口和保持适当的资产负债率等措施,有利于提高光伏企业的自主创新能力。     

我国政府R&D直接资助的规模与结构探究

文章着重分析了政府对企业R&D直接资助的规模与结构。在此基础上,对我国R&D经费投入总体情况作出以下评价:第一,我国R&D经费投入不足,缺乏一套较为稳定和长期的R&D经费投入机制;第二,我国R&D经费投入的结构占比不合理;第三,企业是我国R&D投入当之无愧的执行主体。就我国政府对企业R&D直接资助作出以下评价:第一,政府对企业R&D直接资助力度在加强但比重仍然偏低,并且倾向于大中型企业;第二,政府资助对象主要是内资企业,且对私营经济的资助总量偏低;第三,政府资助的行业投向有待优化,对高技术产业资助力度有待加强。     

政府科技投入最优规模研究——以企业研发投入规模最大化为目标

文章采用2009年至2011年各省、市、自治区的政府科技投入及企业研发投入等数据,以企业研发投入规模最大化为目标,估算了政府科技投入的最优规模。研究表明,政府科技投入规模与企业研发投入规模之间是倒“旷型相关关系,政府科技投入的最优规模为23％;目前我国各地区的政府科技投入规模偏低,非常不平衡,除北京超过了最优投入规模水平之外,其他地区的政府科技投入规模优化度均不足50％。     

政府研发补助、寻租与企业研发绩效

以2009—2016年我国创业板上市公司数据为样本,将政府研发补助作为研究核心,探讨政府研发补助与企业研发绩效之间的关系。研究发现:政府研发补助对企业研发投入、产出以及研发效率(以研发投入与会计业绩之间的关系衡量)的影响均正向显著,政府研发补助对研发效率(以研发投入与未来专利产出关系衡量)的影响不显著;对于寻租企业来说,政府补助会显著促进企业的研发投入以及专利产出,但对会计业绩以及研发效率的影响不显著;对于非寻租企业来说,政府研发补助对企业会计业绩以及研发效率(以研发投入与会计业绩之间关系衡量)有显著的正向影响,但对企业研发投入、企业未来专利的产出以及研发效率(以研发投入与未来专利产出之间关系衡量)均无显著影响。     

政府资助研发促进国际贸易与经济增长作用研究

本文在相关文献研究基础上,对政府资助研发活动对经济增长和国际贸易发展的影响机制和乘数作用进行了研究,构建了政府资助研发资金对经济增长和国际贸易发展的影响机制模型,提出了政府资助研发资金经济增长乘数和政府资助研发资金国际贸易发展乘数的概念,并运用协整理论对我国1991-2010年数据进行了实证,计算出了具体乘数,分析了当前我国政府资助研发资金在促进经济增长和国际贸易发展方面存在问题并提出政策建议.     

Learning from R&D outsourcing vs. learning by R&D outsourcing

We analyze how research and development (R&D) outsourcing influences product innovation. We propose a separation between learning from R&D outsourcing, whereby the firm improves its ability to innovate by using outsourced R&D directly in new products, from learning by R&D outsourcing, whereby the firm indirectly uses outsourced R&D by integrating it with internal R&D to create new products. Building on the knowledge-based view, we argue that learning from R&D outsourcing is likely to have an inverse U-shaped relationship with product innovation, because the initial benefits of using outsourced component R&D knowledge to innovate products is eventually outweighed by the hollowing out of the firm's ability to innovate. In contrast, we propose that learning by R&D outsourcing is likely to have a U-shaped relationship with product innovation, because the initial challenges of integrating internal and external R&D are eventually overcome, resulting in more innovations. Finally, we distinguish between domestic and foreign R&D outsourcing and propose a liability of foreignness in R&D outsourcing as it has a lower impact on new products than domestic R&D outsourcing. The empirical analysis shows that outsourced R&D has an inverted U-shaped relationship with the number of new products, while the interaction between outsourced R&D and internal R&D has a U-shaped relationship with the number of new products. It also shows that domestic outsourced R&D has a higher positive impact on the number of new products than foreign outsourced R&D.     

Optimal R&D investment for a risk-averse entrepreneur

Entrepreneurs investing in R&D projects face technical uncertainty associated with the cost to completion of the project, which is idiosyncratic and inherently unhedgeable. We extend existing real options models of R&D investment to incorporate the cost of bearing this unhedgeable risk and find it decreases risk-averse entrepreneurs’ valuations of R&D projects and increases the minimum NPVs required for continued investment in R&D (threshold NPVs) relative to ‘unpriced risk’ values and threshold NPVs. As in the ‘unpriced risk’ case, for less risk-averse entrepreneurs with small R&D projects, threshold NPVs remain negative and decrease with technical uncertainty. However, for sufficiently risk-averse entrepreneurs with sufficiently large R&D projects, threshold NPVs can become positive and increase with technical uncertainty.     

R&D and aggregate fluctuations

Empirical observations raise interesting questions regarding the sources of the excessive volatility in the R&D sector as well as the nature of the relation between the sector and aggregate fluctuations. Using US data for the period 1959–2007, we identify sectoral technology and capital investment-specific shocks by employing a Vector Autoregression. The identifying assumptions are motivated by a two-sector dynamic general equilibrium model. Controlling for real and nominal factors, we find that capital investment-specific shocks explain 70 percent of fluctuations of R&D investment, while R&D technology shocks explain 30 percent of the variation of aggregate output, net of R&D investment. Technology shocks jointly explain almost all the variation of output in the R&D sector and 78 percent of the variation of output in the rest of the economy. They also constitute the main factor of the procyclicality of R&D investment.     

Industry evolution and R&D externalities

R&D externalities can imply ranges of aggregate increasing returns to scale in R&D. As a consequence several equilibria can exist involving different numbers of firms and different R&D investment levels. In a theoretical model the equilibrium dynamics are analyzed, showing that cyclical fluctuations of the number of firms and R&D investment may be expected, and that the long-run equilibrium is highly sensitive to investors' initial beliefs. The model is tested empirically using a unique database comprising competing firms in various R&D races.     

Introduction: Input–Output Analysis of Interindustry R&D Spillovers

As an introduction to this special issue on intersectoral R&D spillovers, I shall first explain what these spillovers are and how economists try to estimate them. I shall then describe the seven papers selected for this issue from the expanding literature on R&D spillovers, summarize their major results and suggest further avenues of research in this area.     

R&D subsidies and productivity in eastern European countries

This paper shows that R&D subsidy policies at the European Union (EU) and national levels stimulated labor productivity in Central and Eastern European countries (CEEC) in the years after their entry to the EU. However, the average impact of national funding on labor productivity was higher for countries in the Western control group than in the CEEC sample. EU R&D subsidies compensated the CEEC in part for the greater innovation impact of Western economies. Although they crowded out some R&D subsidies by local governments at the country level, the EU subsidies crowded in many national and local subsidies at the firm level. Local/regional state innovation aid to enterprises encouraged no increase in labor productivity in all but one of the sample CEEC countries. These impacts are assessed in a sequential structural econometric model estimated using Eurostat’s collection of Community Innovation Surveys covering the years 2006–2014.     

Issues in Assessing the Effect of Interindustry R&D Spillovers

This paper aims to clarify three issues concerning the weighting methodol ogy generally used to evaluate interindustry R&D spillovers. These issues concern the likely nature of the spillovers estimated through different types of supporting matrices; the similarity between input–output (IO), technology flows and technological proximity matrices; and the relevance of the assumption that a single matrix can be used for different countries. Data analyses of weighting components show that technology flows matrices are in an intermediate position between IO matrices and technological proximity matrices, but closer to the former. The various IO matrices, as well as the three technological proximity matrices, are very similar to each other. The panel data estimates of the effect of different types of interindustry R&D spillovers on industrial productivity growth in the G7 countries reject the hypotheses that a technology flows matrix can be approximated by an IO matrix and that a single IO matrix can be usedfor different countries. By transitivity, the procedure that comprises using a single technology flow for several countries is not reliable. The international comparison shows that each country benefits from different types of R&D externality. In Japan and, to a lesser extent, in the US, the rate of return to direct R&D is very high and is likely to compensate for relatively weak interindustry R&D spillover effects. In the five other industrialized countries, the reverse observation is true: strong social rates of return to R&D counterbal ance the poor performances of direct R&D.     

Abatement R&D,market imperfections,and environmental policy in an endogenous growth model

We develop an endogenous growth model featuring environmental externalities, abatement R&D, and market imperfections. We compare the economic performances under three distinct regimes that encompass public abatement, private abatement without tax recycling, and private abatement with tax recycling. It is found that the benefit arising from private abatement will be larger if the degree of the firms’ monopoly power is greater. With a reasonably high degree of monopoly power, a mixed abatement policy by which the government recycles environmental tax revenues to subsidize the private abatement R&D is a plausible way of reaching the highest growth rate and welfare.     

Technology ladders and R&D in dynamic Cournot markets

Motivated by dramatic and unpredictable technological advances in energy production (for instance drilling and extraction of shale oil), we extend Cournot models of competition to incorporate research and development (R&D) that can lead to (stochastic) drops in production costs. Our model combines features of patent racing with dynamic market structure, capturing the interplay between the immediate competition in terms of production rates and the long-term competition in R&D. The resulting Markov Nash equilibrium is found from a sequence of one-step static games arising between R&D successes, and several numerical examples and extensive analysis of the emerging comparative statics are presented. Analyzing the relationship between current market dominance and the level of R&D investments, we find that market leaders tend to invest more, which in some sense makes oligopoly dynamically unstable. We show that anticipated market transitions have long-term impact; for example the potential of future monopoly can spur R&D investment now, even if the firm is presently uncompetitive and not actively producing. We also show that, surprisingly, random innovations have an ambiguous effect on R&D. This feature, which is driven by the Cournot framework, contrasts with the common situation whereby uncertainty lowers innovation and delays R&D investments. Finally, we demonstrate that increased competition may actually increase efforts to innovate through higher desire to achieve dominance. This would match the anecdotal evidence that the threat of market entrants forces incumbents to maintain high R&D.     

Mining external R&D

Open Innovation presses the case for timely and thorough intelligence concerning research and development activities conducted outside one’s organization. To take advantage of this wealth of R&D, one needs to establish a systematic “tech mining” process. We propose a 5-stage framework that extends literature review into research profiling and pattern recognition to answer posed technology management questions. Ultimately one can even discover new knowledge by screening research databases.Once one determines the value in mining external R&D, tough issues remain to be overcome. Technology management has developed a culture that relies more on intuition than on evidence. Changing that culture and implementing effective technical intelligence capabilities is worth the effort. P&G's reported gains in innovation call attention to the huge payoff potential.