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Fiscal Incentives for Innovation in Foreign Countries: An Analytical Review of Positive and Negative Effects

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  • I. A. Mayburov

    (Ural Federal University named after the first President of Russia B.N. Yeltsin, Yekaterinburg, Russian Federation; Financial University under the Government of the Russian Federation, Moscow, Russian Federation)

Abstract

The technological aspect of innovation stimulation is becoming central for Russia, since the introduction of new technologies is one of the most important factors affecting the economy’s ability to remain sustainable in the context of sanctions restrictions and cut-off from the transfer of breakthrough technologies. The task of the state to improve the efficiency of its fiscal policy with regard to stimulating innovation is highly relevant. In the course of the review we tried to answer the following questions: What impact do the main instruments of fiscal policy have on innovation stimulation? Which effects of innovation incentives are positive and which are negative, and what recommendations can increase the efficiency of fiscal policy? The purpose of this article was to identify the effects generated by the main instruments of innovation stimulation (tax incentives and budget subsidies) and to develop recommendations for the formation of effective fiscal policy. For the theoretical review the protocol of multistage selection of high-quality articles was used. The principle of incentive efficiency was substantiated and its decomposition into constituent effects was performed. Twelve incentive effects were identified. In the process of fiscal stimulation, the manifestation of six positive effects is revealed: the signal effect and the effects of knowledge spillover, productivity, high-tech companies, and market failure correction. Four negative effects are identified: crowding out, substitution, small and excessive incentives, and policy uncertainty. Two mixed effects are also identified: imitation and scale. The author's recommendations to strengthen the positive and mixed effects and neutralize the negative effects of innovation incentives are presented.

Suggested Citation

  • I. A. Mayburov, 2025. "Fiscal Incentives for Innovation in Foreign Countries: An Analytical Review of Positive and Negative Effects," Finansovyj žhurnal — Financial Journal, Financial Research Institute, Moscow 125375, Russia, issue 5, pages 126-142, October.
  • Handle: RePEc:fru:finjrn:250508:p:126-142
    DOI: 10.31107/2075-1990-2025-5-126-142
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    References listed on IDEAS

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    1. Liliana Gelabert & Andrea Fosfuri & Josep A. Tribó, 2009. "Does The Effect Of Public Support For R&D Depend On The Degree Of Appropriability?," Journal of Industrial Economics, Wiley Blackwell, vol. 57(4), pages 736-767, December.
    2. H. Ahmed & SM. Miller, 2000. "Crowding‐out and crowding‐in effects of the components of government expenditure," Contemporary Economic Policy, Western Economic Association International, vol. 18(1), pages 124-133, January.
    3. Gregory Tassey, 2007. "Tax incentives for innovation: time to restructure the R&E tax credit," The Journal of Technology Transfer, Springer, vol. 32(6), pages 605-615, December.
    4. Nicholas Bloom & Mark Schankerman & John Van Reenen, 2013. "Identifying Technology Spillovers and Product Market Rivalry," Econometrica, Econometric Society, vol. 81(4), pages 1347-1393, July.
    5. Uwe Cantner & Sarah Kösters, 2012. "Picking the winner? Empirical evidence on the targeting of R&D subsidies to start-ups," Small Business Economics, Springer, vol. 39(4), pages 921-936, November.
    6. Guan, Jialin & Xu, Huijuan & Huo, Da & Hua, Yechun & Wang, Yunfeng, 2021. "Economic policy uncertainty and corporate innovation: Evidence from China," Pacific-Basin Finance Journal, Elsevier, vol. 67(C).
    7. Cappelli, Riccardo & Czarnitzki, Dirk & Kraft, Kornelius, 2014. "Sources of spillovers for imitation and innovation," Research Policy, Elsevier, vol. 43(1), pages 115-120.
    8. Michael König & Kjetil Storesletten & Zheng Song & Fabrizio Zilibotti, 2022. "From Imitation to Innovation: Where Is All That Chinese R&D Going?," Econometrica, Econometric Society, vol. 90(4), pages 1615-1654, July.
    9. Dang, Jianwei & Motohashi, Kazuyuki, 2015. "Patent statistics: A good indicator for innovation in China? Patent subsidy program impacts on patent quality," China Economic Review, Elsevier, vol. 35(C), pages 137-155.
    10. Bianchi, Mattia & Murtinu, Samuele & Scalera, Vittoria G., 2019. "R&D Subsidies as Dual Signals in Technological Collaborations," Research Policy, Elsevier, vol. 48(9), pages 1-1.
    11. Fan, Weina & Anser, Muhammad Khalid & Nasir, Muhammad Hamid & Nazar, Raima, 2023. "Uncertainty in firm innovation scheme and impact of green fiscal policy; Economic recovery of Chinese firms in the post-Covid-19 era," Economic Analysis and Policy, Elsevier, vol. 78(C), pages 1424-1439.
    12. Danlei Feng & Mingzhao Hu & Lingdi Zhao & Sha Liu, 2022. "The Impact of Firm Heterogeneity and External Factor Change on Innovation: Evidence from the Vehicle Industry Sector," Sustainability, MDPI, vol. 14(11), pages 1-15, May.
    13. Yu, Anyu & Shi, Yu & You, Jianxin & Zhu, Joe, 2021. "Innovation performance evaluation for high-tech companies using a dynamic network data envelopment analysis approach," European Journal of Operational Research, Elsevier, vol. 292(1), pages 199-212.
    14. Cheung Kui-yin & Lin, Ping, 2004. "Spillover effects of FDI on innovation in China: Evidence from the provincial data," China Economic Review, Elsevier, vol. 15(1), pages 25-44.
    15. Hong Xu & Kai Lin & Lei Qiu, 2023. "The Impact of Local Government Environmental Target Constraints on the Performance of Heavy Pollution Industries," Sustainability, MDPI, vol. 15(22), pages 1-24, November.
    16. Michael A. Hitt & David Ahlstrom & M. Tina Dacin & Edward Levitas & Lilia Svobodina, 2004. "The Institutional Effects on Strategic Alliance Partner Selection in Transition Economies: China vs. Russia," Organization Science, INFORMS, vol. 15(2), pages 173-185, April.
    17. Prianto Budi Saptono & Ismail Khozen & Gustofan Mahmud & Sabina Hodžić & Intan Pratiwi & Dwi Purwanto & Lambang Wiji Imantoro, 2024. "Flourishing MSMEs: The Role of Innovation, Creative Compliance, and Tax Incentives," JRFM, MDPI, vol. 17(12), pages 1-50, November.
    18. Liu, Dayong & Chen, Tong & Liu, Xiaoyang & Yu, Yongze, 2019. "Do more subsidies promote greater innovation? Evidence from the Chinese electronic manufacturing industry," Economic Modelling, Elsevier, vol. 80(C), pages 441-452.
    19. Guo, Yan & Zhang, Haochen, 2022. "Spillovers of innovation subsidies on regional industry growth: Evidence from China," Economic Modelling, Elsevier, vol. 112(C).
    20. He, Siyi & Liu, Jinsong & Ying, Qianwei, 2023. "Externalities of government-oriented support for innovation: Evidence from the national innovative city pilot policy in China," Economic Modelling, Elsevier, vol. 128(C).
    21. Scott J. Wallsten, 2000. "The Effects of Government-Industry R&D Programs on Private R&D: The Case of the Small Business Innovation Research Program," RAND Journal of Economics, The RAND Corporation, vol. 31(1), pages 82-100, Spring.
    22. Fengli Kang & Qiaomao Yu & Mengfei Wan, 2023. "Corporate Innovation Incentive Policy During Business Cycles: Fiscal Subsidies or Tax Incentives?," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 59(7), pages 2190-2203, May.
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    JEL classification:

    • H21 - Public Economics - - Taxation, Subsidies, and Revenue - - - Efficiency; Optimal Taxation
    • H25 - Public Economics - - Taxation, Subsidies, and Revenue - - - Business Taxes and Subsidies

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