Econometric modeling of spatial innovation development in the context of institutional factors

Objective: to identify and analyze the spatial mechanisms of the influence of key socio-economic and institutional factors on the innovative development of Russian regions in the context of Veblen dichotomy.
Methods: the study is based on 2017-2023 panel data for the Russian regions. Classical regression models (POLS, FE, RE) and a range of spatial econometric models (SEM, SAR, SAC, SDM) were used to test the hypotheses, allowing for spatial autocorrelation and overflow effects. Using the decomposition of effects in Spatial Durbin Model (SDM), the direct and indirect (neighborhood) effects of factors were estimated.
Results: the study confirmed that innovation activity enjoys a significant positive impact of instrumental factors, such as industrial production and educational potential, as well as a negative impact of ceremonial factors, such as social inequality and unemployment. The authors revealed a significant positive spatial dependence of innovation activity (λ > 0), indicating the presence of an “infection” effect between neighboring regions. At the same time, the quantitative assessment showed that direct (intraregional) effects predominate, while indirect overflow effects turned out to be statistically insignificant.
Scientific novelty: for the first time, the conceptual apparatus of Veblen dichotomy was integrated with modern tools of spatial econometrics for the Russian regions. It allowed quantifying the mechanisms of institutional structures’ influence on innovation dynamics, taking into account spatial interactions.
Practical significance: the results obtained can be used to adjust regional policy aimed at reducing social inequality and increasing innovation potential, taking into account institutional barriers and development resources.

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