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KDI FOCUS

Government R&D Support for SMEs: Policy Effects and Improvement Measures

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  • Author LEE. Sungho
  • Date 2018/04/12
  • Series No. KDI FOCUS No. 89, eng.
  • Language English
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SUMMARY □ 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.
KDI VOD Report
Qualcomm, Symantec, 23andMe and iRobot,
are all firms that started small but are now market leaders
thanks to their innovative technological capabilities.

And, supporting their growth was the US’ Small Business Innovation
Research program, or SBIR, which provides active R&D support to small
companies and startups.

Taking cue from the US’ program,
the Korean government established the Korea Small Business Innovation
Research program in 1998 to drive the growth of Korea’s SMEs.

Since then, the budget for the R&D grant has continued to mount,
nearing the 3 trillion won mark in 2015.

Korea is now ahead of Germany and Japan,
and is the second largest spender after the US.

Thanks to the grants,
many of the recipients have been able to strengthen their technological
capabilities.

However, due to the lack of preceding research,
it is unclear what other benefits the grants offer.

Accordingly, KDI analyzed the economic gains of Korea’s R&D support.

A simple comparison was first conducted between recipients and
non-recipients based on ten performance indicators.

The results found that recipients overwhelmed their counterparts
in terms of operating performance, financing and capabilities and assets
at the time of support.

But, after 2 or 3 years, the trend reverses,
with non-recipients making bigger improvements across the majority of
indicators.

Next, an examination was conducted on
the impact of the grant on corporate growth.

The grants enabled companies to secure more funding
and expand their investments in all aspects.

Unfortunately, this failed to improve the value added,
operating profit and sales.

Then, why is the government grant unable to help with the
corporate value added?

Believing that technological competence generates high growth,
the government selects recipients based on this.

In fact, compared to the small number of companies with a large
number of registered patents, a relatively large share were selected as
recipients, and vice versa.

And, contrary to expectations,
the average value added of those with many patents was lower.

In addition, the value added of numerous recipients showed an
improvement while that of the majority declined.

Those in the lowest decile, in particular, had long histories, large-scale
capital and numerous patent registrations.

As such,
using a predictive model that is more focused on economic performance
than technological competence to select recipients and distribute grants
could double the value added.

[저자 인터뷰]
Until now, the selection and planning processes for
the government’s SME R&D support program
have been overly dependent on technology experts.
As a result, a mismatch has ensued in which
firms with rich R&D experience become recipients
while those at the seed stage receive policy financing.
In order to maximize the creation of value added,
the R&D grant must maintain the role of a seed fund
and focus on supporting underfunded, small businesses
with high-risk research and development.
If a predictive model for the policy effects was to be developed
and applied to the recipient selection process,
the government will be able to break away from
the current complicated system
and turn its attention to supporting the structured research of SMEs.
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