Abstract：Drawing on 3500 China's A-share listed companies from 2008 to 2017,this paper compares non-high-tech enterprises and high-tech enterprises to examine the effect of high-tech enterprise certification on R&D input based on propensity score matching.The results indicate that Recognition of high-tech enterprises of the parent company or subsidiaries has a significant and positive influence on R&D input;Compared with the recognition policy published in 2008,the high-tech enterprises identified by the recognition policy published in 2016 have the less incentive effect of R&D investment but the greater incentive effect of R&D manpower input;High-tech enterprises incline to self-select in increasing R&D input to gain the certification and not significantly adding R&D manpower input after the end of high-tech enterprise certification,and high-tech enterprises become more innovative during the period of certification;Both parent and subsidiary companies in the current period have the high probability to have the same status as the previous period.The results mean that the high-tech enterprise certification policy is an effective institutional arrangement,but government should improve the identification policy in terms of stimulating enterprises to continuously carry out scientific and technological innovation to build an innovative country and a global scientific power.
[1]SOLOW R M.A contribution to the theory of economic growth[J].The quarterly journal of economics,1956,70(1):65-94.
[2]朱平芳,项歌德,王永水.中国工业行业间 R&D 溢出效应研究[J].经济研究,2016(11):5.
[3]TAKALO T,TANAYAMA T,TOIVANEN O.Welfare effects of R&D support policies[C].Bank of finland research discussion paper,2017.
[4]LACOVá ?,HUNADY J.The consequences of tax base rules on enterprise innovation in the european Union//DIAS A,SALMELIN B,PEREIRA D,et al.Modeling innovation sustainability and technologies.Cham:Springer,2018:19-31.
[5]ASSEY P.Environment at the heart of Tanzania′s development:lessons from Tanzania′s national strategy for growth and reduction of poverty,MKUKUTA[M].London:International Institute for Environment and Development,2007.
[6]IENTILE D,MAIRESSE J.A policy to boost R&D:Does the R&D tax credit work[J].EIB papers,2009,14(1):144-169.
[7]CAPPELENÅ,RAKNERUD A,RYBALKA M.The effects of R&D tax credits on patenting and innovations[J].Research policy,2012,41(2):334-345.
[8]胡凯,吴清.R&D 税收激励,知识产权保护与企业的专利产出[J].财经研究,2018,44(4):102-115.
[9]马玉琪,扈瑞鹏,赵彦云.财税激励政策对高新技术企业研发投入影响效应分析——基于广义倾向得分法的实证研究[J].中国科技论坛,2017(2):143-149.
[10]许玲玲.高新技术企业认定、政治关联与民营企业技术创新.管理评论,2017,29(9):84-94.
[11]熊维勤.税收和补贴政策对R&D效率和规模的影响——理论与实证研究[J].科学学研究,2011(5):698-706.
[12]郭瑞玮,李瑞芬,夏龙.税收优惠政策对农业科技创新的影响研究——以农业龙头企业上市公司为例[J].中国农学通报,2018,34(8):145-151.
[13]黄洁莉,汤佩,蒋占华.税收优惠政策下农业企业研发投入、风险与收益——基于中国农业上市公司的实证检验[J].农业技术经济,2014(2):120-128.
[14]孔淑红.税收优惠对科技创新促进作用的实证分析——基于省际面板数据的经验分析[J].科技进步与对策,2010,27(24):32-36.
[15]BESHAROV M L,SMITH W K.Multiple institutional logics in organizations:explaining their varied ownership and implications[J].Academy of management review,2014,39(3):364-381.
[16]HECKMAN J J,LALONDE R J,SMITH J A.The economics and econometrics of active labor market programs[J].Handbook of labor economics,1999,3:1865-2097.
[17]ROSENBAUM P R,RUBIN D B.Constructing a control group using multivariate matched sampling methods that incorporate the propensity score[J].The American statistician,1985,39(1):33-38.
[18]CALIENDO M,KOPEINIG S.Some practical guidance for the implementation of propensity score matching[J].Journal of economic surveys,2008,22(1):31-72.
2019, 
