Identifying priorities for agricultural development in Russia’s Ural federal district: a spatial modeling approach

Ilya V. Naumov, Natalia L. Nikulina

Abstract


Relevance. Food security and balanced territorial development rank among Russia's foremost strategic priorities. Yet in the Ural Federal District (UFD), growing spatial polarization in agricultural production is widening regional disparities and undermining these goals. Identifying where and how to develop the agricultural sector across the UFD's municipalities is therefore a challenge of direct policy importance.

Research objective. This study aims to identify and substantiate promising spatial directions for agricultural development in the municipalities of Russia's Ural Federal District, using a methodological approach developed by the authors for assessing and modeling spatial development priorities at the macroregional level.

Data and methods. The study draws on the official Rosstat data for 198 municipalities over the period 2012–2022. A central contribution of the research is the development and testing of an original methodological approach to assessing and modeling spatial development priorities at the macroregional level. The approach is built on the sequential application of spatial statistical methods: Moran and Anselin indices are first employed to identify clusters and zones of influence, thereby characterizing the existing structure of agricultural production; a spatial autoregressive lag model (SAR) is then applied to validate the effectiveness of the proposed priorities. The novelty of the approach lies in the systematic combination of spatial autocorrelation analysis across multiple spatial weight matrices with spatial autoregressive modeling, allowing for a rigorous assessment of spatial effects within the macroregion.

Results. Application of the methodological framework identified both established and emerging agricultural growth poles within the UFD, characterized respectively by high existing output volumes and significant development potential. The spatial influence zones surrounding these poles were also delineated, forming the empirical basis for the study's strategic recommendations.

Conclusions. The study establishes that agricultural development in the UFD should prioritize the formation of new growth poles and the strengthening of cooperative linkages within their influence zones. The findings provide both a theoretical foundation and practical guidance for government bodies seeking to reduce spatial disparities in agricultural production and enhance regional food security.


Keywords


spatial development priorities, spatial autocorrelation analysis, SAR model, spatial interactions, municipalities, agriculture

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References


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DOI: https://doi.org/10.15826/recon.2026.12.2.011

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