ECONOMETRIC MODELS OF FOOD INDUSTRY DEVELOPMENT IN THE AGRO-CLUSTER SYSTEM

Agro-clusters represent integrated spatial networks that enhance agricultural efficiency and regional growth through production, processing, and marketing synergies. This article reviews key econometric models—including production frontiers, SFA/DEA, spatial autoregression, causal inference, and CGE—for evaluating TFP, spillovers, and optimization. Standardized variables like locational entropy and inputs/outputs are examined, alongside mechanisms such as agglomeration and technology diffusion. Empirical evidence highlights 12-20% TFP gains in clusters, with policy implications for developing economies like Uzbekistan. Limitations and future integrations with machine learning are discussed.