研发税收政策组合对R&D活动影响的空间计量分析
寇明婷1，程敏1，崔文娟1，陈凯华2,3
（1.北京科技大学 经济管理学院，北京100083；
2.中国科学院 科技战略咨询研究院，北京100190；
3.中国科学院大学 公共政策与管理学院，北京100190）
摘要：本文基于我国30个省级行政区域2009—2015年大中型工业企业数据，借助空间计量经济学方法揭示了研发税收政策和研发活动的空间相关性，在此基础上将空间计量模型引入知识生产函数中分析研发税收政策组合对研发活动的影响。研究发现：研发税收政策和研发活动均存在正向空间相关性；考虑空间关联后，两种研发税收政策对研发投入及产出均表现出显著的促进作用，但相对未考虑空间关联时的作用明显减弱；当两类政策同时作用于研发活动时，其组合效果较单一政策明显减弱，即两类政策互相干扰；研发活动存在显著正向空间溢出效应，直接税收优惠政策对研发投入具有显著的正向空间溢出效应。研究揭示了不同研发阶段中研发税收政策及其组合与研发活动的空间关联效果，为促进区域创新政策的制定提供参考。
关键词：研发税收政策组合；空间杜宾模型；研发投入与产出；区域创新
主要研究结论：本文基于我国省级行政区域层面工业企业数据，借助空间计量经济学方法，从空间关联角度衡量研发税收政策组合对研发活动的激励效果。研究发现：
（1）空间相关性层面，研发活动与研发税收政策均表现出正向空间相关性，空间集聚现象明显，且多集中在经济较为发达的东部地区。市场作用下雄厚的经济基础对各类创新资源的吸引使得各地区在创新活力及创新政策受益程度方面存在明显的地域差异，强-强、弱-弱的“抱团”现象明显，若不积极干预，可能会进一步导致地域差异的加剧。
（2）空间溢出层面，研发活动表现出正向空间溢出效应；直接税收优惠政策对研发投入存在显著的正向空间溢出效应，即本地区的直接税收优惠政策会促进相邻地区研发投入的增加。知识的外溢性特点及地区间的借鉴行为使得溢出效应对于相邻地区的研发活动存在激励作用，这表明可以利用示范效应缩小地区间创新水平的差距。
（3）单一政策层面，未考虑空间关联时两种政策对研发投入和产出均表现出显著的促进作用。考虑空间关联后两种政策依然表现出显著的促进作用，但其对研发活动的效果有所减弱，可见忽略空间关联的实证结果对本地政策效果的估计是偏大的。比较考虑空间关联前后的政策效果，进一步验证了溢出效应在促进研发活动过程中的积极作用，为避免评估结果的有偏，在区域层面创新政策效果的评估中需纳入对相邻地区政策溢出影响的考量。
（4）政策组合层面，无论是否考虑空间关联，两种政策对研发活动的影响效果较单一政策时均明显减弱，这表明两种政策同时实施时会削弱彼此的激励效果，即政府在实施政策帮扶时未能达到“1+1>2”的效果。可能的原因是随着我国企业创新政策体系的不断丰富，其跨部门、多领域、多层次等复杂性日益凸显，容易产生政策间相互掣肘的矛盾。因此，迫切需要围绕政策复杂性与协同性的适应演化，从政策的协调性、连贯性、适应性等生态系统属性角度研究企业创新政策理论、实践与优化。
The space econometric analysis of the impact of R&D tax policy mix on R&D activities
Kou Mingting1, Cheng Min1, Cui Wenjuan1, Chen Kaihua2,3
(1. School of Economics and Management, University of Science and Technology Beijing, Beijing 100083, China;
2. Institutes of Science and Development, Chinese Academy of Sciences, Beijing 100190, China;
3. School of Public Policy and Management, University of Chinese Academy of Sciences, Beijing 100190, China)
Abstract:Since the implementation of the innovation-driven development strategy, China has increased support for technological innovation year by year, and successively introduced various policies such as direct subsidies, pre-tax additional deduction policy and preferential tax rates for high-tech enterprises. In this context, the consistency and sustainability of policies issued under different time and backgrounds should be considered. Previous studies have examined the effect of R&D policies on R&D activities based on samples at the company, regional, or industry level. Although some literatures have introduced spatial correlation into the research of R&D policies or R&D activities, few studies consider the spatial correlation of R&D policies and R&D activities at the same time. The first law of geography indicates that geographically adjacent units tend to have stronger correlation. Researchers have pointed out that China′s government R&D subsidies have a significant positive dependence. Correspondingly, the unbalanced distribution of regional R&D activities in China has continued to exist in recent years. It can be seen that the phenomenon of the first law of geography also exists in the process of R&D policies supporting R&D activities. If each region is regarded as an independent unit and the spatial correlation between regions is ignored, it is easy to produce bias in the estimation of the true effects of R&D policies. Therefore, it is urgent to accurately capture the incentive effect of R&D policies in the innovation process from the perspective of spatial correlation and explore the spatial interaction of R&D policies and R&D activities. To this end, what is the spatial impact of a single policy after considering the spatial correlation? Do the policies of a region have spatial spillover effect on the neighboring region′s R&D activities? What is the impact of policy mix when a company benefits from multiple policies at the same time?
On this basis, using the data of large and medium-sized industrial enterprises in 30 provincial-level regions in China from 2009 to 2015, this paper employed the spatial econometric methods to reveal the spatial correlation of R&D tax policies and R&D activities. This article analyzed the impact of R&D tax policy mix on R&D activities by introducing spatial econometric models to the knowledge production function. The study delivers the following results: (1) There is a strong spatial-autocorrelation in R&D tax policies or R&D activities; (2) Both R&D tax policies have significant positive effects on the R&D input or output after considering the spatial relevance. However, the impacts are significantly weakened compared with the research without considering spatial correlation; (3) From the perspective of policy mix, when the impact of two tax policies on R&D activities is considered simultaneously, its impact and significance are weakened compared with the research only considering a single tax policy; (4) From the perspective of spatial spillover effects, R&D activities have significant positive spatial spillover effects. Meanwhile, direct tax credits have significant positive spatial spillover effects on R&D input.
Relevant research results not only shed new insights on how geography matters in the process of R&D tax policy supporting R&D activities, but also provide in-depth understanding on the influence of different R&D tax policies at different stages of R&D process. The results of the paper can provide a useful reference for policy making to design effective policy mix, thereby enhancing policy efficiency and China regional innovation capabilities.
Key words:R&D tax policy mix; Spatial Durbin Model; R&D input and output; regional innovation
引用本文：寇明婷,程敏,崔文娟,等.研发税收政策组合对R&D活动影响的空间计量分析[J].科研管理,2023,44(06):29-39.
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