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    Simulation Model of the Formation and Development of the All-Russian Agrarian Commodity Market in the Second Half of the 18th – Early 20th Century
    (Чехія: European Political and Law Discourse, 2024) Polovyi M.
    The paper analyzes the model of the grain balance’s dynamics in different regions and assesses the efficiency and development of the grain market during 18-19 centuries. It is stated, that in the context of annual grain transportation the overall yearly import and export of grain to and from a region are influenced by the surplus and shortage of grain in various areas. Regions with more than 5% surplus of grain are identified as exporting regions, while those with more than 5% shortage are identified as importing regions. Among the main factors affecting grain trade are the model accounts, the transportation distance, transportation capabilities, epidemic situations, money supply sufficiency, government trade policies, and international trade conditions. The model’s effectiveness was tested by comparing model-derived optimal trade scenarios with actual historical data over a 55-year period (1802-1856). It is stated, that the model was found to adequately describe the grain export dynamics to foreign countries in at least 72% of cases. Regional grain balances in 18-19 centuries were assessed. It is revealed, that grain production and consumption varied greatly due to unstable agricultural yields and changing population demands. Surplus grain was often exported even from regions with overall negative grain balances by reducing local consumption or using lower-quality substitutes. Market development over time characterized with the features: 1) from the 1830s onwards, there was a noticeable improvement in the grain market as more regions could consistently export grain, leading to a more interconnected market; 2) by the late 19th century, interregional grain trade became more active, indicating a well-developed market. The comparison between the optimal model and actual historical data helps identify discrepancies and understand the development level of the grain market. It is proved, that the model’s strength lies in its ability to work with estimated values and limited precise data, providing a robust tool for historical economic analysis.