Assessment of the effectiveness of smart specialization instruments for diversifying regional economies and enhancing their resilience to external shocks and technological disruptions

Abstract

The article is devoted to the quantitative assessment of the effectiveness of smart specialization instruments as a mechanism for diversifying regional economies and increasing their resilience to external shocks and technological disruptions. The purpose of the study is to empirically test, based on panel data from 85 regions for 2015–2023, the hypothesis about the nonlinear and lagged nature of the influence of smart specialization strategies on GRP growth rates, budget revenue volatility, value-added structure, and technological independence. The empirical base includes 12,450 observations on GRP structure indicators, innovation activity, government support measures, and financial sustainability, deflated to the base year 2015; the methodological framework comprises fixed-effects models and dynamic Arellano–Bond GMM, difference-in-differences with pseudorandomization (propensity score matching), k-means clustering, calculation of diversification indices (HHI, entropy), and the development of a stress-testing model for scenarios of external demand decline and supply chain disruption. It is shown that regions leading in the implementation of smart specialization instruments demonstrate a 22.11% decrease in the Herfindahl–Hirschman index, minimal volatility of tax revenues (coefficient of variation 0.0845), and higher GRP growth rates compared with inertial and resource-dependent regions, while the formal presence of strategies without real resources does not yield a statistically significant effect. It was found that the effectiveness of budgetary investments is determined by the volume of private capital attraction: when the share of extra-budgetary co-financing exceeds 40%, the budget multiplier and ROI of investments in competence centers, technoparks, and R and D grants grow exponentially, reaching a multiplier of 3.73 and an ROI of 273% in the innovation hubs cluster. The analysis of adaptation to technological shocks in 2022–2023 shows that regions with deep localization within smart specialization are characterized by the smallest peak output decline (-3.45%), the highest import substitution rates, and the shortest recovery period (2.4 quarters), whereas import-assembly models exhibit significant declines and slow adaptation. Factor analysis reveals the key role of institutional maturity: about 60% of the variation in outcomes is explained by the quality of governance and the accuracy of priority selection, while the volume of funding determines only about 40% of the effect; the integrated model links the smart specialization index to long-term economic resilience with a determination coefficient of 0.78. It is concluded that smart specialization instruments serve as an effective but inertial tool of meso-level policy, requiring a time horizon of at least 3–5 years, a shift of focus from formal growth indicators to metrics of diversification, technological independence, and co-financing, as well as the use of obtained threshold values for adjusting regional strategies and federal support mechanisms.