Assessing the economy-wide impacts of public R&D support options based on a computable general equilibrium model: focusing on types of fiscal incentives and beneficiaries

ABSTRACT

This study conducted quantitative comparisons of various public R&D support options using a CGE model. The analysis considered four different options by varying the types of fiscal incentives and the scope of beneficiaries concerning the firm size. The findings indicate that direct subsidy is more effective in spurring private R&D investments than indirect tax incentives. In addition, selective R&D support toward small and medium enterprises is found to induce balanced growth among industries. In summary, the simulation results suggest that R&D support under the direct subsidy scheme aimed at SMEs has the potential to achieve a higher equilibrium state within the Korean economy. This study confirms that the government should carefully design the R&D promotion policy by ensuring that direct R&D inducement effects are transmitted to industrial output growth with a diversified industrial structure and higher knowledge spillover effects.

KEYWORDS:

• Innovation
• R&D
• Public subsidy
• Tax incentive
• SME
• Computable general equilibrium

JEL CODE:

• O30
• O32
• O38
• O40
• O50
• C68

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 We have considered 28 types of industries within the SAM dataset before specifying the LEs and SMEs in individual industrial sectors. Based on these classifications, we have specified the manufacturing sectors with considerations of firm heterogeneity in terms of firm size into LEs and SMEs.

2 DIR-ALL reveals a higher GDP level in 2030 despite a lower level of investment inducing effects in total assets in DIR-ALL compared to IND-SME. This can be understood via its greater R&D capital inducement effects, as it spurs higher knowledge spillover effects and productivity improvements across industrial sectors, rather than physical capital accumulation.

3 Based on previous approaches (Yeo and Lee 2020), the classification between high-tech and low-tech manufacturing industries is based on whether the R&D intensity is higher than the average level of R&D intensity among manufacturing industries.

4 A higher concentration of industrial structure can be vulnerable to economic volatility and extreme changes in external conditions, which weakens the growth potentials of the economic system.

Additional information

Funding

The work was supported by the Korea Institute of Science and Technology Evaluation and Planning (KISTEP) [KISTEP-BC19010].