Methodology for calculating the diversification of non-traditional agricultural and alternative activities in rural areas

This study identifies key determinants of successful diversification processes within the Russian agrarian economy, emphasizing the significance of institutional frameworks, infrastructure access, and human capital levels. A comparative analysis of methodological approaches to the classification of rural territories facilitates the delineation of parameters shaping their socio-economic profiles. Leveraging a synthesis of economic, environmental, and demographic indicators, we develop an original typology of Federation subjects, accounting for the nuances of inter-industry linkages. Applying input-output analysis, specifically utilizing statistical “Input-Output” tables, enables a quantitative assessment of technological coefficients for intermediate consumption across 33 regions. The methodological framework presented herein is predicated on calculating the proportion of each product type within the structure of intermediate consumption, enabling the quantification of indirect impacts from related industries on the development of tourism clusters within specific localities. Empirical validation of this approach, utilizing application documentation from the “Agritourism” grant program in the Republic of Buryatia for 2022, demonstrates the capacity to forecast multiplicative effects with a planning horizon extending to 2030. Results from the calculations indicate that each ruble of public investment in rural tourism infrastructure generates 2.3 rubles of value added within associated economic sectors. Integrating these findings into the authors’ typology of rural territories reveals four distinct clusters, characterized by differing diversification potential: ranging from agroindustrial hubs with high multiplicative effects to economically depressed zones necessitating targeted interventions. The proposed classification underpins the formulation of differentiated state policy measures designed to mitigate interregional disparities and stimulate endogenous growth drivers. Cross-regional analysis supports the hypothesis of a positive correlation between the degree of diversification and the dynamics of regional gross domestic product. The developed methodological toolkit holds potential for future adaptation in the design of digital models, facilitating the prediction of long-term impacts resulting from the adoption of innovative practices within the agricultural sector.

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