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Regional innovation performance: Evidence from domestic patenting in China
Xibao Li
Research Center for Technological Innovation; Key Research Base in Humanities and Social Sciences, Ministry of Education; School of Economics and Management, Tsinghua University, Beijing, China
Abstract
This paper empirically studies the determinants of domestic patenting at a regional level in China. Applying a stochastic frontier approach to a panel of data published by China government for 30 provinces from 1998 to 2004, I explore the relationship between domestic patent grants and variables associated with R&D inputs and time-varying nuanced factors.
Results imply that region-specific factors affect the efficiency in the production of three types of patents (namely, invention, utility model, design) quite differently. Industrial structure is one influential factor which determines the efficiency levels of all three types of patenting. High technology industries are not as efficient and innovative as expected.
Although the role of educational institution and government support is important in patenting inventions and utility models, it is not significant in patenting designs. Firms' commitment in innovation helps promote the efficiency in patenting utility models and designs only. It does not significantly affect the efficiency in patenting inventions.
It is found that the estimated mean efficiency level is higher in the case of utility model patenting than in other two cases, while the production of design patents is found the most inefficient. Ranking regions by an order of estimated mean efficiency levels, I find that a pattern of center-periphery in innovation efficiency is only observed in the case of invention and utility model patenting, not in the case of design patenting.
Keywords
patent, Regional Innovation System, Regional Innovation Capacity, innovation efficiency, idea production function, Stochastic Frontier Model
Article Text
It is a stylized fact that different innovation systems have quite different ability to innovate at the global technology frontier. The efficiency or productivity is heterogeneous among innovation systems. In spite of the fact that much attention has been paid to identify sources of these differences and roles of innovative settings in innovation literature (Nelson 1993; Niosi 2002; Freeman 2002) only few studies empirically explored these issues. One recent work by Furman et al (2002) put forth a novel framework and empirically examined the relationship between innovation intensity and variables associated with national innovation systems. Drawing upon Romer's endogenous growth theory (Romer 1990), Porter's theory of industrial competitive advantage (Porter 1990) and theory of national innovation system (Nelson 1993), this approach incorporates both economy-wide input factors and environment related nuanced factors. Differences in innovation performance are attributed to differences in national innovation capacity, which in turn depends on the level of a nation's common innovation infrastructure, the environment for innovation and the linkage between these two.
Based on a similar framework, this paper extends Furman et al 'study in three aspects. First, it extends the concept of national innovation capacity to regional levels. As some researchers pointed out (for example, Cooke et al 1997; Tödtling & Kaufmann 1999b; Doloreux 2002), innovation systems have a regional dimension. It is reasonable to argue that the concept of innovation capacity can be extended to regional innovation systems. The difference in innovation intensity varies not only across countries, but also across sub-national regions, like states or provinces (Evangelista et al 2001; Acs et al 2002; Fritsch 2002) It is interesting to see how differences in innovation performance across regions can be attributed to differences in regional innovation capacity. However, previous exploration of the regional comparison is mainly based on case studies (See, for example, Asheim & Isaksen 1996; Héraud 2003; Asheim & Coenen 2005) The purpose of this research is to compare regional productivity based on evidences from an econometric perspective.
Secondly, this paper investigates the regional differences in China. China is not only a less developed country (LDC), but also one of transformation economies such as Central and Eastern Europe and one of Asian Developing Countries as well. Many researchers have noticed that innovation systems in developing or transitional countries are quite different from those in developed countries (Nelson 1993; Liu & White 2001; Radosevic 2002) In most LDCs and transformation economies, there exist serious inequalities in both economic development and innovation capacity across regions. For example, among 30 provinces in China, in terms of domestic patenting, five developed provinces (Guangdong, Shanghai, Zhejiang, JiangSu and Shandong) accounted for 53% of total patent grants in 2003. Fifteen regions below the median level accounted for less than 11% in total. Taking into consideration the peculiar characteristics of these economies properly and using a panel data on domestic patenting, this research will present empirical evidences in China.
Thirdly, this analysis takes a different approach methodologically. In their work, Furman et al (2002) used ordinary linear regressions to explore the relationship between international patents, which are taken to reflect the innovation intensity, and R&D inputs and other nuanced factors. With knowledge production function approach, Fritsch (2002) compared the quality of regional innovation systems based on negative binomial estimations. However, both studies shed little light on the separate effects of input factors and efficiency factors. Using domestic patenting information, I assume that input factors determine the production frontier of patents, and nuanced factors affect the efficiency in patent production. Thus, the effect and the role of various factors should be identified separately. In this sense, innovation systems are regarded as 'X-efficient' (Niosi 2002) Their level of efficiency is variable depending on some region-specific and time-varying variables (Fritsch 2002) Drawing on literature in productivity and efficiency studies, I use a stochastic frontier model in this study. This paper is organized as follows. Section 2 briefly introduces the theoretical literature on regional innovation system, and describes the unit of analysis. Section 3 discusses the theory of idea production function and a stochastic frontier model. Data are summarized in Section 4. In Section 5, findings and results are discussed in details. Finally, Section 6 concludes.
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