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Knowledge spillover effects: empirical evidence from Russian regions

Author

Listed:
  • Luigi Aldieri

    (University of Naples Parthenope)

  • Maxim Nikolaevich Kotsemir

    (National Research University Higher School of Economics)

  • Concetto Paolo Vinci

    (University of Salerno)

Abstract

This study contributes to existing literature on the relationship between productivity and innovation through the knowledge spillover effects. To this end, we consider both a theoretical model and an empirical analysis in Russia. The investigation is based upon a dataset composed of 85 Russian regions for the period 2010–2014. In particular, the effect of R&D Spillovers are analysed through the use of spatial econometric techniques. In so doing, we have allowed the productivity of each region to be affected by the productivity of nearby regions. Results show that R&D significantly affects Russian regions productivity and that productivity spillover across regions matter.

Suggested Citation

  • Luigi Aldieri & Maxim Nikolaevich Kotsemir & Concetto Paolo Vinci, 2018. "Knowledge spillover effects: empirical evidence from Russian regions," Quality & Quantity: International Journal of Methodology, Springer, vol. 52(5), pages 2111-2132, September.
    • Handle: RePEc:spr:qualqt:v:52:y:2018:i:5:d:10.1007_s11135-017-0624-2
    DOI: 10.1007/s11135-017-0624-2
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    Cited by:

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    2. Zhangqi Zhong & Lingyun He, 2022. "Macro-Regional Economic Structural Change Driven by Micro-founded Technological Innovation Diffusion: An Agent-Based Computational Economic Modeling Approach," Computational Economics, Springer;Society for Computational Economics, vol. 59(2), pages 471-525, February.
    3. Crespi, Gustavo & Figal Garone, Lucas & Maffioli, Alessandro & Stein, Ernesto, 2020. "Public support to R&D, productivity, and spillover effects: Firm-level evidence from Chile," World Development, Elsevier, vol. 130(C).
    4. G. A. Untura, 2023. "The Knowledge Economy and Digitalization: Assessing the Impact on Economic Growth of Russian Regions," Regional Research of Russia, Springer, vol. 13(3), pages 397-406, September.
    5. Jan Ženka & Ondřej Slach & Igor Ivan, 2020. "Spatial Patterns of Knowledge-Intensive Business Services in Cities of Various Sizes, Morphologies and Economies," Sustainability, MDPI, vol. 12(5), pages 1-19, March.
    6. Alexander Chepurenko & Maria Kristalova & Michael Wyrwich, 2019. "Historical and Institutional Determinants of Universities’ Role in Fostering Entrepreneurship," Foresight and STI Governance (Foresight-Russia till No. 3/2015), National Research University Higher School of Economics, vol. 13(4), pages 48-59.
    7. Jiangfeng Hu & Zhao Wang & Qinghua Huang & Xiaoqin Zhang, 2019. "Environmental Regulation Intensity, Foreign Direct Investment, and Green Technology Spillover—An Empirical Study," Sustainability, MDPI, vol. 11(10), pages 1-15, May.
    8. Manli Cheng & Zhen Shao & Changhui Yang & Xiaoan Tang, 2019. "Analysis of Coordinated Development of Energy and Environment in China’s Manufacturing Industry under Environmental Regulation: A Comparative Study of Sub-Industries," Sustainability, MDPI, vol. 11(22), pages 1-20, November.
    9. Sihui Zhang & Yong Sun & Xuzhou Yu & Yafeng Zhang, 2023. "Geographical Indication, Agricultural Products Export and Urban–Rural Income Gap," Agriculture, MDPI, vol. 13(2), pages 1-16, February.
    10. Sharafat Ali & Haiyan Xu & Najid Ahmad, 2021. "Reviewing the strategies for climate change and sustainability after the US defiance of the Paris Agreement: an AHP–GMCR-based conflict resolution approach," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(8), pages 11881-11912, August.
    11. Cristian Barra & Nazzareno Ruggiero, 2022. "How do dimensions of institutional quality improve Italian regional innovation system efficiency? The Knowledge production function using SFA," Journal of Evolutionary Economics, Springer, vol. 32(2), pages 591-642, April.
    12. Stepan Zemtsov & Maxim Kotsemir, 2019. "An assessment of regional innovation system efficiency in Russia: the application of the DEA approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 120(2), pages 375-404, August.

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    More about this item

    Keywords

    Innovation; Knowledge spillovers; Russian regional analysis;
    All these keywords.

    JEL classification:

    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes

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