The algorithm calculates a socio-environmental transformation index in agriculture, highlighting economic drivers and implications.
The article develops an algorithm for collecting data necessary to calculate a complex index of socio-ecological transformation in agriculture. Statistical analysis, using this composite index, allows identifying regions (organizations) that are drivers of economic growth and lagging regions. Such differentiation has practical significance for pursuing targeted agricultural policies, aimed at addressing social issues and reducing environmental damage, caused by the industry. The paper analyzes forms of statistical reporting in agriculture, that enable obtaining data on social conditions and environmental state. The research methods used include analytical, comparative, tabular, graphical with subsequent generalization of data, as well as other research techniques. The results of this study are significant for improving statistical monitoring in agriculture and enhancing the efficiency of data collection.
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В. С. Токарев (2025) studied this question.
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