Number of purchasers: 0, views: 530
Readers community rating: votes 0
1. Boeing P., Eberle J., Howell A. (2022). The impact of China's R&D subsidies on R&D in-vestment, technological upgrading and economic growth. Technological Forecasting and Social Change. Vol. 174. DOI:10.1016/j.techfore.2021.121212
2. Bonferroni C. (1936).Teoria statistica delle classi e calcolo delle probabilità.Publicazioni del R. Istituto Superiore di Scienze Economiche e Commerciali di Firenze, 8, 1–62.
3. David P., Hall B., Toole A. (2000). Is public R&D a complement or substitute for private R&D? A Review of the Econometric Evidence. Research Policy, 29 (4–5),497–529.
4. Gavrilets Y.N., Lebedev K.V., Tarakanova I.V. (2021). On statistical evaluation of science and education in the subjects of the Russian Federation in 2017–2019. In: Collection of articles of the international scientific-practical conference. Krasnodar: Prosveshenie-Yug (in Russian).
5. Gavrilets Yu.N. (1974). Social and economic planning. Systems and models. Moscow: Eco-nomics (in Russian).
6. Gavrilets Yu.N., Kudrov A.V., Tarakanova I.V. (2018). Analysis of the internal structure for the economic growth potential. Herald of CEMI, 1, 1. Available at: https://cemi.jes.su/s111111110000009-2-1/ (in Russian).
7. Glazyev S.Y. (2019). The development of the Russian economy in the context of global technological shifts. The future of Russia. Executions and projects: Economics. Technique. Innovations. Moscow: URSS (in Russian).
8. Golichenko O.G. (2007). National innovation system of Russia: State and ways of develop-ment. Voprosy Ekonomiki, 7, 155–157 (in Russian).
9. Hayes D. (1981). Causal analysis in statistical research. Moscow: Finansy i statistika (in Rus-sian).
10. Holm S. (1979). A simple sequentially rejective multiple test procedure. Scandinavian Journal of Statistics, 6, 2, 65–70.
11. Lauritzen S. (1996). Graphical models. Oxford: Oxford University Press.
12. Liu F., Simon D., Sun Y., Cao C. (2011). China’s innovation policies: Evolution, institutional structure, and trajectory. Research Policy, 40, 917–931.
13. Makarov V.L. (2003). Contours of knowledge economy. The Economist, 3, 3–15 (in Russian).
14. Makarov V.L. (2013). Science cannot be effective. Direct Investments: Magazine about Real Economy, 5, 21–23 (in Russian).
15. Mazzucato M. (2015).The entrepreneurial state: Debunking public vs. private sector myths. London: Anthem Press.
16. OECD (2022a). Gross domestic spending on R&D (indicator). DOI: 10.1787/d8b068b4-en
17. OECD (2022b). Researchers (indicator). DOI: 10.1787/20ddfb0f-en
18. Ratkowsky D. (1993). Principles of nonlinear regression modeling. Journal of Industrial Mi-crobiology, 12, 195–199.
19. Seber G., Wild C. (2003).Nonlinear Regression. N.Y.: Wiley.
20. Stiglitz J., Lin Y., Monga C. (2013). The rejuvenation of industrial policy. World Bank Policy, Res. Work. Pap. 6628.
21. Varshavskiy A.E., Makarov V.L. (2004). Sustainable development strategy: The need for in-vesting in the future. In: Innovation management in Russia: Issues of strategic manage-ment and scientific and technological security. V.L. Makarov, A.E. Varshavskiy (head of author's team). Moscow: Nauka (in Russian).
22. Varshavsky A.E., Makarov V.L. (2015). Science, high-tech industries and innovation. In: Russian economy. Oxford compendium. Book 2. Moscow: Gaidar Institute Publishing House (in Russian).