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The development of agriculture in Russia is a high-priority task. Implementation of “Digitalization of Agriculture” program by 2021 will allow solving a number of problems existing in this industry (food security of the country, export potential increase, etc.) and creating a high-tech branch. One of the directions of “Digitalization of Agriculture” program at the regional level is “smart sectoral planning” which will allow optimizing farmer’s activities when making a decision under the conditions of limited time. Currently, digitalization of agriculture in our country is at a low level. There is a lack of scientific and practical knowledge on technologies and methods in this field, a low level of forecast prices for agricultural products, etc. Let us consider the issue of adaptive forecasting in agricultural sector. The real processes in this industry take place in changing conditions, so the economic system has to adapt to them. The model describing economic system behavior will constantly adapt to the economic process. Adaptive forecasting methods allow building a class of self-adjusting models of economic systems that are able to reflect dynamic, changing over time processes in regional agricultural sector, to highlight the most significant parameters and to give fairly accurate forecasts of processes in future. The goal of this paper is to study using of adaptive methods for forecasting in the agricultural sector of the region. Using the data on the agricultural sector efficiency in certain region (Lipetsk Region), we show the mechanism of action of naive, adaptive and rational expectations models. As economical time series, statistical data were used on agricultural sector efficiency in the Lipetsk region – profitability level, parameters for output technological efficiency. As a result of studying the mechanism of action of naive, adaptive and rational models, conclusions were drawn about the feasibility of the wide acceptance of adaptive method for forecasting in the agricultural sector of the region as one of the factors for digital agriculture development. Keywords—adaptive model, naive expectations model, rational model, profitability level of agricultural products, parameters of technological efficiency of agricultural production.

Digital models of naive, adaptive and rational expectations of regional agriculture forecasting