KDI Brief No.127 (April 13, 2018)Subscribe
|Government R&D Support for SMEs:
Policy Effects and Improvement Measures
The government’s R&D grant for SMEs has risen to 3 trillion won a year, placing Korea second among OECD nations. Indeed, analysis revealed that government support has not only expanded corporate R&D investment and registration of intellectual property rights but has also increased investment in tangible and human assets and marketing. However, there has been a lack of improvements found in the value added, sales and operating profit because the recipient selection system, which relies solely on the qualitative assessments of technology experts was ineffective. Nevertheless, if a predictive model was properly applied to the system, the causal effect on the value added could increase by more than two fold. Accordingly, to develop such a model, it is important to focus on the economic performance rather than the technical achievements. Also, more policy experiments should be conducted on small firms and a phased approach for R&D financing should to be adopted (① grant → ② equity investment → ③ loan).
Korea’s R&D subsidy for SMEs has risen to approx. 3 trillion won a year, making Korea the second largest spender among OECD nations.
The SBIR, the main R&D support program for SMEs in the US, is structured in three phases.
The US case shows that the small lump sum grants for a large number of small firms is more effective than large funds for a few mid-sized firms.
The Korean government’s corporate R&D support mostly targets medium-sized development activities, not small-scaled exploratory research.
Current corporate R&D support which is evaluated by the number of registered patents and publications must be reformed.
The scalability of intangible assets is as important as the economies of scale of tangible assets.
In all indicators, recipients exhibited much better performance than nonrecipients at the time of support.
In most performance indicators, recipients stand lower than non-recipients in terms of growth. The former even posted negative growth in operating profit and R&D investment.
This study estimated the causal effects using the two-step approach which integrates the nonparametric matching method and parametric regression model.
The government’s R&D support contributed to SMEs’ debt and equity financing, and firms expanded their investment in capabilities/assets such as intellectual properties, relational assets, tangible assets and human capital.
Using the funding, firms invested more in capabilities/assets, but it did not lead to improving the value added, operating profit and sales growth.
Firms with high growth prospects were selected as recipients in a smaller proportion while those with low growth prospects were selected as recipients in a larger proportion, making the value added growth of recipients lower than the average.
Estimation of the heterogenous causal effects on the value added increments found a positive effect only in the top four deciles.
If the support given to those with negative treatment effect was redistributed, this could double the positive effect.
In keeping pace with the flexibility in corporate R&D practices, the government needs to explore an operating system in which an active exchange of feedback takes place between R&D experiments and market verification.
This study suggests reforming the existing recipient selection practice which is solely based on the qualitative evaluation by technology experts, and promoting the use of the predictive model and a phased expansion of policy experiments.
Evaluations should target economic performance, not publications, IP rights and R&D amount, and a selection model should be developed to optimize the evaluation results.
In accordance to risks associated with the respective stages of R&D and commercialization, the government needs to choose the most suitable financing methods among grants, equity investment and loan support.
More free contests should be offered.