摘要
本文利用等效益面方法和微观企业数据研究企业的效率问题,推导企业的技术进步贡献率,并选取了纺织业和电子设备制造业为例进行实证研究。结果表明两个行业的企业纯技术效率不高,有相当比例企业的规模效率递减,进而制约企业的综合效率提升。纺织业的技术进步贡献率在行业规模缩减期,在40%的水平上有所上升,在规模扩张期则有所下降;电子设备制造业的技术进步贡献率经历一段30%水平的稳定期后,随着研发投入的增加快速提升;产业集聚未能有效提升企业的技术进步贡献水平,核心因素仍是研发投入。
China’s economy is entering a new stage of strengthening innovation, improving economic efficiency and accelerating transformation and upgrading. One of the main tasks of the economy is to transform the elements and investment driven economic growth to an innovation driven one. The index of contribution rate of technological progress is a direct measurement of how much does innovation contribute to the growth of economy. In this context, the contribution rate of technological progress is widely discussed in government departments and academic field. Because of the importance of this index, there are a large number of researches focusing on the measurement of the contribution rate of technological progress. However, most of them have either theoretical or practical defects. For example, lots of results based on popular measuring methods are not stable, which means the measuring results can vary widely according to the parameters of measuring models. Besides, the calculation of capital investment is difficult, and it effects the result of the contribution rate of technological progress to a large extend. Moreover, those calculation methods based on the production function have problems that the assumptions are difficult to be fully satisfied.In this paper, we do not calculate the contribution rate of technological progress based on the production function, thus avoiding the shortcomings of the production function based methods. We derive the formula of contribution rate of technological progress from DEA method and equal efficiency method. Our method of measuring the contribution rate of technological progress is called the equal efficiency method. The main idea of our method measuring the contribution rate of technological progress is as follows. Firstly, according to the input-output data of enterprises, we apply the DEA method to calculate the maximum output that can be obtained under the existing input of each enterprise. Secondly, the relative benefit of an enterprise is defined as the ratio of the actual output to the maximum possible output, thus we find the equivalent benefit surface of enterprises. If the relative distance between the actual output of the enterprise and its maximum possible output does not change(the ratio of the two is unchanged), the general technical level does not change, otherwise, the technical level is changed. Thirdly, through the bridge of equal benefits, we can separate the contributions brought by the changes in input factors and the contribution of technological progress in the growth of enterprise output, so as to obtain the contribution rate of technological progress of each enterprise to its output growth.In our empirical research, we use the data of China’s Industrial Enterprises above Designated Size from 1999 to 2006. We focus on two industries, which are the textile industry and the communication equipment, computer and other electronic equipment manufacturing industry(electronic equipment manufacturing industry in short). We compare the efficiency of production and the contribution rate of technological progress in these two industries. The comparison is mainly in the perspectives of innovation investment, enterprise registration type and the location of enterprises. At the end of this paper, we put forward some relevant suggestions based on the analysis results.From the perspective of enterprise efficiency, we find that technical efficiency of enterprises in both of the two industries is generally low. Although the scale efficiency is higher, it is accompanied by the diminishing returns to scale. By looking into the index of corporate assets, we find that the scale efficiency of smaller enterprises is higher. This means under the current technical level, the enterprise scale is generally larger than the optimal scale of production, which makes most of the enterprises are in the stage of diminishing returns to scale. A wise strategy is to reduce the size of enterprises and put more effort in improving production efficiency.As for the contribution rate of technological progress, we find that the growth of input factors is the main source of output growth in textile industry, while in electronic equipment manufacturing industry, technical progress plays a more important role. The contribution rate of technological progress in electronic equipment manufacturing industries rises faster. It stays on the level of 30% for several years and then rises rapidly with the increasing of R&D expenditure. The contribution rate of technological progress in the textile industry has an increasing trend on the base level of 40% in the period of scale reduction, while in the period of scale expansion, it falls down.From the perspective of regional differences, we find that the contribution rates of technological progress vary widely among different regions. This regional imbalance feature is more obvious in the textile industry. We also find that the industrial agglomeration does not improve the industries’ contribution rate of technological progress. Regions having a lot of enterprises do not have a higher contribution rate of technological progress. Industry’s contribution rate of technological progress mainly depends on its R&D expenditure. Regions having higher R&D investment tend to have higher contribution rate of technological progress.Based on the above research, we propose the following three suggestions on how to improve the contribution rate of technological progress. Firstly, increasing the R&D investment of enterprises. R&D investment is the core channel of improving the contribution rate of technological progress. In the current situation of low business operating profit margins, it is necessary to have favorable fiscal and taxation policies or better innovation environment and R&D infrastructure to encourage enterprises to increase R&D investment. Secondly, emphasizing industrial agglomeration’s role of increasing technological competition, trying to avoid mutual imitation and homogeneous production, and differentiating the core technology and competitiveness of firms. Last but not least, encouraging innovation requires adherence to market orientation. R&D is a high-risk activity with high uncertainty, and production-related innovation mainly occurs at the enterprise side. Tax reduction and deduction are the direct methods to encourage enterprise innovation. Besides, other innovation environment, such as technology market construction and intellectual property protection, are also crucial to encourage R&D activities. Moreover, we should fully trust and encourage enterprises, allocate innovative resources to the market, and reduce administrative intervention in innovation direction, innovation mode and specific innovation behavior.
作者
叶银丹
甄峰
Ye Yindan;Zhen Feng(Research Institute of Bank of China,Beijing 100818,China;Solvay Business School,Vrije Universiteit Brussel,Brussels 1050,Belgium;Center for Applied Statistics,School of Statistics,Renmin University of China,Beijing 100872,China)
出处
《科研管理》
CSSCI
CSCD
北大核心
2019年第12期105-115,共11页
Science Research Management
基金
国家社会科学基金年度项目:“大数据背景下从科技统计到创新统计的体系构建研究”(项目编号:15BTJ013,起止时间:2015-2020)
中国博士后科学基金第66批面上资助:“金融资源配置对我国创新能力的影响研究”(项目编号:2019M660939,起止时间:2019-2021)
关键词
等效益面
技术进步贡献率
微观数据
equal efficiency surface
contribution rate of technological progress
micro data
作者简介
叶银丹(1989-),女(汉),浙江宁波人,中国银行研究院博士后,布鲁塞尔自由大学博士研究生,研究方向:创新经济,宏观经济、经济统计;通讯作者:甄峰(1979-),男(汉),河北藁城人,中国人民大学应用统计科学研究中心、统计学院副教授,研究方向:创新与竞争力、政府统计。
