依靠创新推动全要素生产率提升是中国寻找经济增长新动力的根本途径，然而近年来却出现了R&D投入快速增长与全要素生产率停滞不前的矛盾现象。本项目拟从中国现实经济问题出发，引入创新激励扭曲与企业创新决策行为分析，构建“创新激励扭曲下R&D资金错配与全要素生产率损失”的理论框架，探究R&D错配的原因与全要素生产率损失的形成机理，弥补现有研究聚焦于资本与劳动等传统要素错配，缺乏对R&D资金错配效应分析以及对中国经济问题刻画的不足。在生产率估计与分解的基础上，检验不同政策工具、特征与类型的创新激励政策对R&D配置与全要素生产率的异质性影响，试图识别创新激励政策有效的条件。通过反事实分析，构建单因素直接测算与综合因素间接测算法，模拟R&D资金错配与全要素生产率损失的程度。综合运用理论分析、实证检验与定量测算的结果，为提高我国R&D配置效率与全要素生产率的创新激励政策优化设计与管理提供理论依据与决策支持。

China has to rely on innovation-driven productivity improvements to sustain economic growth. However, the dramatic growth of China’s R&D expenditures is actually associated with poor productivity performance in recent years. This project aims to construct a unified theoretical framework to understand aggregate productivity losses from R&D misallocations. The framework will accommodate the analysis of distortions on innovation incentives and firm innovation decisions, which enables us to explore the causes of R&D misallocations and productivity losses. Since the existing studies mainly focus on capital and labour misallocations, the project contributes to the literature by investigating R&D misallocations and characterizing some stylized facts from China. Combined with productivity estimation and decompositions, we will evaluate the effectiveness of innovation polies on R&D allocation and productivity, varying across different instruments, types and features of innovation policies. Based on counterfactual analyses, we will propose direct and indirect quantitative framework to measure R&D misallocations and aggregate productivity losses. Combined with the theoretical analyses, empirical investigations and measured results, the project will provide implications to more efficient design and management of innovation policies, which in turn help to improve R&D allocation efficiency and productivity growth.