Improving the methodology for calculating the average statistical market price of agricultural land
Year: 2025
Type: article
Abstract: Accurate determination of agricultural land market price was essential for informed economic decisions, yet traditional statistical methods demonstrated unacceptably high discrepancies due to statistical outliers and market structural features. The aim of the study was to develop and validate an improved methodology for calculating the market price of agricultural land that ensured stability and reliability of results through the comprehensive application of multi-level data filtering and an adaptive weighting system. The proposed methodology achieved a threefold reduction in price estimate variability (coefficient of variation 17.2% vs. 54% for traditional methods), while maintaining high representativeness of the sample, this ensured more reliable market price calculations. The analysis revealed that traditional methods produced results ranging from 40.4 to 62.2 thousand UAH per hectare with an amplitude of fluctuations of 54%, whereas the developed methodology provided an estimate of 50.3 thousand UAH per hectare with a coefficient of variation of 17.2%, indicating a threefold improvement in estimation stability. Monthly analysis confirmed the methodology’s resilience to seasonal fluctuations and varying intensities of market activity, revealing a price growth trend of 9.3% over 2024-2025 period. Comparison with official calculations of the State Service of Ukraine for Geodesy, Cartography and Cadastre showed a systematic deviation within 17.8%, reflecting objective methodological differences in approaches to processing market information. The practical value of the developed methodology lies in its applicability for analysing the goals of land market monitoring, valuation activities, and state regulation of land relations
Source: Ekonomika APK
Author: Ihor Yurchenko
Language: English
Topic: Land Use and Management
Field: Social Sciences
Domain: Social Sciences
SDG: Zero hunger
Open Access status: hybrid
OpenAlex ID: W7139028829
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