정부 R&D 자금지원과 중소기업의 성과

Government R&D subsidies (hereafter referred to as government subsidies) have continued to increase over time. In particular, the amount of government subsidies to small and medium enterprises (SMEs) has increased from 651 billion Korean won in 2003 to 1.5 trillion Korean won in 2009. The total amount of government subsidies given to SMEs for the period between 2003 and 2009 was approximately 6.9 trillion Korean won, which was much more than that given to large companies for the same period. This huge amount of government subsidies to SMEs may be justified when the government subsidies led to better R&D and business performance of SMEs. On the basis of this observation, this study attempts to assess the effects of government subsidies on the performance of SMEs. The study supposes that government subsidies have a direct effect on the R&D activities of SMEs, which in turn affects their business performance. In particular, the study tests the following two hypotheses :H1 : Government subsidies tend to improve the R&D performance of SMEs. H2 : Better R&D performance of SMEs leads to better business performance. In the study, R&D performance is measured by three variables; the number of successful R&D activities, the number of successfully commercialized technologies, and the number of intellectual property rights, including patents, utility models and design, which are either applied for or registered. The study used three proxy variables for business performance; sales per employee, operating income per employee, and profit margin ratio which is the ratio of operating income to total sales. The first two variables for business performance measured labor productivity, while the last one measured firm profitability. The study collected cross-sectional data of 2,881 SMEs in the manufacturing sector from “Survey on the State of Technology for SMEs 2007” which was conducted by the Korea Federation of Small and Medium Business. The time span encompassed by the study is the period from January 2005 to December 2006. The data utilized in the study is unique in that it provided a great deal of information on the R&D activities of SMEs, including the number of researchers, the amount of R&D expenditures, types of R&D organization, the presence of incentive scheme for R&D performance etc. Additionally, the data provided detailed information on firm and industry characteristics. <Table 4> shows the relationship between government subsidies and the R&D performance of SMEs. In <Table 4>, the average number of successful R&D activities for the SMEs which did not receive government subsidies over the sample period (Group A) was 5.09, which was greater than that for the SMEs which received government subsidies over the sample period (Group B). Difference in the average number of successful R&D activities between two groups, however, is not statistically confirmed at a 10% significance level. Second, the average number of successfully commercialized technologies for the SMES of Group A was 3.09, while that for the SMEs of Group B was 2.29. The t-test statistic indicates no difference in the average number of successfully commercialized technologies between two groups. Finally, the average number of intellectual property rights for the SMEs of Group A and Group B was 1.99 and 3.57, respectively. Additionally, difference in the average number of intellectual property rights between two groups is statistically significant at a 1% significance level. In summary, this descriptive analysis indicates that government subsidies had positive effects on the R&D performance of SMEs only in terms of the number of intellectual property rights. To test the two hypotheses, the study specifies two regression equations; one for R&D and the other for business performance. Three R&D (business) performance variables were dependent variables in the first (second) regression equation. The key policy variable in the first equation was a dummy variable for government subsidies. This dummy variable was equal to unity for the SMEs which received government subsidies; otherwise, equal to zero. In the second equation, special attention was paid to the parameter estimates of three R&D performance variables. Considering the business performance of SMEs may have an influence on their R&D activities and performance, both R&D and business performance variables are regarded as jointly determined endogenous variables in the empirical model. In this case, the application of the ordinary least squares estimation method produced biased parameter estimates. The study applied the generalized method of moments (GMM) estimation method to a system of the two regression equations. It is well known that the GMM estimation method provides consistent and efficient parameter estimates. <Table 9> provided estimation results for the R&D performance model. In <Table 9>, a majority of independent variables had a statistically insignificant parameter estimate and also the value for adjusted coefficient of determination (adjusted R2) was very low. In particular, the reported parameter estimates of three business performance variables were always statistically insignificant. These findings indicate that the R&D performance of SMEs is determined mainly by unobserved random factors. One of the noticeable results in <Table 9> is that the parameter estimates of government subsidies (SUB) are positively signed in all models, and are statistically significant only when the number of intellectual property rights was used as a dependent variable. That is, government subsidies tended to increase the number of intellectual property rights, but failed to have an effect on the number of successful R&D activities and successfully commercialized technologies. Additionally, the parameter estimates of the number of researchers (NRES) are positively signed and statistically significant, indicating that more researchers produced better R&D performance. <Table 10> presents the estimation results for the business performance model. In <Table 10>, as expected, the parameter estimates of the three R&D performance variables were always positively signed. In particular, they were statistically significant when sales per employee (SPE) and operating income per employee (OIPE) were used as a dependent variable. This finding shows that better R&D performance resulted in higher labor productivity. The results, however, did not confirm the positive effect of R&D performance on profit margin ratio (PMR). Similar to the previous result, many independent variables had a statistically insignificant parameter estimate. In summary, the empirical results did not reject the two hypotheses. Government subsidies contributed to better business performance through their impact on the R&D performance, especially their impact on the number of intellectual property rights. The empirical results provided some public policy implications. First of all, the results suggested the possibility that SMEs attempted to achieve only their short-term goals such as the increased number of intellectual property rights after receiving government subsidies. Clearly, the number of intellectual property rights itself cannot be regarded as the ultimate goal for SMEs’ R&D activities. Thus, this behavior by SMEs may pose a serious threat to government R&D subsidy policies. Second, the results indicate that business performance of SMEs did not affect their R&D performance, implying that SMEs with good financial performance may not be involved in active R&D activities. This lack of R&D activity may prevent sustainable growth of SMEs.