Tax Incentives for R&D and Innovation: Demand versus Effects
Tax incentives have proven to be an efficient tool of state support for science, technology and innovation, and are used by many countries on their way towards sustainable development and enhancing global competitiveness. Fiscal stimuli are increasingly combined in a more flexible manner, thus contributing to attaining wider spectrum of objectives; means of international comparison and evaluating impact of these tools are actively evolving. However, despite the fact that for many countries the tax incentives are demandable and work effectively, Russia's situation is different. Based on the results of a specialized survey, the paper estimates the demand for R&D tax breaks from Russian manufacturing enterprises, research organizations and universities performing R&D. The study demonstrated that such a demand is generally low for all types of surveyed organizations, probably due to both the imperfection of the Russian tax legislation, which makes the considered tool inefficient, and low share of the organizations engaged in R&D and innovation. Among the most frequently noted demotivating factors were mismatch of organization’s activity to the terms of using a specific tax break, as well as unwarranted costs associated with the need to prove the right to use these breaks. When using a specific tax incentive, the research institutions typically seek exemption from VAT for R&D activities and patent licensing operations, as well as benefit to mainstream targeted grants. Universities engaged in R&D are more likely to turn to the benefits for grants and accelerated depreciation of fixed assets used for scientific and technological activities. The analysis showed that in Russia the public sector dominates among all categories of recipients of tax incentives for research and innovation. This situation is contrary to best practices and global trends in supporting research activities, which involve betting on strong national players (including startups and SMEs). It hardly allows STI tax incentives to be an efficient mean and provides a basis for the revision and optimization of these tools. This paper indicates possible further directions in the studying tax incentives, their classification, performance assessment and optimization to meet best practices, global trends, and the forefront of research in this area.