中国工业企业的自主创新能力及其绩效研究
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| Title | An Evaluation of the Efficiency of Chinese Industry Enterprises’ Innovation Performance
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| 作者 | 周亚虹 贺小丹 沈瑶 |
| Author | Yahong Zhou Xiaodan He and Yao Shen |
| 作者单位 | 上海财经大学，上海财经大学，上海大学 |
| Organization | Shanghai University of Finance and Economics, Shanghai University of Finance and Economics, Shanghai University |
| 作者Email | yahong.zhou@mail.shufe.edu.cn |
| 中文关键词 | 自主创新 研发投入 Cobb-Douglas生产函数 工具变量 Chamberlain随机效应 |
| Key Words | Innovation, R&D, Cobb-Douglas production function, IV regression, Chamberlain’s random effect approach. |
| 内容提要 | 后金融危机时代，中国经济发展模式面临转型的瓶颈，而当前中国企业要想在国际竞争中求得生存和发展，自主创新是关键。本文主要围绕我国企业自主创新绩效进行分析。关于企业自主创新的讨论在现有文献中并不少见，但仍存在诸多不足之处：例如，研发活动的累积效应没有得到应有的重视；忽略了企业研发活动的自主选择（self-selection）问题，进而未对由此导致的模型估计内生性问题做出相应的处理等。本文提出了较为全面的研究思路来克服这些不足：在使用Cobb-Douglas生产函数作为企业绩效研究的基本方程的同时，将R&D活动理解为企业技术水平的累积；然后着重讨论研发自选性，通过对企业研发行为决策进行建模分析找出合适的工具变量，从而避免了参数估计值的不一致性。本文实证部分使用了中国2005—2007年度近3万家产值在500万以上的工业企业数据，研究表明：研发促进了技术的累积，从而提高了企业的生产率，其投入产出弹性达到5.5%（详见实证部分），修正了常规方法偏低的估计值。 |
| Abstract | In this Post-Crisis era, China’s economy is now facing a big challenge. With the change of the global economic environment, it is a critical period now for China’s economic transition. This situation strongly requires Chinese industry enterprise’s innovation. And only in this way, China’s enterprises could survive in international competition. In this paper we will discuss the performances of innovation of China’s enterprises. As we know that this is a hot research topic in recent years, and there are a lot of relevant literatures, both in foreign and domestic journals, on the R&D performances. However, there are still some main drawbacks in these literatures. For example, self-selection in the firm’s R&D inputs is seldom discussed, and R&D’s cumulative effect on production has not been emphasized. These drawbacks motivate us to propose more appropriate way to evaluate the efficiency of the innovation performance. In the theoretical part of this paper, we establish models of firms’ innovation determination and production function. To avoid possible model misspecification, we adopt Chamberlain’s random effect approach to estimate the binary probit choice model which determines whether an enterprise engages in R&D activity , and then use the probit fitted value as the IV of R&D input in the linear regression of production function. By using a dataset containing more that 30000 firms in different economic sectors in China from year 2005 to 2007, our empirical result shows that the elasticity of R&D on the added value is 5.5%, which implies that traditional approach underestimated the efficiency of R&D input for the China’s industrial enterprises. |
| 文章编号 | WP199 |
| 登载时间 | 2012-01-13 |
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