创新驱动发展的财政金融激励机制研究——基于产业风险与信息特性的视角

The innovation-driven development strategy is the core of maintaining stable economic growth under the “New Normal Economy”, as investment-driven development is not sustainable any more. The key is to develop a fiscal and financial support incentive mechanism which matches its innovation characteristics: fiscal support can serve better for innovations with lower risk and stronger externalities; while for innovation with higher risk and higher returns, market financing seems to be more effective. However, projects with strong externalities, which are significant to innovation-driven development, usually characterized with higher risks, thus a matching fiscal or financial support is essential. Under the framework of fiscal and financial support policy, this project aims to (1) explore the optimal matching of fiscal support and market financing under circumstances of various industrial risk and information structures based on game theory and theory of industrial organization, thus providing a micro-perspective for the “optimal fiscal and financial matching” of innovation-driven development; (2) discuss the internal mechanism of the inefficiency of innovative PPP and other social financing projects caused by incomplete contract based on the industrial risk and information characteristics, in order to make it feasible; (3) evaluate the performance of fiscal and financial support in promoting innovation development in different of stages, fields and regions using Stochastic Frontier Analysis (SFA) and other methodologies. Furthermore, the proposed project is expected to provide scientific and reasonable policy suggestions for developing a fiscal and financial incentive mechanism of innovation-driven development in China.

投资驱动经济动力不足，创新驱动发展格局尚未确立，形成与创新特性相匹配的财政金融激励机制是推动实现创新发展战略的关键。初步研究表明，对于风险较低外部性较强的创新与产业升级，财政支持往往更为有力；对于高风险高收益的创新，市场融资通常更为有效。然而，对创新驱动发展尤为重要的高外部性项目却往往具有高风险，寻求与之匹配的财政金融支持至关重要。本项目在统一考察财政金融支持政策的框架下：（1）运用博弈论和产业组织理论，考察不同产业风险与信息结构下财政支持与市场融资的最优匹配，为创新驱动的“最优财政金融匹配”提供微观理论基础；（2）基于产业风险与信息特性，探讨由契约的不完全性导致创新型PPP等项目社会融资效率不高的内在机制以及促进其发展的有效措施；（3）运用随机前沿分析等方法，量化评估财政金融促进创新驱动发展的阶段效应、行业效应和区域效应。为构建与创新特性相匹配的激励机制提出科学合理的政策建议。

创新是推动高质量发展、支撑构建新发展格局的根本动力，形成与创新要素相匹配的财政金融激励机制是促进创新、保护创新的关键。在当前数字经济背景下，人工智能、大数据、区块链等数字技术正加速赋能传统产业升级，催生新产业新业态新模式，成为新一轮产业变革的重大历史机遇。然而，数字技术的双面性也衍生了更具隐蔽性、传染性的产业风险，产业发展面临传统经济和数字经济新旧问题叠加的压力。本项目立足我国产业发展阶段和制度环境，尤其结合当前数字经济背景下创新活动的风险特性、信息结构特征，运用前沿的理论分析工具和实证研究方法，系统考察了产业创新与财政金融支持的最优匹配机制、PPP（政府与社会资本合作）项目融资效率不足的成因与对策、数字经济创新的监管和治理等问题。为突破数字经济创新的资金瓶颈问题，更好地发挥财政与金融支持对数字经济创新的支持和引领作用，本项目提出三方面的政策建议：第一，不同发展阶段下的产业结构不同，与之相匹配的最优金融结构也是不同的。要从根本上缓解中小企业的融资约束，关键在于改善银行业结构，发挥中小银行善于甄别软信息的比较优势。同时，大力发展数字供应链金融，利用区块链的技术优势，增强产业链的信息传递和信用穿透功能，助力我国产业链固链强链并走向世界前沿。第二，地方政府政策的“时间一致性”是创新型PPP项目有效得到财政和社会资本支持的必要前提。地方政府应合理界定自身权力边界，减少政策的“时间不一致性”，提高社会资本的进入激励，从而充分发挥PPP融资模式缓解地方财政压力、保障公共品供给的重要作用。第三，数字经济创新风险对行业监管和社会治理提出了更高要求，沙盒监管具备有效的风险补偿和筛选机制，能够对创新项目实现选优逐劣，有望成为数字经济创新的全新治理工具。