1、1How Much Venture Capital Affects Enterprises Innovation in China？Abstract. Venture capital has positive affection to enterprises innovation in developed countries and its precondition is their social， economic system. Whether the rule can be fit for manufacturing industry and information one in Chi
2、na and Chinese whole economy， a developing country， is a very important proposition. The paper made a try for the problem based on micro-data of 230 listed companies in China Growth Enterprise Market. At last， it was found that venture capital also has a positive affection to enterprise innovation i
3、n manufacturing industry and information one in China and Chinese whole economy. At the same time， the paper gave the quantitative analysis on the rule. Key words： Venture Capital， enterprises innovation， different industry 1 Introduction Scholars had analyzed the relationship between venture capita
4、l and technological innovation standing on the view of nation， industry， enterprise and so on. On the view of 2nations， Tykvova used German data from 1991-1997 to analyze the relationship and found that double venture capital could lead to 12% growth rate for patents whole society applied and double
5、 enterprises with venture capital supporting could lead to 21% growth rate 1. It meant that there was a positive correlation between them. On the view of industries， according to survey data， Chemmanur， Krishnan & Nandy studied manufacturing companies supported by venture capital and found it was tr
6、ue that comparing companies without venture capital supports， the former had a higher total factor productivity when venture capital had invested them at first and kept a better higher total factor productivity after that 2. On the view of enterprises， Hellman & Puri found that in 173 high technolog
7、y companies in Silicon Valley those with venture capital had more innovation strategies than ones without venture capital 3. How did scholars explain the phenomenon？ They analyzed it standing on different views and gave some reasonable explanations. In terms of innovation cost， Keuschnigg and Gebhar
8、dt thought that newly established companies had not enough capital and credits and their innovation projects had bigger risks， so they were hard to get enough capital from 3traditional financial institutions， like banks， for researching 4，5. But venture capital institutions could resolve the problem
9、. They invested projects with bigger risks by holding stocks and affording perfect experiences in technology， business and management and implemented perfect inosculation of technology， capital and experiences and enhanced these established companies innovation capabilities. In terms of innovation s
10、ystem and efficiencies， Lv Wei made a comparative study on technological innovation efficiencies of existing enterprises under different economic system and argued that companies would met lots of obstacles when they had some inner technological innovation activities and when venture capital compani
11、es joined the innovation company， they could break through the obstacles by outer contracts 6. At last， he made an empirical analysis and proved his explanation. Wang Liang argued that venture capital created a sources supporting system which was out of the enterprise and could push the overflow of
12、technological innovation system from “slow” to “fast” 7. As a result， the innovation capabilities of a country were improved. In terms of system， Wang Sunqi thought that it was a basic way for building a country with high innovation capability to build a perfect system which could 4efficiently assig
13、n risks and benefits and could implement connection between venture capital and technology 8. On empirical researches， lots of Chinese scholars also pay more attention to the relationships of not only foreign countries but also homeland. Wang Yi and Xu Xiaosong made an empirical study on American ca
14、pital market and found that there was a positive correlation between venture capital and technological patents application and the former obviously improved the latter 9. Ding Wenli also made an empirical research according to American data and got that there was a stable relationships between both
15、10. Chen Kong， Liu Ren and Liu Yin used Chinese macro-data to make empirical study and took patents applied as an index of technology innovation and found that venture capital boosted technology innovation 11. Wang Yurong， Li Jun took listed companies which have venture capital institutions hold som
16、e stock in SMSE stock market and used regression analysis method and got the result that venture capital has a relatively positive function to technology innovation activities 12. Most of those researches used developed countries samples to study. Though a few analyzed Chinese situations， their samp
17、les came from listed companies from SMSE stock market or 5macro statistics data and were lack of samples from different industries and smaller scale companies. It is known that empirical results are based on specialized social and economic system， industrial levels which are very different in differ
18、ent countries. So we have to do more researches using Chinese samples to find our special rules. At the same time， some economic scholars hold cautiously optimistic attitudes because of our self-current situation. Wu Jinglian thought venture capital as one of new mechanism in China needed appropriat
19、e support system for exerting their functions 13. Tan Yi and Feng Zongxian thought that efficiencies of venture capital correlated industries innovation features 14. So， the paper thought it was necessary to analyze the relationships between companies which have venture capital institutions as stock
20、 holders and their technology innovation based on micro-data of different industries. The appearance of China Growth Enterprise Market just affords enough samples for our research. Section 2 contained variables design and samples source. Section 3 analyzed results of regressed samples. The last sect
21、ion is concludes and some policy advices. 2 Data Sources and Variables Designation 6Samples Comparing to Main Board of the stock market and SMSE （small and medium-sized enterprise） stock market， listed companies in the Growth Companies Market absorbed lots of venture capital investment institutions
22、as stock holders. So China Growth Companies Market affords the fittest samples for the researches on analyzing the relationships between venture capital and independent innovations of small and medium-sized enterprises. The paper selected whole fiscal year data before these companies IPO as regress
23、samples and tested the relationships between all companies innovation abilities and venture capital. Samples data came from 243 listed companies in China Growth Companies Market till 2011-6-31 except Suzhou Hengjiu Company because of lost listed qualification and other companies which are lack of en
24、ough information were eliminated. At last， 230 samples were left. All data in the paper were got from prospectuses of above companies， and patent numbers， stock ownerships and financial data were collected by manual work. Variables Designation Patent Num. Patent Num means total number of patents of
25、invention， utility model and design applied by sample-7companies. Patent Num applied by a company was taken as the substitutive variable for independent innovation capabilities of the company. Dum VC. It is a variable for venture capital. If sample-company has venture capital， its value is 1， else i
26、ts value is 0. The paper defined that if a company has one or more venture capital institution in its top ten biggest stock holders when IPO， it was taken as a listed company with venture capital supporting. Other variables that might affect patent numbers applied by the company， including proportio
27、n of technological workers （Tech） ， asset-liability ratio （Leverage） ， enterprise age （Age） ， proportion of holding shares of the largest holding sharer （Largest_Share） ， industry dummy variable （Indust） and region variable （Region） ， they were listed in table 1. Table 1 variables definition Variabl
28、e name Sign Defination Number of Pantents applied Patent_Num All patents applied of whole fiscal year before IPO Dummy variable of venture capital Dummy_VC Whether is there venture capital institutions of top ten stock holders Proportion of technician Tech Proportion of technician of a 8company in a
29、 fiscal year before IPO （%） asset-liability ratio Leverage asset-liability ratio of a company in a fiscal year before IPO （%） Proportion of holding stock of the biggest holder Largest_Share Proportion of holding stock of the biggest holder （%） Age of company Age years of a company from establish to
30、IPO Dummy variable for manufacturing industry Indust_Manu Whether does a company belong to manufacturing industry？ Dummy variable for information industry Indust_Infor Whether does a company belong to IT industry？ Dummy variable for east region Region_East Whether is a company location in east regio
31、n？ Dummy variable for middle region Region_Middle Whether is a company location in middle region？ 3 Regression Analysis Regression model Learning research method from Kortum and Lerner （2000） ， we used cross section regression method to study the affection of venture capital to enterprise independen
32、t innovation and built the following equation： Where 1 is a coefficient which represents whether a company with venture capital investment has more stronger 9independent innovation ability than a traditional company. If the coefficient is positive， it means venture capital can enhance its independen
33、t innovation ability. In the paper， other variables are controlled which are shown in table 1 and whose statistical description are shown in table 2. Table 2 Variables Statistical Description Variable Mean Max. Min. Std. Patent_Num 7.791304 101.0000 0.000000 12.68840 Dummy_VC 0.543478 1.000000 0.000
34、000 0.499192 Tech 26.49287 94.69000 3.720000 18.85649 Age 9.36956 23 1 3.78781 Largest_Share 44.82378 91.82000 11.70000 16.92984 Leverage 38.92365 78.34000 4.310000 14.87367 Indust_Manu 0.691304 1.000000 0.000000 0.462963 Indust_Infor 0.195652 1.000000 0.000000 0.397567 Region_East 0.795652 1.000000
35、 0.000000 0.404104 Region_Middle 0.117391 1.000000 0.000000 0.322588 Regression Result Analysis Because cross-section data came from the single time point， there is not serial correlation. But cross-section data can be heteroscedasticity. Weighted least squares technique （WLS） is used to solve the p
36、roblem. Its weight equals a 10reciprocal of absolute value of estimated error. Table 3 shows regression result of venture capital and enterprise independent innovation. In the table， adjusted R2 is bigger than 0.9 that means the regression equations have better degree of fitting. Both F value and it
37、s p value also gave the same concludes. Column （1） shows the regression result of a basic equation. In the equation dummy variable Dum_VC passed the statistical test in 1% significant level and its coefficient is positive that means companies who have venture capital supporting have stronger innovat
38、ions abilities than other companies without venture capital joining. As a result， we got the conclusion that venture capital improved independent innovation of these companies. Column （2） gives the result including other controlled variables. And we got same conclusion with column （1）. At the same t
39、ime， we found that companies in manufacturing industry have stronger innovation abilities than ones in information industry. This can be explained that in China companies in manufacturing industry have solid bases and less disadvantaged than companies in developed countries. This conclusion is consistent with “big manufacturing country” title. Thinking of patents of invention which can better represent enterprisers independent
