一个新的创新水平衡量指标:R&D投资强度及其衍生测度

财经论丛 ›› 2022, Vol. 38 ›› Issue (11): 21-31.

一个新的创新水平衡量指标:R&D投资强度及其衍生测度

徐蔼婷^1,2, 邱可阳¹, 祝瑜晗^1,2

1.浙江工商大学统计与数学学院,浙江杭州 310018;
2.浙江工商大学统计数据工程技术与应用协同创新中心,浙江杭州 310018

收稿日期:2021-11-22 出版日期:2022-11-10 发布日期:2022-11-22
作者简介:徐蔼婷(1979—),女,浙江慈溪人,浙江工商大学统计与数学学院教授,浙江工商大学统计数据工程技术与应用协同创新中心兼职研究员;邱可阳(1994—),女,浙江温州人,浙江工商大学统计与数学学院博士生;祝瑜晗(1992—),女,浙江兰溪人,浙江工商大学统计与数学学院讲师,浙江工商大学统计数据工程技术与应用协同创新中心兼职助理研究员,通信作者。
基金资助:
浙江省哲学社会科学规划领军人才培育课题(青年英才)(22QNYC14ZD);浙江省“万人计划”青年拔尖人才项目(ZJWR0108041);浙江省重点建设高校优势特色学科(浙江工商大学统计学)资助(21TJ001098);浙江工商大学统计数据工程技术与应用协同创新中心资助(21SE001545)

A New Measurement Indicator of Innovation Level:Ratio of Investment in R&D to GDP and Its Derivative Measurement

XU Aiting^1,2, QIU Keyang¹, ZHU Yuhan^1,2

1. School of Statistics and Mathematics, Zhejiang Gongshang University, Hangzhou 310018, China;
2. Collaborative Innovation Center of Statistical Data Engineering, Technology and Application, Zhejiang Gongshang University, Hangzhou 310018, China

Received:2021-11-22 Online:2022-11-10 Published:2022-11-22

摘要/Abstract

摘要： 为实现“投入”与“产出”双重视角的R&D活动监测,并呼应2008版SNA和2016版CSNA的重大修订和更新,本文提出一个新的创新水平衡量指标——R&D投资强度,继而在厘清其核算基本逻辑及其与R&D投入强度之间内在差异的基础上,对我国的R&D投资强度予以实际测算、动态监测和国际比较。进一步地,运用R&D投资强度及其衍生指标R&D有效投资系数展开全国各省(市)创新表现的定量测度和动态比较。结果显示,改革开放以来,我国R&D投入强度和R&D投资强度的总体趋势“形似而质不同”,两者差距自1995年开始逐步扩大直至2008年形成同步增长态势,而后于2015年呈收缩迹象。基于国际视野,我国的R&D投入强度排名虽不断攀升,但R&D投资强度却远不及大部分OECD国家水平。此外,各省(市)的R&D投资强度增幅明显,但差距依然显著,且R&D有效投资系数均未超过1。综合来看,R&D投资强度的提出有据可依且合乎情理,依托其与R&D投入强度的双重考察,再辅之以两者协同程度的多维度监测,可实现我国创新水平真实脉动的全景式呈现。

关键词: R&D投资强度, R&D投入强度, R&D有效投资系数, 2008版SNA, 创新水平

Abstract: In order to realize R&D activity monitoring from the dual perspectives of “input” and “output”, and echo the major revisions and updates of the 2008 version of the System of National Accounts (SNA) and the 2016 version of China's System of National Accounts (CSNA) on Research and Experimental Development (R&D) capitalization, this paper proposes a new innovation level measurement indicator, ratio of investment in R&D to GDP. On the basis of clarifying its basic accounting logic and its inherent differences with ratio of expenditure on R&D to GDP, this paper makes actual calculation, dynamic monitoring and international comparison of China's ratio of investment in R&D to GDP. Furthermore, this paper uses ratio of investment in R&D to GDP and its derivative index R&D effective investment coefficient to develop a quantitative measurement and make a dynamic comparison of the innovation performance of provinces (cities) across the country. The results show that since the reform and opening up, the overall trends of China's ratio of investment in R&D to GDP and ratio of expenditure on R&D to GDP have been “similar in appearance but substantially different”. The gap between the two began to gradually expand from 1995 until it formed a synchronous growth trend in 2008, and then showed signs of tightening in 2015. Based on an international perspective, although China's ratio of expenditure on R&D to GDP is continuously rising among OECD countries, ratio of investment in R&D to GDP is far below the level of most OECD countries. In addition, ratio of investment in R&D to GDP of China's provinces (cities) has increased significantly, but the gap is still significant, and the R&D effective investment coefficient has not exceeded 1. Overall speaking, the proposal of ratio of investment in R&D to GDP is well-founded and reasonable. Relying on the dual inspection of ratio of expenditure on R&D to GDP and ratio of investment in R&D to GDP, supplemented by multi-dimensional monitoring of the degree of coordination between the two, it is possible to realize the panoramic presentation of the true pulse of China's innovation level.

Key words: Ratio of Investment in R&D to GDP, Ratio of Expenditure on R&D to GDP, R&D Effective Investment Coefficient, 2008 Version of SNA, Innovation Level

中图分类号:

F222.33

徐蔼婷, 邱可阳, 祝瑜晗. 一个新的创新水平衡量指标:R&D投资强度及其衍生测度[J]. 财经论丛, 2022, 38(11): 21-31.

XU Aiting, QIU Keyang, ZHU Yuhan. A New Measurement Indicator of Innovation Level:Ratio of Investment in R&D to GDP and Its Derivative Measurement[J]. Collected Essays on Finance and Economics, 2022, 38(11): 21-31.

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