• Journal of Technology Innovation
• /
• v.11 no.2
• /
• pp.175-193
• /
• 2003

The purpose of this study is to examine relationship between public R&D investment and private R&D investment in Korea, and to obtain policy implications of the results. To this end, the author attempts to provide more careful consideration of the causality issues by applying rigorous techniques of Granger causality. Tests for unit roots, co-integration, and Granger causality based on an error-correction model are presented. The existence of bi-directional causality between public R&D investment and private R&D investment is detected. This finding has various implications for policy analysts and forecasters. Increasing private R&D investment requires enormous public R&D investment, though there are many other factors contributing to private R&D investment, and public R&D investment is but one part of it. Thus, this study generates confidence in decisions to invest in public R&D. Moreover, this study lends support to the argument that increase in private R&D investment, ceteris paribus, gives rise to public R&D investment. Increase in private R&D investment results in greater national income to be spent on R&D investment and stimulates further public R&D investment.

• Proceedings of the Korea Technology Innovation Society Conference
• /
• 2000.11a
• /
• pp.346-356
• /
• 2000

This paper aims to analyse the relationship between R＆D investment and economic growth in Korea. The analysis result shows 38 percent of average economic growth rate(7.1%) of Korea between 1976 and 1998 was achieved by the growth of Total Factor Productivity (TFP), and the R&D investment during the period contributed in achieving the economic growth rate by as much as 9.86 percent. In the process of the estimate, the rate of return of the R&D investment from both government and private was calculated as 47 percent. The relationship between private R&D investment, government R&D investment and the GDP was also investigated, and it was estimated that the private sector invested 2.0 percent of the GDP in R&D during the period, and was found that 1 won of government R&D investment induced 0.202 won of private sector's R&D investment. However, the time-lag effect, which is naturally believed to exist between the R&D investment and the economic growth, could not be analysed in a mathematical form, because of the lack of the data to establish this relationship. However, this paper believe that the time-lag effect in this relationship was included implicitly by using the data of 23 years.

• Journal of Technology Innovation
• /
• v.16 no.2
• /
• pp.147-165
• /
• 2008

The researches on cyclical patterns of R&D investment has a long history in developed economies since the Schumpeterian hypothesis that long-term productivity-enhancing innovative activities increase during recession. But in Korea the cyclical patterns of R&D investment is one of the unexplored academic areas. Unlike theoretical explanation of R&D's cyclical pattern, empirical results has shown that R&D investment is procyclical to business cycles in developed countries. This paper investigates whether Korean R&D investment show procyclical or countercyclical pattern to business cycles. The empirical results show that Korean R&D investment in private area is procyclical to business cycles with statistical significance, which confirms the credit-constraint theory's prediction, while public area's is not sensitive to them. Public R&D investment has long-term investment characteristics and can be utilized to stabilize procyclically-fluctuating private R&D investment.

• Journal of Korea Technology Innovation Society
• /
• v.7 no.2
• /
• pp.257-281
• /
• 2004

In this paper we： (1) analyze the relationship among public R＆D investment, private R＆D investment, and GDP by employing the Clangor causality test; (2) examine if there is any country-specific pattern in the relationship by testing the cases of Korea, the U.S. and Japan. We found some common results for the above countries as follows： (i) GDP causes Public R＆D, not vice versa; (ii) Private R＆D causes GDP; and (iii) Public R＆D does not cause Private R＆D. For the bivariate model of GDP and total R＆D, the results show the existence of one-way causality running from total R＆D to GDP f3r both U.S. and Japan. We also found bidirectional causal relationship between GDP and total R＆D for Korea, which could be interpreted as a typical pattern for newly industrialized countries.

• Journal of Korea Technology Innovation Society
• /
• v.10 no.4
• /
• pp.706-726
• /
• 2007

This study attempts to empirically investigate the effects of government R&D subsidies on private firm's R&D investment in Korean industry. The R&D subsidy effect is defined as the average percentage change in firm's R&D expenditures between what was actually observed among firms that received a subsidy and what these firms would have spent had the subsidy not been received. To measure the effect we use Difference-in-Differences (DID) model which sign as to whether the relationship between government subsidies and private R&D investments is on stimulating or displacing private R&D expenditures. The differences between this study and previous studies are that we tries to measure the effect of Government R&D across various sited firm groups such as large, small & medium, and venture firms and we add one lag of the subsidy indicator in order to capture the effect of the subsidies on private R&D during 2 consecutive period. Empirically, a firm with government R&D subsidy increases its own R&D investment by 13.9%. Also on average, 1% of government R&D subsidy leads to 0.031% of private R&D increase. The main results of this study are as follows : First, Government R&D subsidies stimulate private firm's R&D expenditures. Second, Government R&D subsidies greatly increase (statistically significant) company financed R&D expenditures only for large firms but had no effect on the R&D expenditures of small & medium sized firms and venture firms.

• Journal of Technology Innovation
• /
• v.27 no.3
• /
• pp.27-52
• /
• 2019

This research studied the determinants of private R&D investment by examining the innovation strategies of 481 small and medium enterprises (SMEs, their employee size is 5 or more and less than 300) in Busan, South Korea. The data is derived from the Technology Survey of Small and Medium Enterprises in 2001 and 2003. Three explanatory variables for the innovation strategies are the R&D portfolio, the organization (personnel) for R&D, and the strategic role of CEO for innovation. The technological levels of industries are controlled in the linear regression model. The dependent variable is the total private R&D investment of a firm in the given fiscal year. The empirical results indicate that the private R&D investment positively correlates with the complexity of the R&D portfolio, the formal organization for R&D team, and the increase of R&D personnel. The formal organization for R&D team and the number of R&D personnel are correlated with the increase of private R&D investment across the four groups in the manufacturing sector but not in the service sector. These findings suggest that the innovation policy needs to target firms who have complex R&D portfolios, the formal organization of R&D teams, and sufficient R&D personnel in order to increase the private R&D investment of SMEs in regions, with consideration of industrial characteristics.

• Journal of the military operations research society of Korea
• /
• v.34 no.1
• /
• pp.79-98
• /
• 2008

The purpose of this paper is to find the desirable R&D policies in defense area by analyzing causality between GDP and R&D investments in government, private, defense sectors. We have five variables which are composed of GDP, total R&D investment, R&D investments in government, private and defense sectors to figure out the causality between R&D investment in defense sector and other components. In the course of analysis on causality, we took the unit root test of variables to prevent spurious regression. Also we need to take cointegration test about non-stationary variables before the causality test. According to these test results, we took the causality test using ECM(Error Correction Model) for the models which have cointegrating relations. And we took ordinary Granger causality test for model which doesn't have a long-run stationary relationship. As a result of the causality test, it was shown that there exists the long-nu causality to GDP and R&D investments in government and private sectors from other variables. However, there doesn't exist the causality to defense R&D investment from other variables. We found that there doesn't exist the causality between R&D investments in defense and private sectors, and that they are independent.

• Journal of Technology Innovation
• /
• v.21 no.2
• /
• pp.137-167
• /
• 2013

This article estimates the scale of impact of expanding governmental fiscal expenditure for R&D investment on the private business enterprise's investment for R&D, and the relationship between business enterprise and university for expanding investment of R&D. According to my results, first, an expanding fiscal expenditure from government for R&D investment leads to increase R&D investment from business enterprise. However, an expanding expenditure from university rather leads to decrease R&D investment from business enterprise. Secondly, the crowding-out effect of expanding R&D investment from University on business enterprise's is very strong, and it is affected by structural changes such as the country's economic power, fiscal stance and cyclical volatility. Third, the more governmental expenditure on university expansive is, the stronger asymmetric relationship between business enterprise and university is, and investment sources of university from business enterprise is the main factor of this relationship. Finally, it is not easy to solve out this asymmetric relationship even through the governmental subsidy.

• Clean Technology
• /
• v.17 no.2
• /
• pp.181-188
• /
• 2011

In this study, the complementary or crowding-out effects of public R&D subsidy on private R&D investment in the cleaner production were analysed between the effects and the major determinants (company size, R&D investment intensity, ratio of government investment, R&D manpower intensity). Among 207 firms' projects, the number of the complementary effect was 95 (45.9%) while that of crowding-out effect was 38 (18.4%). Resulting from logistic regression, the higher the R&D investment of sponsored companies is, the more complementary effect they show, responding to public R&D subsidy, and increase own R&D investment. The other determinants, however, showed no significant effects on firms' R&D investment. To heighten the effect of public cleaner production R&D, it is need to increase the priority of R&D investment intensity among the determinants. And to increase the performance of governmental R&D investment, further studies for the individual public R&D programs are necessary.

• Journal of Technology Innovation
• /
• v.18 no.1
• /
• pp.75-98
• /
• 2010

The purpose of this paper is to give policy implications for relevant policy-makers by analyzing factors affecting performance of industrial R&D programs of the Ministry of Knowledge Economy. The independent variables are type of project leader organization(Big Enterprises, SMEs, Ventures Businesses, Public Research Institutions, Universities), cooperative or noncooperative R&D among industry-university-research institution, total number of project participant organization, total R&D investment, and the ratio of private investment to total R&D investment. The dependent variables are domestic or foreign patents granted and domestic or foreign papers accepted. The method of analysis is Poisson Regression analysis operated by STATA. The results of this research are follows ; Universities show higher R&D performance compared to enterprises or public research institutions in terms of patents and papers as well. Venture businesses show higher patent performance compared to SMEs. Inverted U-shaped relationship between total number of project participant organization and R&D performance is not supported. The higher total R&D investment, the higher R&D performance. The higher the ratio of private investment to total R&D investment, the higher R&D performance.