ECONOMETRIC MODELING OF REGIONAL INDUSTRIAL STRUCTURE OPTIMIZATION: EVIDENCE FROM KASHKADARYA REGION, UZBEKISTAN

Abstract

This study develops an integrated econometric framework for evaluating and optimizing the industrial structure of the Kashkadarya region, Uzbekistan. Using panel data from 148 industrial enterprises over the period 2018–2023, the research applies a System Generalized Method of Moments (GMM) estimator alongside structural shift-share analysis, Herfindahl–Hirschman Index (HHI) decomposition, and linear programming optimization. The findings reveal that the regional industrial structure is moderately concentrated (HHI = 2,840) and dominated by the chemical and petrochemical sector (31.4%), with machinery manufacturing accounting for 25% of total output. The Structural Shift Index (SSI = 0.12) indicates incremental structural transformation rather than abrupt sectoral reallocation. GMM estimates confirm that digitalization investment (β = 0.341, p = 0.016) and export volume (β = 0.447, p < 0.001) are the primary determinants of total factor productivity at the firm level. Scenario projections for 2025–2030 demonstrate that the innovative scenario—combining cluster policy, digital technology adoption, and green manufacturing standards—could raise industrial output to 42,000 billion soum by 2030, reduce HHI to 1,450, and increase the share of high-value-added products in exports from 41% to 68%. These results provide a replicable methodological template for regional structural policymaking in transition economies.