MACRODYNAMIC INTERRELATIONSHIPS AND INTERSECTORAL SHOCK TRANSMISSION EFFECTS IN THE ECONOMY OF UKRAINE

Keywords: shock transmission, production networks, intersectoral linkages, input–output tables, structural policy, Ukraine’s economy, transformation

Abstract

This paper examines shock transmission mechanisms in the inter-sectoral production network of the Ukrainian economy during 2015–2023, focusing on the structural break caused by the full-scale Russian invasion in 2022. The empirical basis is a balanced panel of 42 NACE Rev.2 subsectors. PVAR results identify two main channels: the multiplier channel, where lagged changes affect multiplier dynamics, systemic importance, and network centrality, indicating mean reversion with path-dependent reinforcement; and the backward linkage channel, where increased upstream dependency reduces a sector’s capacity to generate systemic impulses. Correlation analysis confirms that network position is the key determinant of systemic influence, with PageRank showing the strongest association. Impulse response functions reveal persistent and heterogeneous dynamics: systemic shocks are highly persistent; forward-linkage shocks exhibit an initial dispersion effect followed by delayed amplification; and PageRank shocks demonstrate self-reinforcing growth. Structural stability tests reject parameter constancy (Chow test, p < 0.05), confirming a significant break in 2022, while OLS-CUSUM does not indicate gradual drift, suggesting a discrete exogenous shock. Sectoral analysis shows a substantial reconfiguration of network roles, with industries shifting between peripheral and core positions due to wartime demand and supply disruptions. Network centrality becomes increasingly polarised after 2022, and its relationship with systemic impact strengthens, indicating the growing importance of structural position in shock propagation. The study contributes by applying panel VAR with network metrics, identifying asymmetries between forward and backward linkages, quantifying war-induced structural change, and validating the Systemic Impact Index as a predictor of spillovers. The results inform the identification of key sectors for industrial policy and post-war reconstruction, highlighting the need to update pre-2022 input–output-based multipliers.

References

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Im K. S., Pesaran M. H., Shin Y. (2003). Testing for unit roots in heterogeneous panels. Journal of Econometrics, vol. 115(1), рр. 53–74. DOI: https://doi.org/10.1016/S0304-4076(03)00092-7

Chow G. C. (1960) Tests of equality between sets of coefficients in two linear regressions. Econometrica, vol. 28(3), рр. 591–605. DOI: https://doi.org/10.2307/1910133

Brown R. L., Durbin J., Evans J. M. (1975) Techniques for testing the constancy of regression relationships over time. Journal of the Royal Statistical Society: Series B, vol. 37(2), рр. 149–163. DOI: https://doi.org/10.1111/j.2517-6161.1975.tb01532.x

Rasmussen P. N. (1956) Studies in inter-sectoral relations. Copenhagen: Einar Harcks Forlag, 217 р.

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Published
2026-05-15
How to Cite
Telnova, H., & Ozhelevskaya, T. (2026). MACRODYNAMIC INTERRELATIONSHIPS AND INTERSECTORAL SHOCK TRANSMISSION EFFECTS IN THE ECONOMY OF UKRAINE. Sustainable Development of Economy, (2 (59), 579-586. https://doi.org/10.32782/2308-1988/2026-59-79