Theoretical Aspects of Assessing the Operational Efficiency of The Grain Farming Sector Under Global Climate Change
DOI:
https://doi.org/10.55640/jme-06-06-06Keywords:
Grain farming efficiency, climate change, data envelopment analysisAbstract
This article presents a comparative theoretical examination of five leading methodologies employed in assessing the operational efficiency of the grain farming sector under conditions of global climate change: Data Envelopment Analysis (DEA), Stochastic Frontier Analysis (SFA), Total Factor Productivity (TFP), Ricardian Analysis, and the Computable General Equilibrium model (CGE). The study employs a theoretical-synthetic approach, utilizing a systematic literature review and a multi-criteria evaluation matrix to compare the methodologies in terms of their effectiveness under conditions of climate variability, data requirements, level of analysis, and policy relevance. The research finds that the direct application of standard methodologies to Uzbekistan’s conditions - without appropriate adaptation - may yield misleading conclusions due to the country’s distinctive ecological and institutional characteristics, including the Aral Sea crisis, water scarcity, soil degradation, and small-scale farm structures. Drawing on the experiences of Kazakhstan, India, and Turkey, the study recommends a three-tier methodological framework for Uzbekistan: descriptive analysis with partial factor productivity; climate-augmented SFA and meta-frontier analysis for farm-level efficiency assessment; and dynamic productivity change measurement using the Malmquist index. The proposed framework enables a unified assessment of efficiency from the farm level to the macroeconomic level and serves as a critical methodological foundation for substantiating food security policy.
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