EVALUATION OF THE PROCESS OF INFRASTRUCTURE DEVELOPMENT IN THE REGION BASED ON ECONOMETRIC MODELS
Keywords:
Infrastructure, Econometric Models, Regional Development, FMOLS, SVAR, Spatial Spillovers, Public Investment, Private Investment, Energy Infrastructure, Transport Connectivity.Abstract
This research provides a rigorous quantitative assessment of the nexus between infrastructure capital stock and regional economic performance, focusing on a global panel of 45 emerging economies (2000–2020) and a sub-regional analysis of the Volga Federal District. Grounded in an infrastructure-augmented Cobb-Douglas production function, the study utilizes Fully Modified Ordinary Least Squares (FMOLS), Structural Vector Autoregressive (SVAR) models, and the Spatial Durbin Model (SDM) to estimate elasticities and capture spatial spillovers. To address inherent endogeneity, Dynamic System-GMM serves as the primary dynamic estimator. Findings indicate a significant positive impact on growth, with static infrastructure elasticity ranging from 0.24 to 0.31. Long-run panel estimates reveal a more substantial elasticity range of 1.08 to 1.23, with an annual error correction speed of 27% toward equilibrium. Sectoral decomposition identifies telecommunications (0.156) and transport (0.142) as the most potent growth drivers, significantly outperforming energy (0.098). Temporal analysis suggests a partial recovery in infrastructure efficacy post-2013 (0.246) following the 2008–2012 crisis period (0.201). The study concludes that while infrastructure contributes 1.2–1.8 percentage points to annual GDP growth, outcomes are mediated by institutional quality and spatial externalities.
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