|
|
|
| Are Factor Allocation Distortions Hindering Breakthroughs in Key Technologies of Chinese Enterprises |
| Xing Jialong,Wu Fuxiang |
| (School of Economics,Nanjing University, Nanjing 210093, China) |
|
|
|
|
Abstract China is lagging behind the developed countries in the fields of lithography, high-end chips and other key technologies, and the developed countries keep the stranglehold of trade embargoes and protectionism. Although Chinese enterprises have been strengthening factor investment in recent years to improve their independent innovation capability, the continuous growth of factor investment has not brought breakthroughs in key technologies due to the factor allocation distortions. With the distorted factor allocation, the optimal allocation of capital and labor cannot be achieved, thus inhibiting the R&D investment, innovation output and innovation efficiency of enterprises, and even the breakthroughs in key core technologies of enterprises. It can be seen that factor allocation distortion has become an important factor affecting the breakthroughs in key technologies of enterprises. Therefore, it is important to examine the impact of factor allocation distortion on the breakthroughs of key technologies of enterprises from the perspective of factor allocation to accelerate the implementation of innovation-driven development strategy and achieve key technology breakthroughs.#br#This paper constructs a mathematical model to explain the theoretical mechanism of factor allocation distortion affecting the breakthroughs in key technologies of enterprises, and measures their breakthrough ability of key technologies from the perspective of technology catch-up. On this basis, the financial data, patent application data and patent citation data of listed companies from the China Research Data Services Platform (CNRDS) and the China Stock Market & Accounting Research Database (CSMAR) are combined by year and with the stock codes of listed companies, the paper finally obtains the panel data of 946 Chinese listed companies from 2001 to 2020. Thus the effects of factor allocation distortions on key technology breakthroughs are robustly examined by using the panel FE and IV-2SLS methods. The heterogeneity of factor allocation distortions affecting enterprise key technology breakthroughs is further examined by introducing the cross-multiplication terms between factor allocation distortions and firm location, firm size and ownership.#br#The results show that, firstly, there are allocation distortions in both capital and labor factors in China, with capital allocation distortions showing an upward trend and labor allocation distortions showing a downward trend. Secondly, in recent years, the overall ability of Chinese enterprises to break through key technologies has been on the rise, but there is a large gap in the innovation ability of most enterprises to achieve key technology breakthroughs, and only a very small number of industry-leading enterprises have the ability to achieve breakthroughs in key technologies. Thirdly, both capital and labor allocation distortions have a significant inhibitory effect on enterprise breakthroughs in key technologies. After dealing with the endogeneity problem and robustness tests, the conclusions still hold. Finally, the inhibitory effect of capital allocation distortion is stronger for the enterprises in western regions than the enterprises in the east, for small, medium, and micro enterprises than large enterprises, and for state-owned enterprises than non-state-owned enterprises in the Hu line. The inhibitory effect of labor allocation distortions is stronger for enterprises on the east side of the Hu line than on the west side, and stronger for large enterprises than for small, medium, and micro enterprises, with no significant difference between state-owned enterprises and non-state-owned enterprises.#br#From the perspective of factor allocation distortion, this paper elucidates the mechanism of factor allocation distortion affecting the breakthroughs of key technologies of enterprises from both mathematical model and mechanism analysis; meanwhile, by constructing the key technology breakthrough capability indicators, this paper measures and evaluates the current capability of Chinese enterprises. Thus, it reveals the important role of industry-leading enterprises in key technology breakthroughs and deepens the understanding of the current situation of key technology breakthroughs of Chinese enterprises. In addition, this paper empirically examines the direction and extent of the impact of capital and labor allocation distortions on enterprise breakthroughs in key technologies using the methods such as FE and IV-2SLS, and analyzes the heterogeneity of firm location, firm size, and nature of firm ownership, providing an empirical supplement to the existing theoretical studies on the breakthroughs of key technologies of enterprises.#br#
|
|
Received: 10 October 2022
|
|
|
|
|
|
[1] 汤志伟,李昱璇,张龙鹏.中美贸易摩擦背景下“卡脖子”技术识别方法与突破路径——以电子信息产业为例[J].科技进步与对策,2021,38(1):1-9.
[2] 袁野,汪书悦,陶于祥.人工智能关键核心技术创新能力测度体系构建:基于创新生态系统视角[J].科技进步与对策,2021,38(18):84-93.
[3] 张杰,周晓艳,李勇.要素市场扭曲抑制了中国企业R&D[J].经济研究,2011,46(8):78-91.
[4] 蒲艳萍,顾冉.劳动力工资扭曲如何影响企业创新[J].中国工业经济,2019,36(7):137-154.
[5] 戴魁早,刘友金.要素市场扭曲与创新效率——对中国高技术产业发展的经验分析[J].经济研究,2016,51(7):72-86.
[6] 韩凤芹,史卫,陈亚平.以大战略观统领关键核心技术攻关[J].宏观经济研究,2021,16(3):111-119,159.
[7] ARDITO L,MESSENI PETRUZZELLI A,PANNIELLO U.Unveiling the breakthrough potential of established technologies:an empirical investigation in the aerospace industry[J].Technology Analysis & Strategic Management,2016,28(8):916-934.
[8] KAMURIWO D S,BADEN-FULLER C,ZHANG J.Knowledge development approaches and breakthrough innovations in technology-based new firms[J].Journal of Product Innovation Management,2017,34(4):492-508.
[9] 张杰.中国关键核心技术创新的特征、阻碍和突破[J].江苏行政学院学报,2019,19(2):43-52.
[10] 庄子银,贾红静,肖春唤.突破性创新研究进展[J].经济学动态,2020,18(9):145-160.
[11] 张杰,吴书凤.“十四五”时期中国关键核心技术创新的障碍与突破路径分析[J].人文杂志,2021(1):9-19.
[12] HSIEH C-T,KLENOW P J.Misallocation and manufacturing TFP in China and India[J].The Quarterly Journal of Economics,2009,124(4):1403-1448.
[13] 陈永伟,胡伟民.价格扭曲、要素错配和效率损失:理论和应用[J].经济学(季刊),2011,10(4):1401-1422.
[14] 蔡旺春,吴福象,刘琦.研发补贴与中国高技术细分行业出口竞争力比较分析[J].产业经济研究,2018,17(6):1-9.
[15] 李平,季永宝.要素价格扭曲是否抑制了我国自主创新[J].世界经济研究,2014,33(1):10-15,87.
[16] KIM J,LEE C Y,CHO Y.Technological diversification,core-technology competence,and firm growth[J].Research Policy,2016,45(1):113-124.
[17] 徐娟.技术多元化、核心技术能力与企业绩效——来自新能源汽车行业上市公司的面板数据[J].经济管理,2016,38(12):74-88.
[18] 王文,牛泽东.资源错配对中国工业全要素生产率的多维影响研究[J].数量经济技术经济研究,2019,36(3):20-37.
[19] 张军,吴桂英,张吉鹏.中国省际物质资本存量估算:1952-2000[J].经济研究,2004,39(10):35-44.
[20] 文东伟.资源错配、全要素生产率与中国制造业的增长潜力[J].经济学(季刊),2019,18(2):617-638.
[21] 陈翼然,李贻东,靳来群,等.我国要素配置优化的着力点在哪——基于多维度要素配置扭曲程度的比较分析[J].管理评论,2022,34(2):62-75.
[22] 乔晓楠,何自力,王奕.防止资本无序扩张的政治经济学分析[J].南开经济研究,2022,38(5):17-37.
[23] 韦朕韬,张腾.高铁开通、资源错配与我国工业产能过剩[J].经济经纬,2021,38(5):80-90.
[24] 孙忠娟,范合君,李纪珍.何种创新政策更有效——基于企业规模的异质性分析[J].经济管理,2022,44(2):73-87.
[25] LEWBEL A.Constructing instruments for regressions with measurement error when no additional data are available,with an application to patents and R&D[J].Econometrica,1997,65(5):1201-1213.
[26] 高翔,刘啟仁,黄建忠.要素市场扭曲与中国企业出口国内附加值率:事实与机制[J].世界经济,2018,41(10):26-50.
[27] 孙圣民,陈强.家庭联产承包责任制与中国农业增长的再考察——来自面板工具变量法的证据[J].经济学(季刊),2017,16(2):815-832.
[28] HALL B H,JAFFE A,TRAJTENBERG M.Market value and patent citations[J].The RAND Journal of Economics,2005,36(1):16-38.
[29] GREENE W H.On the asymptotic bias of the ordinary least squares estimator of the Tobit model[J].Econometrica:Journal of the Econometric Society,1981,49(2):505-513.
|
|
|
|
