Research,Innovation And Productivi[Ty: An Econometric Analysis At The Firm Level

This paper studies the links between productivity, innovation and research at the firm level. We introduce three new features: (i) A structural model that explains productivity by innovation output, and innovation output by research investment: (ii) New data on French manufacturing firms, including the number of European patents and the percentage share of innovative sales, as well as firm-level demand pull and technology push indicators; (iii) Econometric methods which correct for selectivity and simultaneity biases and take into account the statistical features of the available data: only a small proportion of firms engage in research activities and/or apply for patents; productivity, innovation and research are endogenously determined; research investment and capital are truncated variables, patents are count data and innovative sales are interval data.

We find that using the more widespread methods, and the more usual data and model specification, may lead to sensibly different estimates. We find in particular that simultaneity tends to interact with selectivity, and that both sources of biases must be taken into account together. However our main results are consistent with many of the stylized facts of the empirical literature. The probability of engaging in research (R&D) for a firm increases with its size (number of employees), its market share and diversification, and with the demand pull and technology push indicators. The research effort (R&D capital intensity) of a firm engaged in research increases with the same variables, except for size (its research capital being strictly proportional to size). The firm innovation output, as measured by patent numbers or innovative sales, rises with its research effort and with the demand pull and technology indicators, either directly or indirectly through their effects on research. Finally, firm productivity correlates positively with a higher innovation output, even when controlling for the skill composition of labor as well as for physical capital intensity.     

Human capital and firms’ innovation: evidence from emerging economies

ABSTRACT

We explore the relationship between human capital and firms’ innovation in emerging economies. Most papers consider the formal knowledge developed in R&D laboratories as a major source of innovation. However, a critical portion of knowledge required for innovation resides in human resources and is created outside any formalised R&D activity. We consider that, to improve their technological capabilities, firms should invest in different forms of human capital, namely highly educated workforce and experienced managers, but also in strategic human resource (HR) practices aimed at developing human capital by increasing employees’ firm-specific technical skills and competences. Besides looking at the type of innovation outcomes, we place greater emphasis on the strategies of innovation development, as these should signal an improved firms’ ability, not just to innovate, but to put their own creative effort in the development of innovation. Our results contrast with the traditional view of firms in emerging economies as mainly relying on the external acquisition of innovations, by showing their actual ability to develop new technologies. In this respect, HR practices aimed at fostering employees’ learning and autonomy at work appear more important than the educational attainment of workers, whilst the experience of managers does not seem effective.     

Measuring and Explaining Innovative Capability: Evidence from Southeast Asia

What causes firm‐level product innovation in developing economies? This paper answers this question by emphasizing the role of process improvements that are influential in product innovation. We construct a firm‐level innovative capability score using novel, broad‐based, but detailed data on various process improvement practices obtained from firms in Southeast Asia. We then investigate the factors that may affect innovative capability. We also estimate the effect of the innovative capability score on product innovation controlling for research and development intensity and other firm characteristics. Our empirical investigation identifies a chief executive officer (CEO)'s past experience at a foreign or large firm, and buyer pressure to adopt international standards as key determinants of innovative capability. Novel and unique findings from our examination include: (i) the impact of a CEO's past experience at a foreign or large firm on the innovative capability is larger for local enterprises and small‐ and medium‐sized enterprises; (ii) the impact of share of foreign workers in the upper managerial levels only appears to be significant in foreign firms and larger firms; and (iii) buyer pressure is a more likely contributor to innovative capability compared with capital tie‐ups with multinational enterprises or joint venture buyers that capture vertical technology transfers. Finally, our empirical results show that a firm in Southeast Asia is more likely to achieve product innovation if the firm has had a higher innovative capability.     

知识产权保护对我国成长型创新企业自主创新影响的定量分析

以创业板上市企业2009-2014年面板数据为样本,定量分析知识产权保护对成长型创新企业技术创新的影响。研究表明,对创新投入的影响：加强知识产权保护对成长型创新企业研发资本投入具有显著促进作用;加强政府补贴资助力度会进一步强化这一促进作用;企业利润越高、规模越大,加强知识产权保护对企业研发投入的促进作用越大。对创新产出的影响：目前,各地加强知识产权保护能促进成长型创新企业发明专利产出,但是知识产权保护水平较高地区,如北京、上海、天津、广东、浙江和江苏知识产权保护抑制实用新型专利产出。企业研发资本投入增加、政府补贴提高、企业利润水平提升、规模扩大等都会提高知识产权保护对创新产出的正向促进作用。知识产权保护水平提高对于外观设计申请量的影响显著为负。     

组织创新氛围、网络嵌入对员工创新行为的影响

员工创新行为是企业获得持续竞争优势的关键，并受到员工所拥有资源的影响。新时代背景下，员工借助组织嵌入网络获取的异质性资源成为促进创新行为的关键要素。基于资源保存理论，构建组织创新氛围、网络嵌入和员工创新行为关系模型并进行实证调查研究，结果发现：组织创新氛围各维度中，资源供应、团队协作显著促进员工创新行为，而领导效能影响不显著；组织创新氛围与员工关系嵌入显著正相关，资源供应、团队协作与结构嵌入显著正相关，但领导效能对结构嵌入影响不显著；网络嵌入在资源供应、团队协作与员工创新行为关系中发挥中介作用，但在领导效能与员工创新行为关系中不起中介作用。最后，提出建立高绩效工作系统、优化和完善激励机制、强化内部创新文化氛围建设、提升企业和员工网络嵌入水平等管理建议。     

创业投资对异质性创新的甄别效应及作用机制

企业创新活动在质量上存在异质性，采用渐进式创新与突破式创新二分法，利用2009-2016年创业板上市公司数据探究创业投资的影响。使用创业投资哑变量进行Tobit估计和PSM检验，发现创业投资对于突破式创新具有明显的额外激励效应，再使用创业投资持股比例进行Tobit估计和Heckman两阶段模型的内生性检验，发现创业投资显著抑制了渐进式创新，却与突破式创新呈现出“倒U型”关系，体现了非控股性质的创业投资对于异质性创新的甄别效应。进一步，中介效应模型显示,缓解融资约束起到了完全中介作用，交互效应模型表明吸收能力起到了平滑的调节作用。     

一步到位还是步步为营？哪种资本战略更激励创新

在多层次资本市场框架下,研究资本战略选择对创新投入的影响,通过手工搜集从新三板转板至主板上市企业（成功实行步步为营资本战略企业）的相关数据,利用PSM匹配直接IPO上市的公司（实行一步到位资本战略企业）,比较两种不同资本战略实施对创新投入的差异化影响。结果表明,借助多层次资本市场成长的步步为营资本战略上市公司具有更高的创新投入。在此基础上,探究企业内部决策机制、资本市场中观层面以及宏观经济政策在资本战略影响创新投入过程中的作用。结果表明,资本战略通过缓解投融资约束提高研发费用化强度和研发资本化强度;中观层面,分析师关注起调节作用,分析师关注程度越高,实施步步为营资本战略上市公司的研发资本化强度越高;外部经济政策不确定性会降低企业创新投入,进而产生挤出效应,但是挤出效应在实施步步为营资本战略上市公司中得到部分缓解。研究结论对创新企业如何更好地利用资本市场助力自身发展具有一定启示意义。     

CAS视角下创新成功率与创新周期对两类创新模式的影响

创新模式选择有着复杂的内外部因素，现有研究缺少对核心因素与不同创新模式之间影响机理、影响结果的详细刻画。鉴于此，引入复杂适应系统理论，将影响因素集中于创新成功率和创新周期，抓住企业发展过程中生产销售、创新、贷款、还款等核心环节，建立基于主体的仿真模型。结果表明：①创新成功率对两类企业存活数量有正向影响，且对渐进式创新企业影响更显著，创新成功率与企业平均资金余额正相关，当突破式创新成功率超过渐进式创新成功率一半时，突破式创新企业平均资金余额大于渐进式创新企业平均资金余额；②创新周期与突破式创新企业存活数量、渐进式创新企业存活数量之间不存在明显关系，但与两类企业平均资金余额呈负相关；③创新成功率和创新周期对两类企业平均资金余额变化有正向协同作用，且该协同作用对突破式创新企业更显著。     

风险投资背景、持股比例对初创企业技术创新产出的影响

为研究风险投资对初创企业技术创新产出的影响，基于中介效应模型，结合数据包络分析方法和静态面板回归分析方法，对创业板上市公司样本进行了实证分析。研究发现：有风险投资参与的初创企业技术创新产出高于无风险投资参与的初创企业，且风险投资持股比例越高，对初创企业创新的促进作用越显著。不同背景的风险投资对初创企业技术创新产出的影响不同：政府风险投资和外资风险投资持股比例越高的初创企业全要素生产率越高，且政府背景风险投资最为有效，外资背景风险投资次之；研发投入在风险投资与技术创新之间发挥部分中介作用，即风险投资通过直接作用和间接作用共同影响初创企业技术创新产出。     

人力资本、科技创新与信息经济发展关系研究

基于2006-2015年全国20个省市面板数据,利用双对数回归模型,实证分析了人力资本、科技创新与信息经济发展关系,并对人力资本和科技创新的异质性效应进行了验证。结果显示：人力资本、科技创新以及两者的交互作用均对信息经济发展具有显著正向影响,其中,人力资本的作用最大。此外,人力资本和科技创新都对信息经济发展具有异质性效应,其中,在人力资本异质性方面,体力劳动者、基础型人力资本的系数为负,而技能型人力资本、创新型人力资本系数为正,就作用强度而言,基础型人力资本最大,技能型人力资本最小;在科技创新异质性方面,科技创新对信息经济发展的影响取决于技术含量和创新程度,技术含量和创新程度越高,对信息经济发展的促进作用越大。     

董事长—总经理校友关系对公司创新投入的影响——公司内部控制与机构投资者持股的调节作用

作为社会关系的重要一环,校友关系会对管理者决策产生影响。选取2012—2017年中国沪深两市A股上市公司为研究样本,利用固定效应模型检验董事长—总经理校友关系对公司创新投入的影响,通过考察公司内部控制和机构投资者持股对上述影响的调节作用,进而揭示其中相关作用机制。结果显示：董事长—总经理校友关系会促进公司创新投入;公司内部控制和机构投资者持股均正向调节董事长—总经理校友关系对公司创新投入的促进作用。进一步研究发现,董事长—总经理校友关系对公司创新投入的促进作用在非国有企业、高科技公司中更显著,而地区市场化程度差异对上述促进作用的影响并未表现出显著不同。研究结论能够为公司更有效地植入校友文化、完善选人用人与高管再教育机制等提供管理启示。     

联盟组合多样性中的创新价值获取——搜索惯例和社会资本的作用

根据资源基础理论和动态能力理论,采用问卷调查法,对联盟组合多样性中创新价值的获取进行了深入的研究.探讨了联盟组合多样性与企业创新绩效的关系,分析了搜索惯例在二者关系中的中介作用及社会资本的调节作用.研究结果表明:联盟组合多样性与企业创新绩效呈非线性倒U型关系;搜索惯例在联盟组合多样性与企业创新绩效之间起中介作用;结构型社会资本和关系型社会资本均正向调节联盟组合多样性与搜索惯例之间的倒U型关系和上述中介作用.其中,关系型社会资本在两种调节效应中的作用都更强.     

产学研创新资源错配对省域创新效率的影响——基于要素扭曲测度模型与超效率SBM-DEA模型

基于2009-2018年中国内地30个省市区（西藏数据缺失）面板数据,利用要素扭曲测度模型测算企业、高校、科研机构的人才错配指数和资金错配指数,将资源配置分为相对不足和相对冗余两种情形,并采用超效率SBM-DEA模型测算省域创新效率,进而探讨产学研创新资源错配对省域创新效率的影响。研究发现,就不同省域而言,企业“人多财寡异曲同工”,人才配置冗余和资金配置不足均有利于省域创新效率提升,而人才配置不足和资金配置冗余对省域创新效率的影响不显著;高校“人财多寡事关创新兴衰”,人才配置不足和资金配置不足不利于省域创新效率提升,人才配置冗余和资金配置冗余有利于省域创新效率提升;科研机构“人财不足掣肘创新”,人才配置不足和资金配置不足均不利于省域创新效率提升,人才配置冗余和资金配置冗余对省域创新效率的影响不显著。     

英国构建国家创新评价体系的发展现状与趋势

文章结合欧盟传统的创新指标，分析了英国的创新与其他发达国家存在着的差距，提出了英国悖论（UK Paradox）：即没有创新的经济成功。然后，进一步从对这一悖论的原因分析入手，对英国的隐性创新、开放创新、创新“需求侧”、柔性创新进行概括性研究。为了实现对创新全面科学的评价，为对我国建立创新评价指标体系提供借鉴，文章介绍了英国创新需求指标体系，创新投入、企业创新和创新环境指标体系，以及柔性创新指标体系等，并在此基础上对英国的经验进行了简要总结，供国内相关创新管理者和研究人员参考。     

城市科技创新效率与网络结构特征——对国家级创新型城市的实证分析

以2003—2017年中国75个创新型城市面板数据为样本，首先，运用SBM超效率模型测度各城市科技创新效率；其次，基于修正引力模型测度城市间创新联系强度，运用社会网络分析法，从人才流动、资本流动和制度学习3个方面对创新型城市的网络结构及演变特征进行测度和分析；最后，利用考虑城市地理位置的地理加权回归（GWR）模型分析网络结构特征对科技创新效率的影响机制。结果发现：①科研基础设施和人才流动中心度对城市科技创新效率提升具有促进作用，而制度学习中心度、人才教育和产业结构为负向影响；②随着时间推移，城市人才流动中心度对科技创新效率提升具有积极促进作用且趋于强化，资本流动中心度从具有微弱的积极作用趋向于在不同城市呈现出激励和阻碍两种效应，制度学习中心度的负面影响亦趋于强化；③各城市创新网络结构对科技创新效率的影响在测度期前期差别较小，而在后期呈现出越发显著的空间差异性。     

上市公司股票流动性对企业创新的促进作用*

本文利用A股上市公司的交易数据和财务数据，通过多种匹配分析方法控制企业的异质性，分析了股票流动性对企业创新的影响。本文研究发现股票流动性好的企业其创新能力更强。融资融券业务提升股票流动性但是不影响企业创新活动，基于融资融券业务的拟自然实验分析发现流动性改善有利于企业扩大研发投资规模，提高创新能力。股票流动性促进企业创新的作用机制包括提高融资规模以及提高机构持股比例。本文为通过发展资本市场促进企业创新提供了经验证据。     

企业家技术进步路径选择与经济增长

发达国家的知识和技术进步速度越快,发展中国家越是能收到技术模仿的好处,从而带来较高的经济增长率。越是接近技术前沿的发达国家,创新型企业家的作用越大,离技术前沿越远的发展中国家,模仿型企业家的作用往往更明显。发展中国家的企业家通过知识过滤、吸收、模仿、"干中学",不断积累人力资本和物质资本,为自主创新积蓄力量,最终能实现模仿式创新和自主创新的良性互动。     

城市科技创新效率与网络结构特征——对国家级创新型城市的实证分析

以2003—2017年中国75个创新型城市面板数据为样本，首先，运用SBM超效率模型测度各城市科技创新效率；其次，基于修正引力模型测度城市间创新联系强度，运用社会网络分析法，从人才流动、资本流动和制度学习3个方面对创新型城市的网络结构及演变特征进行测度和分析；最后，利用考虑城市地理位置的地理加权回归（GWR）模型分析网络结构特征对科技创新效率的影响机制。结果发现：①科研基础设施和人才流动中心度对城市科技创新效率提升具有促进作用，而制度学习中心度、人才教育和产业结构为负向影响；②随着时间推移，城市人才流动中心度对科技创新效率提升具有积极促进作用且趋于强化，资本流动中心度从具有微弱的积极作用趋向于在不同城市呈现出激励和阻碍两种效应，制度学习中心度的负面影响亦趋于强化；③各城市创新网络结构对科技创新效率的影响在测度期前期差别较小，而在后期呈现出越发显著的空间差异性。     

Innovation spending and productivity growth in the German economy 1980–1986

A newly developed technique involving vertically integrated input-output sectors is used to examine the relationship between labour productivity and innovation expenditures in the German economy during the period 1980 to 1986. The productivity measures used, dubbed Harrod-Robinson-Read (HRR), take into account the direct and indirect labour used in each consumption goods sector. Included in these measures is the labour content of new capital investment.

The HRR measures show higher rates of productivity growth in most sectors, compared to the simple direct labour requirements measures. This is due to the fact that the HRR measures take into account the increased efficiency with which new capital is produced. The second part of the study examines the relationship between labour productivity and innovation expenditures as measured by the IFO (Institute for Economic Research – Munich) innovation survey. Using cross section data for 58 German industries, a strong correlation was found between direct labour productivity growth and direct innovation expenditure.

These results suggest that with more detailed capital expenditure data it should be possible to describe more precisely the relationships between innovation activity, spending on new capital, and productivity changes. The key to examining these relationships in more detail is the growing wealth of information contained in recent innovation surveys such as those done by the IFO.     

Distinguishing Between the Effects of Primary and Post-primary Education on Economic Growth

The paper follows Benhabib and Spiegel (Journal of Monetary Economics, Vol. 34, 1994:143–73) in examining the effect of human capital accumulation on economic growth. The paper is innovative in two ways. First, it takes the R&D‐based models more seriously. This delivers more structural specifications in which human capital affects growth as an input of final output and as a catalyst of technological innovation and imitation. Second, owing to data availability it is possible to disaggregate human capital and assign different roles to primary and post‐primary education. Regression estimates obtained from these alternative specifications suggest that the relative contribution of human capital to technology adoption and final output production vary by country wealth. More importantly, regression estimates suggest that primary education contributes mainly to production of final output, whereas post‐primary education contributes mainly to innovation and imitation of technology.