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Does Government Research And Development Funding Promote Innovation Efficiency Of Enterprises?

Posted on:2019-12-10Degree:MasterType:Thesis
Country:ChinaCandidate:D P WangFull Text:PDF
GTID:2429330545955385Subject:Financial
Abstract/Summary:PDF Full Text Request
Currently,innovation has become an important driving force for the industrial trans-formation and upgrading in China and has become the key factor of the economic gro-wth.However,the externalities of innovation activities lead to market failure,making the enterprise's own innovation expenditure often below the social optimal level.Thus,it becomes a top priority for the government to develop effective innovation incentive policies that can effectively promote independent innovation capability in China.How to evaluate the innovation efficiency of Chinese enterprises scientifically and objectively?Do government R&D funding to promote the efficiency of China's business innovation enhance it?These issues have become the focus of the hot and controversial issues in the current innovation economics research.Many papers have explored this issue in depth,such as Bai and Li(2011),Xiao and Lin(2014),Maietta(2015),Zhang et al.(2017)and Carboni(2017).Different from these literatures,this paper empirically analyzes the relationship between government R&D funding and the innovation efficiency of Chinese enterprises based on conditional non-parametric frontier analysis models,which not only effectively avoids the risk of function rnis-setting but also does not suffer from the separation condition.Based on the analysis of the research results,this paper draws the following conclu-sions:First,the innovation efficiency of large and medium-sized industrial enterprises in China's provinces is generally low,but the average efficiency has been increasing over time,and the efficiency distribution has been continuously approaching 1 over time.Second,the innovation efficiencies of enterprises of different seales have different characteristics.First,the average efficiency of innovation in large companies is higher than that of medium-sized companies.Second,the average efficiency of innovation in large and medium-sized industrial companies has continued to increase over time.However,after considering government R&D funding and time in the efficiency evalu-ation,it was found that the innovation efficiency of large-scale industrial enterprises continued to improve,while the innovation efficiency of medium-sized industrial enter-prises did not improve significantly.It shows that the improvement of the innovation capability of large-scale industrial enterprises not only comes from the improvement of the external environment,but also from the improvement of their own efficiency,but the improvement of the innovation capability of the medium-sized industrial enterprises mainly comes from the improvement of the external environment.Third,different provinces have large differences in their innovation efficiencies and different driving forces.Some provinces have higher innovation efficiency due to the higher innovation efficiency of large-scale industrial enterprises,while some provin-ces are driven by higher innovation efficiency of medium-sized enterprises,and some provinces have higher efficiency in innovation of two scales.Fourth,government R&D funding will not only increase the frontiers of innovation production in large and medium-sized industrial enterprises in China's provinces,but also promote its efficiency distribution closer to one another.Through further non-parametric regression of conditional efficiency,it is found that there is a non-linear relationship between government R&D funding and innovation efficiency of China's provincial large-and medium-sized industrial enterprises.When the level of govern-ment funding is low,government R&D funding has a slight inhibitory effect on inno-vation efficiency,and when the level of funding is high,government R&D funding can significantly promote innovation efficiency.
Keywords/Search Tags:Innovation Efficiency, Government Grant, Nonparametric Approach
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